Category: 8. Health

Introduction

The elderly population has been rapidly expanding in Japan, which has the most aging society in the world.¹ The ageing of populations leading to an increase in the prevalence of frailty. Frailty is a geriatric syndrome that can be vulnerable to stressors due to a decline in multiple organ function.² Frailty is highly associated with chronic obstructive pulmonary disease (COPD).^3,4 The prevalence of frailty is 32.1% in patients with COPD.⁵ Frailty leads to poor health outcomes in COPD, such as disability, hospitalization, and death.^6–8

The high prevalence of multimorbidity in COPD, including diabetes, cardiovascular diseases, chronic kidney disease, osteoporosis, and sarcopenia, is a key component of frailty in patients with COPD.⁹ Recently, a concept of syndemic, the occurrence of chronic disease clusters including COPD with shared risk factors (eg, ageing, smoking, and inactivity) and biological interactions, has been proposed to manage COPD with a multidisciplinary approach in the context of multimorbidity, moving away from considering COPD as just a single chronic respiratory disease.¹⁰

COPD is closely related to cardiovascular diseases as part of the complex interaction between multimorbid diseases. Compared with the general population, patients with COPD have a higher risk of developing major adverse cardiovascular events (MACE), including acute coronary syndrome (ACS), heart failure (HF), and stroke.^11,12 The underlying mechanisms between COPD and MACE are hyperinflation of the lungs, endothelial dysfunction, hypoxemia, sympathetic hyperactivity, hypercoagulability, and systemic inflammation.^13–17 MACE is a leading cause of mortality in COPD.¹⁸ Nonetheless, cardiovascular diseases are often undiagnosed and undertreated in patients with COPD, leading to worse outcomes.¹⁹

The identification of patients with COPD at risk for MACE is a cornerstone for reducing cardiovascular events and achieving healthy longevity in patients with COPD. Previous studies have demonstrated that frailty is a risk factor for poor prognosis in patients with cardiovascular disease.^20,21 However, the impact of frailty on MACE in patients with COPD remains unknown. In this multicenter, longitudinal, and population-based study, we aimed to evaluate the long-term association between frailty and MACE in patients with COPD using routinely collected clinical data from Sado-Himawari Net, a regional electronic health record (EHR) system in Sado City, Niigata Prefecture, Japan.

Material and Methods

Data Source

We used a routinely collected medical database from Sado-Himawari Net, an EHR system in Sado City, Niigata Prefecture, Japan. This regional EHR system was launched in April 2013 to facilitate cooperation between medical and long-term care resources and to effectively utilize the limited medical resources in the city. This EHR system covers the entire area of Sado across 81 facilities, including hospitals, medical clinics, dental clinics, pharmacies, nursing facilities, and health centers. This EHR system is based on common exchange protocols, such as Health Level Seven International (HL7) and Fast Healthcare Interoperability Resources (FHIR). The medical database includes information on age, sex, diseases, treatments, laboratory tests, and medical image data. All tables show consistent ID numbers for each patient across the tables. Data cleaning and pre-processing were conducted using Python package pandas (version 2.2.2). A total of 17,205 people living in Sado City participated in Sado-Himawari Net in March 2023. The geographical characteristics of Sado city, being on an isolated island (Sado island), lead to a small migration of people in this regional EHR system. Overall, healthcare in Sado City is covered within the regional EHR network system. Sado-Himawari Net continuously collects medical databases over time (every day) from 81 medical facilities across the entire area of this region (Sado city). These characteristics of this EHR system enable a continuous and longitudinal evaluation of clinical outcomes in a small population lost to follow-up in this cohort. We confirm that the data accessed complied with relevant data protection and privacy regulations.

Study Design and Participants

This was a retrospective multicenter longitudinal study. The study period was April 2013 to March 2023. A schematic representation of the study is illustrated in Figure 1. Patients in Sado-Himawari Net database were recruited for this study. Patients with COPD were identified using the corresponding codes from the International Statistical Classification of Diseases and Related Health Problems, 10th revision (ICD-10), J42, J43, and J44 (any position). The eligibility criteria were patients with COPD diagnostic codes at least twice and subjects aged 40 years. The index date was defined as the earliest date of COPD diagnosis. The accuracy of these specific codes for COPD diagnosis was validated in previous reports, with a positive predictive value of 85.2–90.8% by COPD diagnostic codes alone.^22–25 We obtained the occurrence of MACE and the time to first MACE. The end of the follow-up period was defined as follows: (i) the date of the first MACE for patients with MACE, (ii) March 2023 (the end of the study period) for patients without MACE, or (iii) the date of loss to follow-up from Sado-Himawari Net. Demographic data, such as age, sex, and inhaled treatments for COPD, were collected from the Sado-Himawari Net at baseline (within 1 year prior to the index date). Comorbidities were identified using corresponding ICD-10 codes (Table S1). Comorbidities included hypertension, diabetes, dyslipidemia, chronic kidney disease, sleep apnea syndrome, depression, sinusitis, and asthma. We evaluated COPD exacerbation during the follow-up period. COPD exacerbation was defined as dispensation claims for systemic corticosteroids within 14 days. This study was approved by the ethics review committee of Yamaguchi University Hospital (approval number:2022–023). This study was conducted in accordance with the principles of the Declaration of Helsinki. This study was registered in the UMIN Clinical Trials Registry (UMIN000048551). Informed consent was waived by the ethics committee because of the retrospective nature of the study.

Figure 1 Study timeline. The index date was defined as the date of the earliest diagnostic code for COPD (ICD-10 codes: J42, J43, and 44). The end of follow-up was defined as the date of the first MACE occurrence, loss to follow-up, or March 31, 2023 (the end of the study period). Abbreviations: COPD, chronic obstructive pulmonary disease; ICD-10, International Statistical Classification of Diseases and Related Health Problems, Tenth Revision. MACE, major adverse cardiovascular event.

Frailty Risk Assessment

In the present study, we evaluated the hospital frailty risk score (HFRS) by using hospital administrative data at baseline as a measure of frailty risk. We calculated the HFRS for individual participants according to the methods described by Gilbert et al.²⁶ HFRS is a frailty assessment tool using 109 ICD-10 diagnostic codes from a health administrative database. Briefly, each ICD-10 code was assigned a score, and HFRS was calculated as the sum of scores for ICD-10 codes that the subjects had received during the hospital visits. The HFRS is a well-validated risk score for frailty that is associated with hospitalization, length of hospitalization, disability, and death. The frailty scores were classified into four categories: no-frailty with HFRS=0, low with HFRS >0 and <5, intermediate with HFRS ≥5 and <15, and high with HFRS ≥15, as previously defined.²⁶ No ICD-10 codes for calculating HFRS were included in the specific codes for the definition of individual MACE.

Outcome Measurements

The time to the first MACE was evaluated. MACE were defined as ACS, HF, or stroke occurrence after the index date. We selected ACS, HF, and stroke because these three were the most utilized MACE endpoints.²⁷ In all participants, we defined individual MACE (ie, ACS, HF, and stroke) by a combination of both ICD-10 codes and medications that were specific to the respective MACE, as previously described.^28–30 ACS was defined as ICD-10 codes I20, I21, I22, I23, and I24 (codes for acute myocardial infarction and unstable angina) with antiplatelet agents. We defined HF using ICD-10 codes I50, I11.0, I13.0, and I13.2 (diagnostic codes for HF) for diuretics and/or cardiotonic drugs. Stroke was defined as ICD-10 codes I63 and I64 (specific codes for cerebral infarction occurrence) with medications for stroke (brain-protective drugs, antiplatelet agents, and/or anticoagulant drugs). The definitions of individual MACE (ACS, HF, and stroke) are detailed in Table S2.

Statistical Analysis

In this study, we describe the numerical variables using the mean and standard deviation for each value. The incidence of MACE for each frailty category (ie, no-frailty, low, intermediate, and high) was calculated in patients with COPD using the Kaplan–Meier method, and differences were compared using the Log rank test with Python package lifelines (version 0.29.0). We applied a multivariate Cox proportional hazard model to evaluate whether these frailty categories were independently associated with MACE, with adjustment for confounding factors such as age, sex, comorbidities (hypertension, diabetes, dyslipidemia, chronic kidney disease, sleep apnea syndrome, depression, sinusitis, and asthma), and inhaled treatments for COPD (ie, inhaled corticosteroids, long-acting β2 agonists, and/or long-acting muscarinic antagonists). We calculated hazard ratios (HR) and corresponding 95% confidence intervals (CIs) for the time to first MACE in the frailty categories (ie, no-frailty, low, intermediate, and high) using the Cox proportional hazard model. Patients were censored if they experienced any MACE or were lost to follow-up. Statistical analyses were performed using the SciPy package (version 1.7.3) in Python. All statistical tests were two-sided, and statistical significance was set at p < 0.05.

Sensitivity Analysis

We performed two sensitivity analyses to confirm the potential association between frailty and MACE in COPD patients. First, we performed a sensitivity analysis excluding patients who experienced COPD exacerbations during the observational period to verify whether the association between frailty and MACE was independent of COPD exacerbations. Second, we performed a sensitivity analysis to adjust for airflow limitation severity (ie, Global Initiative for Chronic Obstructive Lung Disease [GOLD] grade 1–4) in addition to age, sex, inhaled treatments, and comorbidities in subjects who underwent spirometry.

Results

Patients’ Demographics

A total of 1527 patients with COPD were enrolled from Sado-Himawari Net (Figure 2). The mean age was 79.2 years old (SD 10.0) and 691 patients (45.3%) were female (Table 1). The proportion of male was higher in patients with COPD with MACE than in those without MACE. The number (proportions) of patients in each frailty category (no-frailty, low, intermediate, and high) were 230 (15.1%), 702 (46.0%), 519 (34.0%), and 76 (5.0%), respectively (Table 2). Participants with a higher frailty risk were older than those with a lower frailty risk.

Table 1 Baseline Characteristics of COPD Patients with and without MACE During the Follow-up Term

Table 2 Baseline Characteristics of Patients with COPD Stratified by Frailty Categories

Figure 2 Flow diagram of the inclusion/exclusion of COPD participants in this study. For the analysis of the present study, a total of 1527 patients with COPD were enrolled. Abbreviations: COPD, chronic obstructive pulmonary disease; ICD-10, International Statistical Classification of Diseases and Related Health Problems, Tenth Revision.

Clinical Outcomes

Table 3 shows cumulative proportions of occurring any MACE and individual MACE (ie, ACS, HF, and stroke) in all subjects and subjects in each frailty category: no frailty, low, intermediate, and high. A total of 363 (23.8%) patients with COPD experienced MACE during the 10-year follow-up. The number (proportion) of subjects with ACS, HF, and stroke occurrence were 113 (7.4%), 155 (10.2%), and 195 (12.8%), respectively (Table 3). The higher HFRS groups (eg high with HFRS≥15 points) showed a more frequent occurrence of any MACE.

Table 3 The Proportion of Major Adverse Cardiovascular Events Stratified by Frailty Categories During the 10-Year Follow-up

The Association Between Frailty and Risk of MACE Occurrence

The severity of frailty, as evaluated by the HFRS, was significantly associated with an increased risk of a composite of MACE occurrence in patients with COPD. Figure 3 shows the cumulative incidence curve of any MACE in the subjects during the 10-year follow-up period. Patients with COPD and a higher HFRS score showed a higher proportion of MACE (log-rank p<0.001). In the Cox proportional hazard model adjusted for age, sex, inhaled treatments, and comorbidities, frailty categories were significantly associated with MACE occurrence as follows: no-frailty versus low HFRS (HR 1.47 [95% confidence interval, 1.01–2.14], p<0.05), intermediate HFRS (HR 2.00 [1.34–2.97], p<0.001), and high HFRS (HR 2.62 [1.50–4.59], p<0.001) (Table 4).

Table 4 Cox Multivariate Proportional Hazard Ratio for MACE in Patients with COPD (n=1527)

Figure 3 The Kaplan–Meier curves show cumulative incidence of MACE (any of acute coronary syndrome, heart failure, and stroke) in COPD patients in four frailty categories: No-frailty, HFRS=0 (blue line); low, HFRS >0 and <5 (green line); intermediate, HFRS ≥5 and <15 (Orange line); high, HFRS ≥15 (red line). Abbreviations: MACE, major adverse cardiovascular events; COPD, chronic obstructive pulmonary disease; HFRS, hospital frailty risk score.

Sensitivity Analysis

The association between frailty and MACE in patients with COPD was generally consistent with the sensitivity analysis.

Even when including only patients without COPD exacerbations during the follow-up period (n=1339), COPD patients with a higher HFRS category had a higher incidence of MACE (Figure S1). In the multivariable analysis adjusted for age, sex, inhaled treatments, and comorbidities in this sub-population, the association between frailty and MACE remained statistically significant as follows: no-frailty versus low HFRS (HR 1.49 [1.01–2.18]), p<0.05); intermediate HFRS (HR 1.98 [1.32–2.98], p<0.005), and high HFRS (HR 2.48 [1.39–4.42], p<0.005), respectively (Table S3).

Similarly, in the subgroup of patients with spirometry (n=514), COPD patients with a higher HFRS category had a higher incidence of MACE (Figure S2). The association between HFRS and MACE was consistent even after adjusting for the severity of airflow limitation in the COPD subpopulation who underwent spirometry (n=514). After adjusting for the severity of airflow limitation by GOLD classification (ie GOLD 1–4) in addition to age, sex, inhaled treatments, and comorbidities, the association between frailty categories and MACE occurrences remained statistically significant as follows: no-frailty versus low HFRS (HR 1.31 [0.76–2.26]), p=0.33), intermediate HFRS (HR 2.08 [1.17–3.68], p<0.05), and high HFRS (HR 3.37 [1.35–8.43], p<0.05), respectively (Table S4).

Discussion

Utilizing routinely collected clinical data from the EHR system during the 10-year follow-up, we demonstrated that frailty, assessed using HFRS, was associated with a higher proportion of MACE (a composite of ACS, HF, or stroke) in Japanese patients with COPD. Frailty was independently associated with MACE in patients with COPD, even after adjustment for age, sex, comorbidities, inhaled treatments, COPD exacerbations, and severity of airflow limitation, although these results might not be generalized to patients in the other countries.

From the results of the sensitivity analysis, we found that frailty was an independent risk factor for MACE in patients with COPD, even after controlling for the effects of COPD exacerbations and airflow limitation severity. COPD exacerbations were highly associated with an increased risk of MACE in previous studies from Japan and other countries.^31–35 Nonetheless, even after excluding subjects who experienced COPD exacerbations during the follow-up period, the association between frailty and MACE in patients with COPD remained significant in the present study. The severity of airflow limitation has also been associated with MACE in previous reports.^36–38 In contrast, even after adjustment for the severity of airflow limitation defined by the GOLD classification (ie, GOLD 1–4) in a sub-population of COPD patients with spirometry, a higher HFRS category was associated with a risk of developing MACE.

To our knowledge, this is the first study to demonstrate a long-term association between frailty assessed by HFRS and the risk of developing MACE in patients with COPD, although HFRS is not a physical frailty assessment tool like Fried phenotype which can be prevented by rehabilitation and nutrition. Previous studies have shown that frailty is associated with worse outcomes in patients with pre-existing cardiovascular diseases. Previous study demonstrated that physical frailty measured by Fried phenotype was associated with a poor prognosis in patients with preexisting cardiovascular diseases.²⁰ Another previous prospective study showed that a multi-domain frailty (physical, social, and cognitive domain) was a prognostic factor of cardiovascular outcomes in patients with chronic heart failure.²¹ The frailty assessed by HFRS was related to poor prognosis following stroke and transient ischemic attack.³⁹ The results of the present study are in line with these previous reports. Taken together with the results of our study, these findings reinforce an association between frailty and MACE. The underlying pathophysiological mechanisms linking frailty and MACE are believed to be subclinical atherosclerosis due to oxidative stress, endothelial senescence, and systemic inflammation.^40–42 Furthermore, our study is the first to focus on this association in patients with COPD, while these previous reports showed an association in patients with pre-existing cardiovascular diseases. COPD patients with frailty showed an increased level of senescence-associated secretory phenotype proteins such as interleukine-6 and growth differentiation factor-15,^43,44 which potentially aggravate the association between MACE and COPD. These complicated and mutual interactions between the three conditions (frailty, MACE, and COPD) may be a plausible underlying mechanism linking frailty with COPD and MACE in the present study.

The association between frailty and MACE in COPD provides an opportunity to stratify the cardiopulmonary risk in patients with COPD. The coexistence of COPD and cardiovascular diseases is frequently observed. The coexistence of these two diseases is related to worse outcomes than those of either disease alone. However, cardiovascular diseases are often underdiagnosed and undertreated in COPD patients. Notably, a previous study reported that 70% of COPD patients were underdiagnosed with coronary artery disease identified by electrocardiography.¹⁹ Given the association between frailty and MACE in COPD in this study, a frailty assessment supports the identification of COPD patients with cardiopulmonary risk. Physical frailty assessment tools, such as Fried phenotypes, remain the gold standard for evaluating physical frailty status. However, it is difficult to implement these physical frailty assessments in routine clinical practice, owing to limitations in human resources, time, and space in medical facilities. In contrast, utilizing a readily available frailty screening tool such as HFRS and a patient-reported outcome measurement will help to easily detect COPD patients with frailty.^26,45 Consequently, in COPD patients with frailty, early screening with exercise electrocardiograms and/or cardio-echograms may aid early detection of subclinical cardiovascular risk and personalized intervention to mitigate cardiovascular risk. Further prospective studies are required to verify whether early multidiscipline approaches for COPD patients with frailty will reduce the incidence of MACE and ultimately improve longevity in this population.

As part of the complicated relationship between frailty and multimorbidity conditions, we focused on the association between frailty and MACE in patients with COPD. It is not clear how frailty results in adverse outcomes, including disability, hospitalization, and mortality in patients with COPD. Numerous factors such as environmental factors, social factors, genetic factors, and comorbidities might be synergistically and mutually involved in COPD patients with frailty and their accelerated ageing.⁴⁶ Our results may provide insights into understanding these complicated mechanisms in terms of cardiopulmonary relationships. The relationship between frailty and MACE in this study might explain the worse health outcomes (eg, disability, hospitalization, and mortality) in patients with both COPD and frailty. Further comprehensive approaches across multiple organs are required to understand the complex mechanisms of frailty progression in COPD patients. Tian et al showed that biological aging processes are driven by the multiple organ system network of participants in the UK biobank cohort,⁴⁷ which can be a clue for understanding the complicated mechanisms of frailty progression.

Our study, which used an EHR system, has several strengths. First, the utilization of this regional EHR system enabled a longitudinal assessment of clinical outcomes with a small proportion of loss to follow-up for the following reasons: (i) the geographical characteristics of the EHR system (isolated island, Sado Island, with few migrations); (ii) the healthcare system in this region (completion of the overall healthcare within this regional EHR system); and (iii) continuity of medical database collection in this EHR system (Sado-Himawari Net continuously collects the medical database across 81 medical facilities every day). These characteristics of the EHR system are advantageous in evaluating the natural history of COPD. Second, the regional EHR system used in the present study, Sado-Himawari Net, consists of 81 medical facilities, reflecting a real-world clinical setting. This finding supports the generalizability of our results. Third, using the EHR system, frailty could be automatically evaluated by calculating the HFRS based on ICD-10 codes. Frailty assessment, such as the Fried frailty phenotype in routine clinical practice, is difficult to implement owing to time constraints and limited space and human resources in hospitals. By contrast, the EHR-based frailty assessment HFRS can be automatically obtained using routinely collected ICD-10 codes, which overcomes the challenge of assessing frailty in routine clinical practice. Fourth, owing to the longitudinal nature of Sado-Himawari Net, this EHR system continuously collects routine medical information over time, which enables the calculation of HFRS before the occurrence of MACEs. The time between HFRS calculation and MACE occurrence reinforces the longitudinal association between frailty and MACE in patients with COPD.

This study had several limitations need to be mentioned. First, the mean age of patients with COPD was 79.2 years old in the present study. This older demographic, compared to the broader COPD population, might have influenced the study outcomes. Second, we did not obtain cardiovascular risk factors such as smoking, alcohol history, and body mass index. Third, we used a health administrative database to diagnose diseases, which may lead to misclassification of diseases, including COPD, in the present study, as with all studies using EHR systems. A significant limitation of the present study is that subjects with COPD were recruited based on ICD-10 coding rather than spirometry-defined COPD. Fourth, the rate of inhaled treatment was low in patients with COPD from Sado-Himawari Net, which may have affected our results. This may be because there were no pulmonologists in the medical facilities of the regional EHR system. Nonetheless, the rate of inhaled treatments in the present study was similar to that in previous studies of COPD using the EHR database.^33,48 Fifthly, this study did not include participants without COPD, and did not completely demonstrate the direct interaction between COPD, frailty, and MACE. The further study including subjects without COPD will reinforce this relationship. Finally, we did not exclude patients with MACE prior to the index date, possibly leading to left censoring or truncation. This potential bias in the EHR database might have affected the estimation of HR for MACE in this study. The EHR database was not collected for the purpose of this study, and the results of studies using EHR systems should be interpreted with caution.

Conclusion

In conclusion, we verified the long-term impact of frailty on MACE in patients with COPD during a 10-year follow-up, even after adjustment for age, sex, comorbidities, inhaled treatments, COPD exacerbations, and airflow limitation severity. Frailty assessment may play an important role in the identification of COPD patients at risk of MACE, leading to personalized and early interventions using a multi-discipline approach (eg, pulmonologists and cardiologists). Prevention of frailty progression in COPD may ultimately reduce the cardiopulmonary risk toward healthy longevity.

Data Sharing Statement

Clinical data from Sado-Himawari Net were only available to the participating researchers because the participants of the present study did not agree that their data would be shared publicly.

Ethics Approval and Informed Consent

This study was approved by the ethics review committee of Yamaguchi University Hospital (approval number:2022-023). Informed consent was waived by the ethics committee because of the retrospective nature of the study.

Acknowledgments

We thank Mari Shimizu, Kuniaki Imai, Tetsuo Akita, and Hajime Yokota at Healthcare Relations Co., Ltd. and Kenji Sato at Sado General Hospital for providing the EHR database from Sado-Himawari Net. We also thank Nanami Shiosaki at Yamaguchi University for support in obtaining the EHR database.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Funding

This work was funded by the AstraZeneca K.K. (Externally Sponsored Research Program [ESR-21-21503]). The funder of the study had no role in the study design, data collection, data analysis, data interpretation, or writing of the manuscript.

Disclosure

KH received speaker fees from AstraZeneca, Kyorin Pharmaceutical, Novartis Pharma and Sanofi. KO received speaker fees from AstraZeneca, Boehringer Ingelheim and Sanofi. TH received speaker fees from AstraZeneca, Novartis Pharma and Sanofi. KM received speaker fees from AstraZeneca, Boehringer Ingelheim, GlaxoSmithKline, Kyorin Pharmaceutical, Novartis Pharma and Sanofi. The other authors have no conflicts of interest to declare related to our work.

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31. Matsunaga K, Yoshida Y, Makita N, et al. Increased Risk of Severe Cardiovascular Events Following Exacerbations of Chronic Obstructive Pulmonary Disease: results of the EXACOS‑CV Study in Japan. Adv Ther. 2024;41(8):3362–3377. doi:10.1007/s12325-024-02920-y

32. Yang HM, Ryu MH, Carey VJ, et al. Chronic Obstructive Pulmonary Disease Exacerbations Increase the Risk of Subsequent Cardiovascular Events: a Longitudinal Analysis of the COPDGene Study. J Am Heart Assoc. 2024;13(11):e033882. doi:10.1161/JAHA.123.033882

33. Graul EL, Nordon C, Rhodes K, et al. Temporal Risk of Nonfatal Cardiovascular Events After Chronic Obstructive Pulmonary Disease Exacerbation A Population-based Study. Am J Respir Crit Care Med. 2024;209(8):960–972. doi:10.1164/rccm.202307-1122OC

34. Hesse K, Bourke S, Steer J. Heart failure in patients with COPD exacerbations: looking below the tip of the iceberg. Respir Med. 2022;196:106800. doi:10.1016/j.rmed.2022.106800

35. Hawkins NM, Nordon C, Rhodes K, et al. Heightened long-term cardiovascular risks after exacerbation of chronic obstructive pulmonary disease. Heart. 2024;110(10):702–709. doi:10.1136/heartjnl-2023-323487

36. Krishnan S, Tan WC, Farias R, et al. Impaired Spirometry and COPD Increase the Risk of Cardiovascular Disease A Canadian Cohort Study. CHEST. 2023;164(3):637–649. doi:10.1016/j.chest.2023.02.045

37. Heidorn MW, Steck S, Müller F, et al. FEV1 Predicts Cardiac Status and Outcome in Chronic Heart Failure. CHEST. 2022;161(1):179–189. doi:10.1016/j.chest.2021.07.2176

38. Silvestre OM, Nadruz W, Roca GQ, et al. Declining Lung Function and Cardiovascular Risk. The ARIC Study. J Am Coll Cardiol. 2018;72(10):1109–1122. doi:10.1016/j.jacc.2018.06.049

39. Kilkenny MF, Phan HT, Lindley RI, et al. Utility of the Hospital Frailty Risk Score Derived From Administrative Data and the Association With Stroke Outcomes. Stroke. 2021;52(9):2874–2881. doi:10.1161/STROKEAHA.120.033648

40. Inglés M, Gambini J, Carnicero JA, et al. Oxidative stress is related to frailty, not to age or sex, in a geriatric population: lipid and protein oxidation as biomarkers of frailty. J Am Geriatr Soc. 2014;62(7):1324–1328. doi:10.1111/jgs.12876

41. Walker KA, Walston J, Gottesman RF, et al. Midlife Systemic Inflammation Is Associated With Frailty in Later Life: the ARIC Study. J Gerontol a Biol Sci Med Sci. 2019;74(3):343–349. doi:10.1093/gerona/gly045

42. Baylis D, Bartlett DB, Syddall HE, et al. Immune-endocrine biomarkers as predictors of frailty and mortality: a 10-year longitudinal study in community-dwelling older people. Age (Dordr). 2013;35(3):963–971. doi:10.1007/s11357-012-9396-8

43. Woldhuis RR, Heijink IH, van den Berge M, et al. COPD-derived fibroblasts secrete higher levels of senescence-associated secretory phenotype proteins. Thorax. 2021;76(5):508–511. doi:10.1136/thoraxjnl-2020-215114

44. Hirano T, Doi K, Matsunaga K, et al. A Novel Role of Growth Differentiation Factor (GDF)-15 in Overlap with Sedentary Lifestyle and Cognitive Risk in COPD. J. Clin. Med. 2020;9(9):2737. doi:10.3390/jcm9092737

45. Oishi K, Matsunaga K, Harada M, et al. A New Dyspnea Evaluation System Focusing on Patients’ Perceptions of Dyspnea and Their Living Disabilities: the Linkage between COPD and Frailty. J. Clin. Med. 2020;9(11):3580. doi:10.3390/jcm9113580

46. Burke H, Wilkinson TMA. Unravelling the mechanisms driving multimorbidity in COPD to develop holistic approaches to patient-centred care. Eur Respir Rev. 2021;30(160):210041. doi:10.1183/16000617.0041-2021

47. Tian YE, Cropley V, Maier AB, et al. Heterogeneous aging across multiple organ systems and prediction of chronic disease and mortality. Nat Med. 2023;29(5):1221–1231. doi:10.1038/s41591-023-02296-6

48. Spece LJ, Epler EM, Donovan LM, et al. Role of Comorbidities in Treatment and Outcomes after Chronic Obstructive Pulmonary Disease Exacerbations. Ann Am Thorac Soc. 2018;15(9):1033–1038. doi:10.1513/AnnalsATS.201804-255OC

DALLAS, September 3, 2025 — Atrial fibrillation, or AFib, often goes unrecognized despite affecting millions and increasing stroke risk by up to 5 times[1]. New consumer patient research from the American Heart Association, conducted by The Olinger Group, finds that most people with AFib (62%) had no prior knowledge of the condition before being diagnosed[2]. During September, AFib Awareness Month, the American Heart Association, a relentless force changing the future of health for everyone everywhere, is raising awareness nationwide about the condition, and that early identification and treatment of AFib are critical to stroke prevention.

Anyone can develop AFib, and risk increases with age. It is important to know the signs and risk factors:

1. Recognize AFib symptoms and risks. Irregular heartbeat is a common symptom of AFib, while high blood pressure and family history are key risk factors that increase the likelihood of developing the condition.
2. AFib is manageable and treatable. With the right plan you can lower your stroke risk and live fully.
3. You are not alone on your AFib journey. Find support and connect with others at MyAFibExperience.org.

AFib is a quivering or irregular heartbeat that can lead to blood clots, stroke, heart failure and other heart-related complications. According to the latest statics from the American Heart Association, the heart rhythm disorder (arrhythmia) affects over 6 million people in the U.S., and that number is expected to double by 2030[3].

“This projected rise is driven by several factors, including the growing prevalence of high blood pressure, a major risk factor for AFib, as well as increasing rates of diabetes, obesity and an aging population,” said José Joglar, MD, American Heart Association volunteer, professor of cardiac electrophysiology at UT Southwestern Medical Center in Dallas and chair of the 2023 guideline for the diagnosis and management of atrial fibrillation. “It’s important for people to understand their risk factors, recognize potential symptoms and have regular conversations with their health care professional. Early detection and proactive management can make a life-saving difference.”

To better understand this growing public health issue, the Association conducted a nationwide online survey of 1,200 participants, including 770 patients with AFib and 430 caregivers, between January and March 2025. The study assessed awareness of the condition, as well as motivations and barriers to treatment

The findings reveal gaps in public knowledge about AFib and highlight areas where increased awareness is essential to promote earlier recognition and diagnosis of the condition.

Learn the signs and risk factors

Symptoms can vary widely or be completely absent. Many people associate AFib with a racing or irregular heartbeat, however, other symptoms like shortness of breath, fatigue, dizziness, chest pain or fainting may occur.

While anyone can develop AFib, risk increases with age and is higher among people with uncontrolled high blood pressure, Type 2 diabetes, overweight, have had a prior heart attack or a family history of the condition.

According to the research, AFib patients reported experiencing an average of three symptoms before receiving a diagnosis[4], highlighting the need to recognize early warning signs, understand personal risk factors and discuss them with a health care professional. 

Managing AFib

Being diagnosed with AFib may feel overwhelming. However, with the right care plan, you can effectively manage AFib and reduce your risk of stroke and other complications.

Collaborating with a health care team helps patients understand their specific type of AFib and develop a personalized plan. Treatment options for AFib may include medication, procedures and lifestyle changes such as weight management, increasing physical activity, quitting smoking and managing conditions like high blood pressure to support long-term health.

Support is within reach

You’re not alone on your AFib journey. People living with AFib and caregivers can find support and connect with others through the American Heart Association’s online community MyAFibExperience.

This AFib Awareness Month, take action and inspire change by understanding the signs of AFib and talking to your health care team to manage your risk factors. Learn more at Heart.org/AFib.

The HCA Healthcare Foundation is a national sponsor of the American Stroke Association’s Together to End Stroke® initiative and AFib Awareness Month. The research was sponsored by the American Stroke Association, a division of the American Heart Association, with funding support from the HCA Healthcare Foundation.

Additional Resources:

###

About the American Heart Association

The American Heart Association is a relentless force for a world of longer, healthier lives. Dedicated to ensuring equitable health in all communities, the organization has been a leading source of health information for more than one hundred years. Supported by more than 35 million volunteers globally, we fund groundbreaking research, advocate for the public’s health, and provide critical resources to save and improve lives affected by cardiovascular disease and stroke. By driving breakthroughs and implementing proven solutions in science, policy, and care, we work tirelessly to advance health and transform lives every day. Connect with us on heart.org, Facebook, X or by calling 1-800-AHA-USA1.   

For Media Inquiries: 214-706-1173

Darcy Wallace: Darcy.Wallace@heart.org

For Public Inquiries: 1-800-AHA-USA1 (242-8721)

heart.org and stroke.org

Providence, RI, Sept. 03, 2025 (GLOBE NEWSWIRE) — As the school year begins, the Association of Migraine Disorders (AMD) is highlighting the challenges students with migraine face during the back-to-school transition. Returning to the classroom means changes in schedules, routines, and new stressors. This shift can increase the risk of migraine attacks for students.

“The transition back to school can be a particularly challenging time for students with migraine,” said Natalia Zorrilla, a board-certified pediatric nurse practitioner and member of AMD’s Advanced Practice Provider Education Committee. “After the more relaxed pace of summer, kids are suddenly faced with early wake-up times, a full day of classes, homework, extracurriculars, and social pressures. This change in schedule and increase in demands can be overwhelming and may trigger migraine attacks. The stress and anxiety that often come with school transitions can also make symptoms worse.”

Migraine in kids and teens

Migraine affects about 1 in 10 school-aged children. Although headache is the most recognized symptom, migraine can look different in kids—making it easier to overlook. Some kids experience the classic throbbing head pain. Some may primarily complain of stomachaches, nausea, and vomiting. Other symptoms may include dizziness, tiredness, irritability, paleness, dark under-eye circles, visual aura (seeing spots, colors, kaleidoscope), or sensitivity to light, sound and smell. 

Common back-to-school migraine triggers

AMD wants to help parents understand that no one trigger will “cause” a migraine attack. But exposure to multiple triggers can increase the risk of an attack. The most common triggers for kids are irregular and inconsistent sleep, dehydration, and changes in eating habits.

“Combined factors including earlier morning wake times, less sleep, prolonged time between meals, exposure to bright fluorescent lighting and noise—think busy hallways and cafeterias—are known to trigger an increase in migraine attacks,” said Deanna Duggan, a pediatric nurse practitioner, headache specialist, and member of AMD’s Advanced Practice Provider Education Committee. “Increased academic and athletic demands can also contribute to anxiety and stress.” 

Other back-to-school migraine triggers:

• Stress (tests/exams, presentations, family life, bullying, etc.)
• Bright lights, fluorescent lights, or flashing lights
• Changes in weather or barometric pressure
• Exposure to certain smells or loud noises
• Increased screen time
• Acute illness

How parents and schools can help

Creating and sticking to a consistent routine can help minimize the risk of an attack. Duggan and Zorrilla recommend the following to support kids living with migraine: 

• Plan ahead: Work with your child and the school to ensure access to water and snacks throughout the day.
• Protect downtime: Avoid overscheduling and leave room for rest or “blank space” in their day.
• Support a healthy sleep routine: Aim for a consistent bedtime and enough hours of rest each night.
• Partner with the school: Share your child’s diagnosis and treatment plan with the school and the school nurse. If needed, request a formal 504 accommodation plan.
• Get medical support: Talk with your child’s provider about lifestyle modifications and treatment options. 

Migraine attacks happen

“Give yourself and your child some grace,” said Duggan. “No matter how hard we try to minimize triggers, migraine attacks can occur abruptly, without warning. If a prescribed migraine treatment becomes less effective, discuss it with your child’s healthcare provider. There are other options.”

About The Association of Migraine Disorders

The Association of Migraine Disorders (AMD) is a 501(c)(3) nonprofit dedicated to advancing the understanding of migraine through research, education, and awareness. AMD is guided by an advisory board of diverse healthcare professionals who understand the wide-ranging symptoms of this complex disease.

• Migraine and Back-to-School

Introduction

Klebsiella pneumoniae (Kp) is a gram-negative bacterium that exists as normal flora in the respiratory and digestive tracts; however, it can cause opportunistic infections. The virulence-related factors contributing to Kp pathophysiology include bacterial capsular polysaccharides (polymorphic), lipopolysaccharides, pili (types 1 and 3), outer membrane proteins, and iron-binding siderophores (aerobactin, enterobactin, salmochelin, and yersiniabactin).^1,2 These virulence factors are resistant to antimicrobial peptides, enabling bacteria to resist the phagocytic influence of host immune cells, adhere to biological and abiotic surfaces, and alter their permeability to antibiotics.^3–5 Siderophores tightly bind to extracellular iron and re-enter bacteria via specific import mechanisms.⁶

Clinically isolated Kp can be divided into two types.^7,8 The first is classical (cKp), which is typically isolated from immunocompromised persons and can easily cause nosocomial infections. cKp strains are not virulent in mouse infection models but often harbor genes that confer multiple drug-resistance, including carbapenem resistance. Carbapenemases are classified into Ambler class A ((carbapenemase) KPC, GES, IMI, NMC, SME), B (IMP, VIM, New Delhi metal-β-lactamase (NDM), GIM, SIM, SPM), or D (OXA-48).^9,10 A previous study showed that the proportion of drug-resistant Kp carbapenemases increases with age, with the highest resistance rates found in patients > 60 years and higher proportions of drug-resistant strains in blood and urine than in sputum.^11,12 The antibiotics tigecycline and colistin are considered last-resort treatments for carbapenem-resistant Kp (CRKp). Key mechanisms of resistance to tigecycline in Kp include the overexpression of efflux pumps (such as AcrAB and OqxAB), inactivation of efflux-pump negative feedback factors, acquisition of the plasmid-borne tet(A) variant gene, and mutation of the rpsJ gene.^13–15 Colistin resistance is associated with genetic changes in lipid A modifications, including the overexpression of two-component regulatory systems (PmrAB and PhoPQ), inactivation of MgrB proteins, and the presence of mcr-1-carrying plasmids.^16–18

The second type, hypervirulent Kp (hvKp) (Figure 1), is characterized by capsular hyperproduction and a hypermucoviscous colony phenotype. hvKp typically causes community-acquired infections, as well as multi-site infections occurring rapidly in sequence, such as liver abscess, encephalitis, endophthalmitis, bacteremia, pneumonia, and empyema, and is usually sensitive to antibiotics.^19,20 The hypervirulent phenotype may be caused by the cumulative effect of different combinations of helper genes that work together to increase bacterial virulence. However, no clinical molecular diagnosis or microbial consensus currently exists for hvKp strains.^1,21,22 Moreover, although the high capsular production and hypermucoviscous phenotype may be closely related to the high virulence of hvKp, this correlation is not consistent.

Figure 1 Virulence mechanisms of hypermucoviscous Klebsiella pneumoniae: This figure illustrates the key mechanisms of virulence of the recently isolated hypermucoviscous Klebsiella pneumoniae.

In recent years, an increasing number of reports on drug-resistant Kp strains have led to an awareness of hypervirulent CRKp (hv-CRKp) strains. hv-CRKp strains emerge from hvKp acquiring mobile genetic elements carrying multiple antibiotic-resistance genes (such as genes encoding extended-spectrum beta-lactamases (ESBLs) and carbapenemases) or multi-drug-resistant (MDR)-Kp acquiring virulence genes (such as rmpA and siderophores), with the subsequent convergence of resistance and virulence.^1,23 Some studies suggest that MDR-Kp is more likely to acquire virulence genes.^1,23

Owing to the highly pathogenic nature of the hv-CRKp strain and its resistance to many antibiotics, many researchers have analyzed its characteristics. In this review, we summarize existing literature on the clinical characteristics, virulence, drug resistance, and treatment of hv-CRKp infection.

Epidemiological and Clinical Features

The combination of hypervirulence and multi-drug resistance in hv-CRKp represents a major medical and health challenge. Multivariate analysis has revealed that a strong biofilm-producing strain, an independent predictor of CRKp mortality, is associated with increased CRKp infection-related deaths.²⁴ The dominant strain of CRKp in the United States and European countries is Kp sequence type (ST) 258, whereas that in China is ST11.^25–28 The main carbapenemase genes in CRKp strains are bla KPC-2, bla NDM-1, and bla OXA-48. The prevalence of hypervirulence among CRKp strains ranges from 7.5% to 15%.^29–31 According to a study by the top three hospitals in Shanghai, China, the isolation rate of the hv-CRKp strain is 1.5%, and the dominant ST is ST11/K64, followed by ST11/K47, ST23/K1, and ST86/K2. ST11 is the most common ST among hv-CRKp isolates in China.²⁵ An Iranian study indicated that 85.7% of hvKp isolates produce ESBL; the carrying rates of bla NDM-6, bla OXA-48, bla CTX-M, blaSHV, and blaTEM were 7.1, 14.3, 21.4, 28.6, and 78.6%, respectively. Of the hvKP isolates, 42.9% were CR-hvKP. Moreover, XDR-hvKP isolates belong to ST15, ST377, ST442, and ST147, respectively.³² hv-CRKp is mainly isolated from respiratory tract and bile specimens but is also detected in other specimens, including urine, blood, and pleural effusion.^25,26 Among infected men, those aged 50–60 years have the highest risk of disease. Other studies have confirmed that older people are more susceptible to hv-CRKp infection, although CRKp has also been isolated from hospitalized infants.^25,26,33,34 Diabetes mellitus is a high-risk factor for hvKp infection.^35,36 Surgery and ICU are the major endemic departments. Furthermore, the mortality rate of hv-CRKp infection is approximately 17.1%.²⁶

Laboratory Analyses

Kp strains have been identified via traditional culture isolation, and virulence-related and drug-resistance genes have been detected using a variety of bacterial strain identification and gene detection methods.³⁷ Classical detection methods include antimicrobial susceptibility testing approaches, such as disk diffusion, AGAR dilution, broth microdilution, MALDI-TOF MS, VITEK MS, and biomsamrieux, which test for antibiotic sensitivity. The string test can be used to determine the hyperviscous phenotype; here, when a loop applied to a colony pulls a “string” of >5 mm, it indicates a positive result; however, this test is affected by many factors, such as culture conditions. The sedimentation assay is more reliable than the string test for determining the hyperviscous phenotype.⁸ The virulence profiles of Kp isolates have been evaluated using a Galleria mellonella infection model. In addition, virulence phenotype identification can be achieved using in vivo virulence models, biofilm formation assays, neutrophil assays, and iron carrier production assays.^38–40 PCR, sequencing, PCR-based multilocus sequence typing, and phylogenetic multilocus sequence typing are also used to detect strains and serotypes.⁴¹ A microdilution checkerboard method can be used to determine the activity of Kp strains against various drugs. In recent years, the application of next-generation and whole-gene sequencing technology, which can rapidly detect strains, drug resistance, and virulence genes, has gradually increased and been applied in clinical practice.⁴²

Virulence and Drug Resistance

Host factors and antibiotics may drive the adaptive evolution of Kp virulence-related and drug-resistance genes.⁴³ Prior antibiotic therapy, previous hospitalization for five days or more, invasive procedures, and mechanical ventilation are all notable risk factors for hv-CRKp strain colonization. When combined with underlying diseases (such as diabetes), carbapenem exposure is an independent risk factor for hv-CRKp strain colonization.^44–46 The common capsular antigens of hv-CRKp in China are K1, K2, and K54 and the ST is ST11.^31,45,47 A study in Malaysia confirmed that all strains isolated from hypermucoviscous CRKp contained carbapenemase-resistance genes and showed multi-drug resistance, whereas the virulence genes detected in hypermucoviscous CRKp harbored the aerobactin siderophore receptor gene (iutA), iroB, rmpA, and rmpA2, with no K1/K serotype, peg-344, allS, or magA.²⁹ As mentioned previously, hv-CRKp has two evolution patterns (Figure 2): CRKp acquiring virulence genes or hv-Kp acquiring resistance genes. Specifically, through the horizontal gene transfer of outer membrane vesicles (OMVs) carrying virulence or resistance genes, OMVs can carry blaNDM-1 genes and pass them to the hvKp strain NTUH-K2044; similarly, OMVs containing virulence genes isolated from hvKp can also be horizontally transferred to ESBL-producing cKp strains, thereby promoting the emergence of hv-CRKp.^38,48,49 The hypervirulence and multi-drug resistance of hv-CRKp are mainly due to the existence of large plasmids containing multiple virulence genes (such as pLVPK) or hybrid conjugation plasmids with both virulence-related and carbapenem-resistance genes.^28,50,51 Capsular evolution may lead to the convergence of carbapenem resistance and high virulence in Kp. According to research on the ST23-K1 strain, the wcaJ gene was interrupted by insertion sequence elements, resulting in small capsule synthesis and decreased virulence. However, the blaKPC-2 plasmid coupling frequency increased, which promoted high virulence and carbapenem resistance in the strain.⁵² Hypervirulent ST11-KL64 can rapidly diversify its resistance to tigecycline and polymyxin treatment. Sequencing analysis has revealed that ramR and lon frameshift mutations are the main causes of tigecycline resistance and that ceftazidime–avibactam (CZA) resistance is associated with the blaKPC-2 mutation. Several mechanisms have been shown to contribute to polymyxin resistance: increased expression of blaKPC-2 that increases the minimum inhibitory concentration of CZA; mutations in pmrB, phoQ, and mgrB; and the insertion of IS (ISKpn74 and IS903B) into the same location of mgrB, as well as a mutation associated with the efflux pumping system.^18,53 Deletion of the acyltransferase gene (act) at the cps site plays a crucial role in the virulence evolution of ST11 CRKp.^54,55 Wang et al isolated a strain of hv-CRKp from patients with scrotal abscess and urinary tract infection and observed its phenotypic transition from high viscosity to low viscosity, which was attributed to either defective or low expression of rmpADC or the capsule synthesis gene wcaJ, or mediated by ISKpn26 insertion/deletion or base pair insertion. Their experiments on mice confirmed that the invasiveness of the strain decreased significantly after transformation to the low-viscosity phenotype; however, the residence time of the strain in the urinary tract and gallbladder of mice was significantly extended.⁴³

Figure 2 Mechanisms of carbapenem-resistant hypermucoviscous Klebsiella pneumoniae formation: This figure presents the formation mechanisms contributing to carbapenem-resistant hypermucoviscous Klebsiella pneumoniae.

The hv-CRKp isolates reported in recent years often harbor multiple resistance genes and a large plasmid containing multiple virulence genes. The Kp0179 strain (found in routine monitoring of clinical samples isolated from a patient in China) was confirmed to belong to K2-ST375. Six resistance genes were identified, including blaSHV-99, fosA, oqxAB, blaNDM-1, qnrS1, and blaSHV-12, the last three of which were located on the binding plasmid pNDM-Kp0179 (IncX3 type), as well as the plasmid pLVPK, of approximately 121 kb (carrying iroBCDN, iucABCDiutA, rmpA, rmpA2, and other virulence genes).⁵⁶ KP18-3-8 and KP18-2079, which are ST11-KL64 CRKp clinical isolate strains, harbor the positive resistance genes blaKPC-2 and rmpA2. Two new hybrid virulence plasmids, KP18-3-8 (pKP1838-KPC-vir, 228,158 bp) and KP18-2079 (pKP1838-KPC-vir, 182,326 bp), have been identified. The IncFII/incr virulence plasmid, pKP18-2079-vir, may be the result of recombinant PLVPK-like virulence and MDR plasmids.⁵⁷ LABACER 01 has a genome sequence of 5,598,020 bp, belongs to ST25, and contains 19 antibiotic-resistance and virulence-related genes, including mrkA-F and ecpD, as well as iron acquisition systems, such as iutA, iron, entB, entS, and entH. The ferric enterobactin-binding periplasmic protein fepB-D is also encoded by basic structural genes cyoA/B, tamA/B, hemN, and gltB associated with dense intestinal colonization. LABACER 27 has a genome sequence of 5,622,382 bp, belongs to ST25, and contains 20 different antibiotic-resistance and virulence factor-related genes, including ycfM, mrkD, kpn, and entB.⁵⁸ SZ651 is a ST15/K19 clone containing multiple resistance genes, including aac(3)-IId, aac(6’)-Ib-cr, blaSHV-28, blaSHV-106, blaTEM-1B, blaOXA-1, blaCTX-M-15, blaKPC-2, mph(A), and tet(A). Several key virulence factors have also been identified in this strain, including genes encoding type 3 fimbria virulence determinants (mrkA, mrkB, mrkE, mrkF, mrkI, and mrkJ) and the iron-containing factor yersiniabactin (ybtA, ybtP, ybtQ, ybtS, ybtT, and ybtU).⁵⁹

A previous study analyzed RJ-8061, a urine isolate from an 86-year-old female patient with pneumonia, which contains KPC-2 and NDM −5 enzymes. This study identified the pRJ-8061-hybrid plasmid as a 294,249 bp hybrid plasmid that contains both resistance genes [blatemm-1b, mph(a), aac(3)-IId] and virulence genes (iucABCDiutA, rmpA2), although rmpA2 was truncated. In addition, blaKPC-2 and blaNDM-5 are located on the pRJ-8061-KPC-2 (IncFII/IncR) plasmid (171,321 bp) and pRJ-8061-NDM-5 (IncX3) plasmid (46,161 bp), respectively.⁶⁰ The Kpn216 strain (French isolate) is resistant to penicillin and its combination with beta-lactamase inhibitors, as well as carbapenems, third-generation cephalosporins, quinolones, and tigecycline. blaCTX-M-15, encoded by a new ST9-IncN plasmid, is found in an IS26-based composite transposon, the downstream of which is a truncated isecp1 insertion sequence. Each isolate carries one IncHI1B/IncFIB replicator and is numbered VIR-KPN154 and VIR-KPN2166.³⁰ KP75w, which belongs to ST11, harbors resistance genes, including carbapenemase genes (blaNDM-1), as well as highly virulent genes (rmpA2, iucABCD-iutA, fyuA, irp, mrk, ybt, fep, and virB2).⁶¹

Treatment

A meta-analysis of 77 studies from 17 countries showed widespread resistance among hvKp strains, including resistance to ampicillin sulbactam, cefazolin, cefuroxime, ceftazidine (57.1%), cefepime (51.3%), and carbapenems, with all resistance rates greater than 40%.⁴⁷ Drug-resistance analysis of hv-CRKp in China revealed resistance to ampicillin, ampicillin/sulbactam, cefoperazone/sulbactam, piperacillin/tazobactam, cefazolin, cefuroxime, ceftazidime, imipenem, meropenem, and amikacin, with resistance rates ranging from more than 60% for ciprofloxacin and 43.8% for benzidine-sulfamethoxazole.²⁵

CZA is a novel combination preparation with good antibacterial activity against MDR gram-negative bacteria that is well-tolerated by patients, with few adverse reactions. Accordingly, CZA is used as salvage therapy in patients infected with CRKp but is ineffective against carbapenemase B.^62–64 Polymyxins and tigecycline are considered critical therapeutics for resistant strains and represent the last line of defense against CRKp infections.^65–69 However, reports of polymyxin and tigecycline resistance have gradually increased. A Chinese study reported that the percentages of tigecycline- and colistin B-resistance in isolated CRKp strains were 1.2% and 4.8%, respectively.⁴⁷ Furthermore, elacycline is a novel preparation that can be used to treat hv-CRKp.

In recent years, non-antibiotic treatments have gradually received attention. For example, the application of Corynebacterium pseudodiphtheriticum to the nasal cavity of mice challenged with the MDR-Kp strain ST25 reduced lung bacterial cell counts and tissue damage.⁷⁰ This was attributed to modulation of the recruitment of white blood cells into the lung and the production of TNF-α, IFN-γ, and IL-10 in the respiratory tract and serum. Thus, this bacterium could represent a novel respiratory tract probiotic, replacing antibiotic therapy and reducing the generation of drug-resistance genes under the burden of antibiotics. However, further studies are required to confirm these findings. Additionally, treatment with the phage kpssk3 improved the survival rate of mice with hypermucoviscous CRKp infection by 100%, with no significant changes in the intestinal microbiota and no serious side effects.⁷¹ Thus, kpssk3 may represent an effective method for treating hypermucoviscous CRKp.

Conclusions

Owing to the annual increase in the number of hv-CRKp strains, the high mortality rate of hv-CRKp infection, and the lack of effective anti-infective drugs, hv-CRKp has become an important burden on global medicine and health. The dominant endemic CRKp strain in the United States and European countries is ST258, whereas that in China is ST11. hv-CRKp can emerge from two main pathways: CRKp acquiring virulence genes or hvKp acquiring drug-resistance genes via the horizontal gene transfer of OMVs. The detection rate of hv-CRKp is the highest in sputum specimens but also very high in bile specimens. The incidence of hv-CRKp is higher in males and increases with age; however, hv-CRKp is also detected in newborns. ICU stays, carbapenem exposure, and diabetes are major risk factors for infection with this strain. The identification of hv-CRKp strains primarily involves the detection of virulence-related and drug-resistance genes. Whole-gene detection has recently emerged as an efficient method, although other detection methods, including 16sRNA and PCR, are also commonly used. Despite this availability of various detection methods for rapid diagnosis for drug resistance genes, it is sometimes difficult to determine whether a specific strain is pathogenic, and the responses of some patients to antibiotics do not match the results of drug resistance gene tests. It is therefore necessary to develop more accurate detection methods to distinguish pathogenic Kp, especially for drug resistance gene detection and drug selection. The drug-resistance rate of hv-CRKp is high. Currently, the commonly used drugs for the treatment of hv-CRKp in clinical practice include CZA, tigecycline, and polymyxin. However, in recent years, the resistance rates to the above-mentioned drugs have gradually increased, including tigecycline resistance caused by ramR and long frame shift mutations, and CZA resistance caused by blaKPC-2 mutations. Additionally, the expression of blaKPC-2 increased, raising the minimum inhibitory concentration of CZA. Mutations in pmrB, phoQ and mgrB, insertion of IS (ISKpn74 and IS903B) into the same position of mgrB, and mutations related to the drainage pump system are all associated with polymyxin resistance. It is therefore recommended to combine antibacterial drugs for the treatment of hv-CRKp. Moreover, new drugs, including elacycline, have gradually emerged for the treatment of hv-CRKp. Furthermore, non-antibiotic therapies, such as C. pseudodiphtheriticum 090104 and kpssk3, represent promising therapies for hv-CRKp that require further research.

Abbreviations

Kp, Klebsiella pneumoniae; cKp, classical Klebsiella pneumoniae; CRKp, carbapenem-resistant Klebsiella pneumoniae; hvKp, hypervirulent Klebsiella pneumoniae; hv-CRKp, hypervirulent CRKp; ESBLs, extended-spectrum beta-lactamases; MDR, multi-drug-resistant; ST, sequence type; iutA, aerobactin siderophore receptor gene; OMVs, outer membrane vesicles; CZA, ceftazidime–avibactam; KPC, carbapenemase; NDM, New Delhi metal-β-lactamase.

Data Sharing Statement

No new data were analyzed or created in this article.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval ofthe version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Funding

This study was supported by grants from the Science and Technology Department of Jilin Province (No.20220508068RC).

Disclosure

The authors declare no conflicts of interest.

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OXFORD, England and CHICAGO, Sept. 3, 2025 /PRNewswire/ — Brainomix, a global leader and pioneer of AI-powered imaging tools in stroke and lung fibrosis, has garnered widespread media attention¹ this week following a renewed focus on the impact of its Brainomix 360 Stroke technology to improve recovery rates for stroke patients.

A study published by the Royal Berkshire Hospital demonstrated that Brainomix software tripled the number of stroke patients achieving functional independence, from 16% to 48%. Additional data from the largest real-world evaluation of stroke AI imaging showed that Brainomix 360 Stroke was associated with a more than 50% increase in mechanical thrombectomy, a life-changing stroke treatment.

Brainomix 360 Stroke is a comprehensive platform powered by highly advanced AI algorithms, supporting clinicians by providing real-time interpretation of brain scans to help guide treatment and transfer decisions for stroke patients in both specialist and general hospitals.

David Hargroves, the NHS Clinical Director for Stroke, said: “This AI decision support technology is revolutionizing how we help people who have been affected by stroke. It is estimated a patient loses around 2m brain cells a minute at the start of a stroke, which is why quick diagnosis and treatment is so critical. AI decision support software provides real-time interpretation of patients’ brain scans – supporting expert doctors and other NHS staff to make faster treatment decisions.”

Dr Michalis Papadakis, CEO and Co-Founder at Brainomix, said: “Brainomix is helping clinicians every day improve the level of care they can deliver to stroke patients in the UK and worldwide. We are delighted to see a focus on the unique and powerful impact that our technology is having on patient outcomes, validated by an expanding base of published, real-world evidence.”

Brainomix is widely recognised as one of the UK’s most successful AI healthcare companies, having developed its technology through commercial scale up to market launch, and having secured a number of successful partnerships with NHS England and The Health Innovation Network.

Brainomix 360 Stroke has been deployed widely across the UK and Europe, where it is the established market leader, and in the United States, where it has been validated by a number of world-class stroke institutions and exhibiting a similar clinical impact on stroke care.

¹ The Times, The Guardian, The Telegraph, The Daily Mail, The Independent, The Sun, The Mirror

Notes to Editors

About Brainomix

Brainomix specializes in the creation of AI-powered software solutions to enable precision medicine for better treatment decisions in stroke and lung fibrosis. With origins as a spinout from the University of Oxford, Brainomix is an expanding commercial-stage company with offices in the UK, Ireland and the USA, and operations in more than 20 countries. A private company, backed by leading healthtech investors, Brainomix has innovated award-winning imaging biomarkers and software solutions that have been clinically adopted in hundreds of hospitals worldwide. Its first product, the Brainomix 360 stroke platform, provides clinicians with the most comprehensive stroke imaging solution, driving increased treatment rates and improving functional independence for patients.

To learn more about Brainomix and its technology visit www.brainomix.com, and follow us on Twitter, LinkedIn and Facebook.

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SOURCE Brainomix

Introduction

Urologic diseases represent a major public health concern for women worldwide.¹ These include both nonmalignant and malignant conditions such as urinary tract infections (UTIs), urolithiasis, kidney cancer, and bladder cancer, which are highly prevalent and associated with substantial morbidity and disability. Although urologic trauma related to obstetric complications is an important issue in some low-resource settings, data on its burden remain limited.² Accordingly, this study focuses on four major urologic diseases in women: UTIs, urolithiasis, kidney cancer, and bladder cancer. UTIs affect more than 40% of women during their lifetime, with Escherichia coli being the most common pathogen.^3,4 A prior history of urinary tract infections is one of the strongest risk factors for future UTIs.⁵ Approximately 30% of women experience recurrent infections within six months. Rising antimicrobial resistance has diminished the effectiveness of standard antibiotic treatments, prompting interest in alternative preventive strategies, such as vaginal estrogen and lactobacillus-containing probiotics in postmenopausal women.⁶ Meanwhile, the burden of urolithiasis has also increased, particularly among women.⁷ Compared to nulliparous women, pregnant women under 50 years of age face more than double the risk of stone formation.⁸ Contributing factors include metabolic syndrome, dietary habits, weight loss interventions, hypercalciuria, and environmental and socioeconomic conditions, all of which have been linked to elevated risk of stone recurrence.^9–11

Kidney and bladder cancers are two other urologic diseases with rising incidence in women. Kidney cancer is now the ninth most common cancer among women globally, with incidence rates increasing by 2–3% per year between 2015 and 2019.¹² Alarmingly, mortality rates for kidney cancer are twice as high in Native American individuals compared to individuals of White descent.¹³ Risk factors for kidney cancer include smoking, alcohol consumption, overweight or obesity, and hypertension.¹⁴ For bladder cancer, smoking remains a major modifiable risk factor, responsible for approximately 50% of cases in men and 40% in women in the United States.¹ While the overall incidence and mortality remain higher in men, women who are active or passive smokers still face significant risk.¹⁵ Additionally, emerging evidence implicates occupational exposures, specific dietary habits, microbiome dysbiosis, gene–environment interactions, diesel exhaust, and pelvic radiotherapy in bladder cancer development.¹⁶ These disparities highlight the complex interplay of biological, behavioral, and social factors in shaping disease burden.

Despite the considerable health impact of these urologic diseases, up-to-date, sex-specific epidemiological data are scarce. Regional and national differences in incidence and outcomes are influenced by healthcare access, sociodemographic development, and environmental exposures.¹⁷ To address this gap, we used data from the Global Burden of Disease Study 2021 to systematically evaluate the incidence and disability-adjusted life years (DALYs) of UTIs, urolithiasis, kidney cancer, and bladder cancer in women across 204 countries and territories from 1990 to 2021.^18–20 This analysis aims to uncover global patterns and temporal trends of four major urinary conditions in women to support evidence-based public health strategies and inform future research and clinical practice.

Patients and Methods

Data Source and Screening

This study utilized data from the Global Burden of Disease (GBD) Study 2021, which systematically estimates the incidence, mortality, DALYs, and age-standardized rates for 371 diseases and injuries across sexes, age groups, and 204 countries and territories worldwide.¹⁸ GBD 2021 employed three core analytical tools—Cause of Death Ensemble Model (CODEm), Spatiotemporal Gaussian Process Regression (ST-GPR), and DisMod-MR 2.1—to synthesize data and generate consistent estimates of disease burden.^18,20

For the present analysis, we extracted data specific to four major urologic diseases in women—urinary tract infections, urolithiasis, kidney cancer, and bladder cancer. We extracted global-level data to analyze overarching trends. For more detailed national and subregional comparisons, we selected Western Europe, China, and North Africa and the Middle East as representative regions based on their geographic diversity, data availability, and distinct epidemiological profiles of urologic diseases. “Incidence” and “DALYs” were chosen as the primary measures of disease burden. To provide a comprehensive overview, we examined age- and year-specific incidence and DALY rates for each of the four conditions across the selected regions.

The Socio-demographic Index (SDI), a composite indicator reflecting income per capita, average educational attainment, and fertility rates, was included to account for variations in development level, given its strong association with health outcomes.²¹ Using GBD 2021 data, countries and territories were categorized into five groups based on SDI: high, high-middle, middle, low-middle, and low. Additionally, the Human Development Index (HDI), a composite measure of overall human development obtained from the United Nations Development Programme, was employed.²² Correlation analyses between GBD data and HDI were conducted to examine the relationship between human development and disease burden.²³ Risk factor attribution was based on the GBD’s comparative risk assessment framework, which comprises six key steps to estimate the proportion of disease burden attributable to modifiable risk exposures.²⁴ This framework enabled further insight into the global patterns and drivers of urologic disease burden in women.

Statistical Analysis

The age-standardized rate (ASR), was used to account for differences in age structures between populations and over time. It was calculated using the following formula:

In the equation, _i represents the age-specific rate in the i^th age group, and w_i denotes the count of individuals in the same age group based on the GBD 2021 standard population.¹⁸

To evaluate temporal trends in the burden of urologic diseases in women, we calculated the estimated annual percentage change (EAPC) in age-standardized incidence rate (ASIR) and age-standardized DALY rate (ASDR) from 1990 to 2021.²⁵ EAPC was derived from a linear regression model fitted to the natural logarithm of the ASR, specified as:

EAPC was then defined as:

The 95% confidence interval (CI) of the EAPC was also obtained from the regression model.²⁶ We interpreted a trend as statistically significant if both the EAPC and its 95% CI were either entirely above or entirely below zero. If the 95% CI included zero, the trend was considered statistically insignificant.

Finally, to project trends through 2046, we conducted an age–period–cohort (APC) analysis using the “Nordpred” package in R. This approach considers both demographic changes and temporal trends and has been well-established in previous studies.²⁷ All statistical analyses were performed using R software (version 4.3.2), and rates were expressed per 100,000 population. Statistical significance was determined using a p value of <0.05.

Results

Global and Regional Patterns in the Burden of Urologic Diseases in Women

In 2021, the global incidence of urologic diseases in women showed a notable increase. The estimated number of new cases was 35,718.97 × 10⁵ for UTIs (95% UI: 31,808.47–39,914.82), 3,487.81 × 10⁵ for urolithiasis (95% UI: 2,913.36–4,247.25), 13.52 × 10⁵ for kidney cancer (95% UI: 12.41–14.42), and 12.26 × 10⁵ for bladder cancer (95% UI: 10.82–13.39). To better capture temporal trends while accounting for population growth and changes in age distribution, age-standardized rates (ASRs) were utilized. Analysis of the ASIR and ASDR from 1990 to 2021 revealed heterogeneous trends across different diseases.

The ASIR of UTIs remained relatively stable globally with EAPC of 0.03 (95% CI 0.02 to 0.05), whereas its ASDR generally declined with EAPC of −0.6 (95% CI: −0.76 to −0.25), except in China where a slight upward trend was observed. For urolithiasis, both the ASIR and ASDR declined steadily over the study period, with a global ASIR EAPC of −0.16 (95% CI −0.19 to −0.14) and ASDR EAPC of −0.26 (95% CI −0.35 to −0.08). In contrast, the ASIR for kidney cancer remained relatively stable with EAPC of 0.04 (95% CI −0.03 to 0.12), while its ASDR significantly decreased with EAPC −0.23 (95% CI −0.30 to −0.13). For bladder cancer, both ASIR and ASDR showed a favorable and consistent downward trend, with an ASIR EAPC of −0.15 (95% CI −0.22 to −0.07) and ASDR EAPC of −0.31 (95% CI −0.38 to −0.22). These results are detailed in Table 1.

Table 1 Global Incidence and DALYs of Four Female Genitourinary Diseases from 1990 to 2021

National and Subregional Trends in the Burden of Urologic Diseases in Women

At the national level, the ASDR for UTIs has declined in most countries or regions worldwide, with China showing the most pronounced decrease (EAPC: –0.60; 95% CI: –0.76 to –0.25). In contrast, several countries in North Africa and South America, such as Argentina, Uruguay, and Kuwait, have experienced a rapid increase in ASDR (Figure 1A). For urolithiasis, the ASDR has increased in several countries, including Libya, Brazil, and Guyana, whereas Czechia recorded the fastest decline (EAPC: –0.73; 95% CI: –0.80 to –0.65) (Figure 1B). Regarding kidney cancer, although the ASDR is generally decreasing, the rate of decline is relatively modest. Sri Lanka leads in the reduction trend with an EAPC of –0.79 (95% CI: –0.87 to –0.67) (Figure 1C). As for bladder cancer, some countries show substantially faster declines in ASDR than others, with Mongolia, Mauritius, and Egypt ranking in the top three (Figure 1D). Overall, China stands out globally for achieving substantial reductions in the ASDR across all four major urologic diseases in women, with an EAPC of –0.60 (95% CI: –0.76 to –0.25) for urinary tract infections, –0.66 (95% CI: –0.76 to –0.40) for urolithiasis, –0.52 (95% CI: –0.67 to –0.32) for kidney cancer, and –0.33 (95% CI: –0.55 to –0.05) for bladder cancer.

Figure 1 Global and regional variations in the EAPC of ASDR for urologic diseases in women. (A) Urinary tract infections. (B) Urolithiasis. (C) Kidney cancer. (D) Bladder cancer.

Correlation Among EAPC, ASR, and HDI

In the correlation analysis between the ASR and the EAPC from 1990 to 2021 for urologic diseases in women, a notable negative correlation was observed between the ASDR of UTIs and the corresponding EAPC in 1990 (cor=−0.3184, p<0.0001), while a positive correlation emerged by 2021 (cor=0.2299, p=0.0009) (Figure 2A). A similar trend was found for urolithiasis, with a negative correlation in 1990 (cor=−0.3376, p<0.0001) and a positive correlation in 2021 (cor=0.2236, p=0.0013) (Figure 2B). In contrast, for urologic cancers, including kidney and bladder cancer, significant negative correlations were noted in 1990 between ASIR/ASDR and EAPC, but no significant correlations were found in 2021 (Figure 2C and D). Regarding the association between EAPC and the Human Development Index (HDI) in 2021, a positive correlation was observed between the ASDR and EAPC for UTI (cor = 0.2546, p = 0.0013), and a negative correlation for bladder cancer (cor = –0.1810, p = 0.0233). No statistically significant associations were identified for other diseases (Figure 2E–H).

Figure 2 Correlations of EAPC with ASR and HDI for urologic diseases in women. Panels (A–D) show the correlation between EAPC and ASRs in 1990 for urinary tract infections (A), urolithiasis (B), kidney cancer (C), and bladder cancer (D). Panels (E–H) show the correlation between EAPC and HDI in 2021 for the same diseases (E–H, respectively).

Current Age-Specific Burden of Urologic Diseases in Women

Figure 3 illustrates the global age-specific distribution of incidence and DALYs for four major urologic diseases in women in 2021. Non-neoplastic diseases displayed pronounced differences in age patterns. The incidence of UTIs peaked between ages 30–34, with approximately 37 million new cases. Conversely, urolithiasis peaked later, around ages 55–59, reaching nearly 50 million cases. Regarding incidence rates, UTIs demonstrated a bimodal distribution, with the first peak in middle-aged adults (25–54 years) and a second sharp increase among individuals older than 85, exceeding 10,000 per 100,000 population. The incidence rate pattern for urolithiasis mirrored its case distribution, peaking similarly in the 55–59 age group (Figure 3A).

Figure 3 Global incidence and DALY counts and rates for urologic diseases in women by age group. (A) Incidence of non-neoplastic diseases. (B) DALYs of non-neoplastic diseases. (C) Incidence of neoplastic diseases. (D) DALYs of neoplastic diseases.

The age distribution of DALYs for UTIs followed a bimodal trend, with a pronounced peak in the 15–24 age group, followed by a decline and then a second rise, reaching the highest burden in the 70–74 age group. In contrast, the DALYs burden for urolithiasis steadily increased until 55–59 years, then gradually declined. In terms of DALY rates, both UTIs and urolithiasis showed a general increase with age, with UTIs displaying a marked surge after age 85 (Figure 3B).

Due to the life-threatening nature of kidney and bladder cancers, both diseases exhibited similar age-related patterns in incidence and DALYs. Peaks were observed in the 65–79 age range, with the burden consistently increasing with age. Notably, kidney cancer showed a minor uptick in incidence between ages 2–10, and the corresponding DALYs among individuals aged 2–19 showed a negative correlation with age (Figure 3C and D).

Figure 4 presents the EAPC in age-specific DALY rates across different regions from 1990 to 2021. For UTIs, China experienced declines in all age groups, while many other regions, particularly high-middle SDI areas, showed a pattern of decreasing burden in younger groups and increasing burden in the oldest age groups, peaking at an EAPC of 2.48 in individuals aged 95 and older (Figure 4A). Urolithiasis showed an overall decreasing trend in most age groups globally, especially in China. However, an increasing trend in DALY rates after age 35 was observed in North Africa and the Middle East (Figure 4B). For kidney cancer, most age groups in low, low-middle, and middle SDI regions demonstrated an increasing trend in DALY rates (Figure 4C). In contrast, bladder cancer presented a more favorable picture: DALY rates declined across nearly all regions and age groups, except among individuals older than 95, where a slight increase was noted (Figure 4D).

Figure 4 EAPC in DALY rates for urologic diseases in women by age group and region, 1990–2021. (A) Urinary tract infections. (B) Urolithiasis. (C) Kidney cancer. (D) Bladder cancer.

Composition of Incident Cases and Risk-Attributable DALYs for Urologic Diseases in Women

The composition of incident cases and risk-attributable DALYs for major urologic diseases in women in 1990 and 2021 was analyzed (Figure 5). In 2021, among non-neoplastic urologic diseases in women, urinary tract infections (UTIs) accounted for a significantly higher proportion of global incident cases compared to urolithiasis (91.1% vs 8.9%). However, in China, urolithiasis contributed a relatively higher proportion than the global average, with UTIs and urolithiasis accounting for 75.7% and 24.3% of cases, respectively (Figure 5A). For urologic cancers, kidney cancer represented a slightly greater share of incident cases globally than bladder cancer (52.5% vs 47.5%). This disparity was particularly pronounced in North Africa and the Middle East (60.5% vs 39.5%). In contrast, low Socio-demographic Index (SDI) regions demonstrated the opposite pattern, with bladder cancer comprising a higher proportion (59.6% vs 40.4%) (Figure 5B). Longitudinal trends from 1990 to 2021 indicate that the global proportion of UTIs among non-neoplastic urologic diseases has continued to rise. Meanwhile, the proportion of kidney cancer among urologic malignancies has increased across all SDI regions.

Figure 5 The proportion of incident cases and DALYs attributable to risk factors for urologic diseases in women, 1990–2021. (A) Proportional distribution of incident cases among non-neoplastic urologic diseases. (B) Proportional distribution of incident cases among neoplastic urologic diseases. (C) Proportion of DALYs attributable to specific risk factors for kidney cancer. (D) Proportion of DALYs attributable to specific risk factors for bladder cancer.

In 2021, the leading attributable risk factor for kidney cancer was high body mass index (BMI), accounting for 85.0% of the DALYs, followed by smoking (14.8%) and occupational carcinogens (0.2%) (Figure 5C). The contribution of smoking was highest in high-SDI and Western European countries (23.3% and 23.2%, respectively). Risk factors for bladder cancer showed marked regional variation: in low-SDI and North Africa/Middle East regions, high fasting plasma glucose was the predominant risk factor (62.8% in North Africa and the Middle East), whereas in high-SDI and Western Europe, smoking was the leading contributor (69.1% and 71.9%, respectively) (Figure 5D). Compared to 1990, the contribution of high BMI to kidney cancer burden increased in 2021, while the role of high fasting plasma glucose as a risk factor for bladder cancer also rose. Consequently, the proportion of urologic cancer-related DALYs attributable to smoking among women has declined.

Projections of Global Incidence and DALY Rates of Urologic Diseases in Women

We projected the trends in ASIR and ASDR for four major urologic diseases in women worldwide from 2021 to 2046 (Figure 6). For UTIs, both the ASIR and ASDR are expected to remain relatively stable over the next decade, with a modest upward trend anticipated after 2032 (Figure 6A). In the case of urolithiasis, projections suggest that both ASIR and ASDR will remain stable throughout the forecast period, without significant fluctuation (Figure 6B). For malignant urologic conditions, the predicted trajectories for kidney and bladder cancers show a slight initial decline in both ASIR and ASDR, followed by a mild increase in subsequent years. However, the magnitude of these changes is relatively small, indicating a generally stable burden over time (Figure 6C and D).

Figure 6 Predicted trends in incidence and DALY rates for urologic diseases in women from 2021 to 2046. (A) Projected age-standardized incidence rates for non-neoplastic urologic diseases. (B) Projected age-standardized DALY rates for non-neoplastic urologic diseases. (C) Projected age-standardized incidence rates for neoplastic urologic diseases. (D) Projected age-standardized DALY rates for neoplastic urologic diseases.

Discussion

In recent years, women’s urologic health has gained increasing global attention due to its growing prevalence and associated healthcare burden. These diseases pose substantial challenges to public health systems and call for urgent, coordinated responses.²⁸ Using data from the Global Burden of Disease Study 2021, we systematically assessed the incidence and DALYs for UTIs, urolithiasis, kidney cancer, and bladder cancer in women across global, regional, and national levels from 1990 to 2021.

These four urologic diseases display two distinct epidemiological patterns—non-malignant conditions like UTIs and urolithiasis, and malignant ones like kidney and bladder cancers. UTIs remain a major public health concern among women due to their high prevalence and potential complications.²⁹ Our findings indicate that although the ASDR for UTIs has remained stable in most regions, the absolute number of cases has risen significantly, likely driven by population growth, aging, and the heightened susceptibility of elderly women.³⁰ This is consistent with the findings of Yang et al, who reported a rising incidence of UTIs associated with aging populations.³¹ Cognitive impairment, incontinence, and diminished functional capacity—common among older women—are established risk factors for UTIs.^32,33 Notably, several South American countries experienced a marked rise in UTI-related ASDR, possibly due to the increased prevalence of multidrug-resistant infections.³⁴ Correlation analyses further revealed shifting trends in burden disparities. In 1990, a negative association was observed between baseline ASDR and EAPC, suggesting convergence across countries. However, by 2021, this relationship reversed, possibly reflecting inequities in healthcare access. A similar trend was observed in urolithiasis, whereas it is less pronounced in kidney and bladder cancers. Additionally, UTI-related ASDRs positively correlated with HDI, potentially due to the higher prevalence of resistant pathogens in high-income settings.³⁵

Although the overall burden of urolithiasis appears stable or declining, an upward trend is evident in tropical and hot-climate regions, possibly linked to dehydration, dietary factors, and environmental exposures.^36–38 This finding aligns with Wang et al’ s findings on climate-related risk for stone formation.³⁹ The highest burden was noted among women aged 50–59, suggesting a possible link to menopause, which may increase urinary calcium excretion and thereby the risk of stone formation as suggested by Prochaska et al^40,41 Future projections indicate a relatively stable burden, likely supported by advances in surgical and minimally invasive treatment options.⁴²

Urologic cancers show distinct epidemiological trajectories. Kidney cancer has surpassed bladder cancer as the leading malignant urologic disease in women in regions such as North Africa and the Middle East. ASDRs for both kidney and bladder cancers were negatively associated with HDI, underscoring the disproportionate burden in low-resource settings due to delayed diagnosis and limited treatment access.⁴³ The long-term cancer control successes observed in North America, Oceania, and parts of Europe emphasize the importance of early detection and effective treatment.⁴⁴ While these cancers primarily affect older populations, kidney cancer also contributes substantially to DALYs in children, likely due to nephroblastoma and early-onset clear cell carcinoma.⁴⁵

Among modifiable risk factors, smoking remains the predominant contributor to DALYs from female bladder and kidney cancers. Despite a global decline in smoking prevalence since 1990, it continued to account for the largest share of bladder cancer-related DALYs in women throughout the study period. This highlights the persistent need for robust tobacco control policies, especially targeting youth and secondhand smoke exposure.^46,47 Although men are generally at higher risk for bladder cancer, women tend to be diagnosed at more advanced stages.^48,49 Sex differences in tumor detection may contribute to these disparities, with men more likely to receive early diagnosis.⁵⁰ Emerging evidence also suggests that sex hormones and their receptors may influence tumorigenesis and progression.^51–53 These findings underscore the necessity of gender-specific prevention and treatment strategies to reduce sex-based disparities in cancer outcomes. In addition, obesity, particularly abdominal obesity, is a well-documented risk factor for kidney cancer, with obese individuals showing a 1.32-fold higher risk than their non-obese counterparts.^54,55 We also observed an increasing contribution of elevated fasting plasma glucose to bladder cancer DALYs, pointing to the growing global burden of metabolic syndrome.⁵⁶ Strong evidence supports the role of lifestyle interventions, such as physical activity and balanced diets, in mitigating cancer risk.^57,58 Therefore, alongside anti-smoking measures, strategies to enhance metabolic health including diabetes management and nutritional guidance should be prioritized in future cancer control efforts targeting women.

While our study offers the most recent GBD-based estimates on the global burden of four common urologic diseases in women, it is subject to several limitations. First, like all GBD studies, the quality and completeness of data vary across countries, particularly in low- and middle-income settings where robust epidemiological data are often lacking. Biases in diagnostic criteria and data reporting in primary studies also affect accuracy.^18–20,24 Second, the impact of the COVID-19 pandemic introduces uncertainty in mortality estimates, especially in heavily affected regions. Third, our focus was limited to UTIs, urolithiasis, kidney cancer, and bladder cancer, excluding other urologic conditions that may be significant. Fourth, definitional constraints in the GBD database may lead to underestimation of disease burden. Fifth, differences in diagnostic practices across countries and over time could limit comparability. These limitations necessitate a cautious interpretation of global burden trends and call for improved data collection, harmonized diagnostic criteria, and complementary analytical approaches to validate our findings. Lastly, the GBD risk analysis is literature-based and may not account for all disease-specific risk factors.

Conclusion

Urologic diseases in women pose a growing global health challenge. The burden of UTIs and kidney cancer continues to rise with aging populations, while urolithiasis and bladder cancer are declining. Disparities in healthcare access and prevention have led to a polarized disease burden across countries. The rising impact of metabolically related cancers highlights the need for better metabolic health management. Strengthening global collaboration to develop effective screening and targeted, gender-sensitive strategies is essential to reduce the burden of these diseases.

Abbreviations

DALYs, disability-adjusted life-years; ASR, age-standardized rate; ASIR, age-standardized incidence rate; ASDR, age-standardized DALYs rate; EAPC, estimated annual percentage change; UI, uncertainty interval; SDI, socio-demographic index; HDI, human development index.

Ethics Approval and Consent to Participate

The study got an exemption from the Ethical Review Committee of the Fourth Affiliated Hospital of School of Medicine, Zhejiang University, because it used publicly available and deidentified data from GBD database.

Disclosure

The authors report no conflicts of interest in this work.

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41. Prochaska M, Taylor EN, Curhan G. Menopause and risk of kidney stones. J Urol. 2018;200(4):823–828. doi:10.1016/j.juro.2018.04.080

42. Borofsky MS, Lingeman JE. The role of open and laparoscopic stone surgery in the modern era of endourology. Nat Rev Urol. 2015;12(7):392–400. doi:10.1038/nrurol.2015.141

43. Lunyera J, Kilonzo K, Lewington A, Yeates K, Finkelstein FO. Acute kidney injury in low-resource settings: barriers to diagnosis, awareness, and treatment and strategies to overcome these barriers. Am J Kidney Dis. 2016;67(6):834–840. doi:10.1053/j.ajkd.2015.12.018

44. Fitzgerald RC, Antoniou AC, Fruk L, Rosenfeld N. The future of early cancer detection. Nat Med. 2022;28(4):666–677. doi:10.1038/s41591-022-01746-x

45. Salzillo C, Cazzato G, Serio G, Marzullo A. Paediatric renal tumors: a state-of-the-art review. Curr Oncol Rep. 2025;27(3):211–224. doi:10.1007/s11912-025-01644-8

46. Purdue MP, Silverman DT. Clearing the air: summarizing the smoking-related relative risks of bladder and kidney cancer. Eur Urol. 2016;70(3):467–468. doi:10.1016/j.eururo.2016.04.009

47. Cumberbatch MG, Rota M, Catto JW, La Vecchia C. The role of tobacco smoke in bladder and kidney carcinogenesis: a comparison of exposures and meta-analysis of incidence and mortality risks. Eur Urol. 2016;70(3):458–466. doi:10.1016/j.eururo.2015.06.042

48. Dobruch J, Daneshmand S, Fisch M, et al. Gender and bladder cancer: a collaborative review of etiology, biology, and outcomes. Eur Urol. 2016;69(2):300–310. doi:10.1016/j.eururo.2015.08.037

49. Doshi B, Athans SR, Woloszynska A. Biological differences underlying sex and gender disparities in bladder cancer: current synopsis and future directions. Oncogenesis. 2023;12(1):44. doi:10.1038/s41389-023-00489-9

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A recent study demonstrated the efficacy and safety of subcutaneous venom immunotherapy (VIT) in children with a Hymenoptera venom allergy.¹

“The results showed that the cluster protocol represents a safe and effective treatment in children, with a low rate of SR (0.4% in relation to the total number of doses administered) and none requiring epinephrine,” wrote study investigator Mattia Giovannini, from the University of Florence and the allergy unit at Meyer Children’s Hospital IRCCS in Florence, Italy, and colleagues.

VIT, recommended for patients with a history of systemic reactions to stings who test positive for venom-specific allergens, remains the sole proven treatment for venom allergy.² Extensive research has examined the safety of venom immunotherapy, but data on adverse reactions and their predictive risk factors in children remain limited.¹

In this study, investigators sought to evaluate the safety of VIT, identify factors linked to adverse reactions, assess the accuracy of insect identification and its impact on VIT extract selection, and determine treatment efficacy by examining adverse reactions following re-sting. The team retrospectively analyzed the medical charts of 58 patients < 18 years followed up at the Allergy Unit of Meyer Children’s Hospital IRCCS in Florence, Italy, who received VIT between 1997 and 2021.

Participants were mostly male (87.9%) and had a median age of 9.4 years. The median VIT duration was 5.4 years, and the median number of injections per patient was 63.4 years. Nearly half (47.7%) had a positive family history of atopy, and 27.6% presented atopic manifestations, including rhinoconjunctivitis (18.9%), asthma (6.8%), food allergy (6.8%), and atopic dermatitis (5.2%).

A diagnostic workup, conducted in line with the European Academy of Allergy and Clinical Immunology guidelines and the Italian Consensus on Hymenoptera venom allergy management, guided clinicians in selecting the VIT extract. The study examined 4 extracts: Apis mellifera (28.4%; n = 17), Vespula (33.3%; n = 20), Polistes (33.3%; n = 20), and Vespa crabro (5%; n = 3). Following 3739 injections, 335 adverse reactions occurred (9.5%), classified as local reactions (8.2%; n = 306), extended local reactions (0.9%; n = 34), and systemic reactions (0.4%; n = 15).

The study included both build-up and maintenance phases. During the buildup phase, clinicians administered 1120 injections, with 194 adverse reactions reported; most were local reactions (8.2%). The maintenance phase included 2619 injections, with 161 adverse events reported; 84.5% were local reactions.

Compared to the maintenance phase, the build-up phase was associated with a greater number of adverse and local reactions during VIT (P < .0001). The study found no differences between the build-up and maintenance phases for extended local reactions (P =.5) or systemic reactions (P =.35). The study identified no other significant factors related to the risk of developing any adverse reaction.

Systemic reactions occurred the most during VIT for Polistes (0.5%). The study found no significant differences in allergic reactions across the venom extracts.

In total, 31 patients reported 51 re-stings following VIT. Among these patients, only 2 (3.9%) experienced a systemic reaction after their re-sting, and these reactions occurred from a different Hymenoptera species than the one targeted during VIT.

The study also found that males had a lower risk of adverse reactions compared with females. No statistically significant associations emerged for age at VIT initiation or family history of atopy.

Furthermore, the study demonstrated that patients could easily identify mellifera and Vespa crabro but struggled to differentiate Vespula from Polistes before and after VIT initiation. Despite this finding, VIT demonstrated efficacy for treating venom allergies.

“The present study confirmed that cluster protocol VIT is safe and effective in pediatric patients, with a low rate of [systemic reactions],” investigators concluded.¹ “The build-up phase was associated with a higher frequency of [adverse reactions], while factors such as sex, age, atopy, and type of venom extract showed no significant impact. VIT with Polistes venom had the highest [systemic reactions] rate, requiring further validation. Despite initial [systemic reactions], VIT demonstrated indisputable efficacy upon re-stinging, underscoring its value as an essential therapy for eligible patients.”

References

1. Giovannini M, Catamerò F, Masini M, et al. Efficacy and safety of subcutaneous venom immunotherapy in children: A 24-year experience in a pediatric tertiary care center. Pediatr Allergy Immunol. 2025;36(9):e70195. doi:10.1111/pai.70195

2. Dhami S, Nurmatov U, Varga EM, et al. Allergen immunotherapy for insect venom allergy: protocol for a systematic review. Clin Transl Allergy. 2016;6:6. Published 2016 Feb 16. doi:10.1186/s13601-016-0095-x

CAMBRIDGE, Mass., Sept. 3, 2025 /PRNewswire/ — Apnimed, Inc., a pharmaceutical company building the industry-leading portfolio of first-in-class oral drugs that address the root causes of obstructive sleep apnea (OSA) and other sleep-related breathing diseases, today announced multiple upcoming oral and poster presentations at the World Sleep Congress, which will take place September 5-10, 2025, in Singapore. The presentations will highlight AD109, the company’s lead investigational once-daily oral therapy for OSA, which recently reported two Phase 3 trials, LunAIRo and SynAIRgy, as well as results from the SHINE survey of US adults highlighting the significant real-world impact and burden of OSA.

Apnimed World Sleep 2025 Presentation Details:

Oral Presentations

Title: “A combination of antimuscarinic agents with selective norepinephrine reuptake inhibitors to treat OSA”
Session Title: S-01: Pharmacotherapy of obstructive sleep apnea in 2025
Session Date: Monday, September 8, 2025
Presentation Time: 9:18 AM – 9:34 AM SGT
Location: Hall 406C

Title: “Targeting upper airway muscle dysfunction in OSA: A new frontier in treatment”
Session Title: S-42: Revolutionizing personalized medicine in OSA: Exploring new treatment modalities
Session Date: Tuesday, September 9, 2025
Presentation Time: 9:50 AM – 10:06 AM SGT
Location: Hall 406C

Poster Presentations

Title: “Impact of Obstructive Sleep Apnea on Daily Life by Disease Severity Level: Analysis from the SHINE Survey”
Session Title: Poster abstract group 1
Session Date: Sunday, September 7, 2025
Presentation Time: 5:00 PM to 6:00 PM SGT
Poster Board Number: 369

Title: “Unmasking Obstructive Sleep Apnea: Estimated Prevalence and Impact in the United States“
Session Title: Poster abstract group 2
Session Date: Monday, September 8, 2025
Presentation Time: 6:30 PM to 7:30 PM SGT
Poster Board Number: 364

Title: “Demographic and Baseline Disease Characteristics of SynAIRgy: A Phase 3 Trial of Aroxybutynin and Atomoxetine (AD109) in Obstructive Sleep Apnea”
Session Title: Poster abstract group 3
Session Date: Tuesday, September 9, 2025
Presentation Time: 4:45 PM to 5:45 PM SGT
Poster Board Number: 379

Title: “The SHINE Survey: Uncovering Gender Differences in Psychosocial Burden of Obstructive Sleep Apnea”
Session Title: Poster abstract group 3
Session Date: Tuesday, September 9, 2025
Presentation Time: 4:45 PM to 5:45 PM SGT
Poster Board Number: 346

Title: “Real-world Incremental Economic Burden of Fatigue among Patients with Obstructive Sleep Apnea in the Medicare Fee-for-Service Population”
Session Title: Poster abstract group 3
Session Date: Tuesday, September 9, 2025
Presentation Time: 4:45 PM to 5:45 PM SGT
Poster Board Number: 358

About AD109
AD109 is designed to be the first pharmacological treatment to improve oxygenation during sleep by directly addressing the neuromuscular root cause of upper airway collapse in people with obstructive sleep apnea. It is a first-in-class anti-apneic neuromuscular modulator, combining aroxybutynin, a novel antimuscarinic, and atomoxetine, a selective norepinephrine reuptake inhibitor (NRI). Their combined pharmacological synergy targets the underlying neuromuscular root cause of OSA. AD109 is an investigational, once-daily pill taken at bedtime that is designed to lower the complexity of intervention and may help more people benefit from effective, restorative sleep. In a disease characterized by complex and invasive treatment options, AD109 may be a simple solution to help improve oxygenation and wellbeing for people living with OSA.

About Obstructive Sleep Apnea
Obstructive sleep apnea (OSA) is a serious, chronic sleep-related breathing disease in which the upper airway repeatedly collapses during sleep, leading to intermittent oxygen deprivation. It is caused by two overlapping mechanisms: neuromuscular dysfunction during sleep and predisposing anatomic abnormalities. OSA affects individuals across all walks of life, impacting both males and females of all age groups, ethnicities, and weight classes, including those with or without obesity. An estimated more than 80 million people in the United States and nearly one billion people worldwide suffer from OSA. Up to 80% of people living with OSA are undiagnosed and therefore untreated.

An individual with OSA can experience hundreds of sleep apnea events in a single night, each one reducing the blood oxygen levels and negatively impacting cellular functions vital to normal health and function. Failure to effectively treat OSA increases the risk of serious long-term health consequences, including cardiovascular disease, neurocognitive impairment, metabolic dysfunction, and early mortality. Yet, the majority of those diagnosed with OSA refuse, abandon, or underutilize treatment. Currently, no available pharmacological treatments directly address the underlying neuromuscular dysfunction that is present in OSA.

About Apnimed
Apnimed is a privately held, clinical-stage pharmaceutical company based in Cambridge, Massachusetts, dedicated to transforming the treatment landscape for sleep-related breathing diseases. We believe the introduction of simple, once-nightly oral drugs may dramatically expand diagnosis and the reach of treatment for people with OSA. OSA, like other common chronic diseases such as diabetes or hypertension, would benefit from having multiple drugs with differing mechanisms to more fully address the heterogeneity of disease pathophysiology. Apnimed envisions a new era where novel oral therapies simplify intervention, expand the reach of diagnosis and treatment, and help more people get the oxygen and restorative sleep needed to thrive.

Apnimed is advancing a robust pipeline of oral pharmaceutical product candidates designed to improve oxygenation in individuals living with OSA and other chronic sleep-related breathing diseases. Our lead candidate, AD109, could become the catalyst for a new oral treatment paradigm for OSA that has been historically limited to cumbersome devices or invasive surgeries. Apnimed is also developing several therapies as part of its joint venture with Shionogi & Co., Ltd., Shionogi-Apnimed Sleep Science. Learn more at apnimed.com or follow us on X and LinkedIn.

Media Contact:
[email protected]
Investor Contact:
[email protected]

SOURCE Apnimed, Inc.

Introduction

Heart failure (HF) is a significant global health problem with substantial morbidity and mortality, affecting an estimated 26 million people worldwide.¹ Due to its high readmission rates, poor prognosis, increasing frequency with an aging population and the rising prevalence of lifestyle risk factors, HF has become a major challenge in developed countries.² In Asian countries, HF prevalence ranges from 1.3% to 6.7%.³ With its unique healthcare system, China faces a comparable HF prevalence rate of 1.2%–2.2%.^4–7 The economic burden is significant, with 70–80% of HF treatment costs in wealthy nations borne by healthcare systems.⁸ In China, the average cost per capita for inpatients with HF is $4406, and 40.5% of inpatients require three hospitalisations.⁷

Despite advancements in medical tools and medications, HF management remains challenging for healthcare professionals. Among the various strategies, transitional care interventions are the most innovative programmes aimed at improving continuity of care from admission to post-discharge.^9,10 Transitional care refers to the steps taken during clinical interactions to ensure coordination and continuity of treatment for patients transitioning between facilities or care levels. However, inadequate planning, insufficient patient/family education and fragmented access to essential services contribute to disparities in the hospital-to-home transition.^11,12 These disparities are often exacerbated by limited financial resources, insurance coverage and social support.

In the transition stage from hospital to home following discharge for patients with HF, the coordination of subsequent care is crucial. This is closely related to the compliance challenges faced by patients in various aspects, such as medication treatment, diet control, exercise adherence and psychosocial adaptation. Such patients generally need to visit the emergency department more frequently and be hospitalised multiple times and for longer periods, and these situations often interact with and reinforce each other in relation to the above-mentioned compliance issues. It is worth noting that 50% of patients with HF will be readmitted within 1 year after discharge, and 20% of patients will even experience two or more readmissions. In-depth analysis of the reasons for readmission reveals that, in addition to symptom deterioration and disease progression, self-care compliance problems – such as poor medication adherence (eg missed or incorrect dosing), lax diet management (eg excessive sodium intake) and interrupted exercise plans – as well as psychosocial factors such as anxiety, depression or insufficient social support, and patients’ lack of awareness of when and how to seek help from medical staff are all important contributing factors. Imperfect discharge planning will further exacerbate these compliance problems, thereby causing pain and anxiety for patients.¹³ This will increase the risk of adverse events and medication errors, leading to a continuous decline in treatment compliance, including medication, diet and exercise, and ultimately reducing the quality of life of patients.¹⁴ Therefore, to achieve a smooth transition from hospital to home, it is necessary to specifically address the practical difficulties of patients with HF in aspects such as medication treatment norms, diet structure adjustment and exercise plan implementation while paying attention to their psychological and mental needs. Practice has shown that transitional care plans can effectively improve the quality of life of patients and reduce the readmission and all-cause mortality rates following hospitalisation of patients with HF by optimising the intervention measures related to the above aspects.⁹

The transition period is a critical phase in HF management, requiring collaboration among individuals with diverse backgrounds, experiences and abilities. While transitional nursing models have improved overseas, research in China remains fragmented, with no unified descriptions or conclusions.¹⁵ In China, hospital-to-home transitional care typically includes pre-discharge oral health education, post-discharge telephone follow-up and home visits by family physicians and transition nurses upon request. However, the lack of a unified implementation plan, evaluation standards and training for key personnel has resulted in significant variations and disparate research outcomes. Transitional care strategies are influenced by medical resources and cultural differences, necessitating localised policy formulation combined with standardisation. Prior research has not adequately described how Chinese patients with HF perceive care transitions. Understanding patients’ experiences and perceptions is essential to identifying gaps and optimising the transition process, ultimately improving patients’ quality of life.

This study examines the difficulties and obstacles patients with HF face during the transition to self-care, exploring their needs and challenges to inform the development of targeted health interventions.

Methods

This qualitative study employed a phenomenological approach to explore the transitional care experiences of patients with HF in China. The study was conducted between June 2023 and October 2023 at a tertiary hospital’s cardiology department.

Participants were recruited using purposive sampling to ensure diversity in age, gender and urban/rural residence. The inclusion criteria included (1) confirmed diagnosis of HF (NYHA Class II–IV); (2) discharged from the hospital within the past 3 months; and (3) ability to communicate in Mandarin. The exclusion criteria included severe cognitive impairment or terminal illness. Based on the method of “theoretical saturation”, we continuously recruited volunteers before thematic saturation was reached. When we interviewed the 15th and 16th volunteers, we found that the difficulties, ideas and needs mentioned by the newly arrived patients were essentially the same as those of the previous patients, and no new information was introduced. The final sample, therefore, comprised 18 participants.

Data were collected through semi-structured, face-to-face interviews conducted in a private hospital room. The interview guide was developed based on a literature review and pilot-tested with three patients with HF (not included in the final sample). Key topics included challenges during the hospital-to-home transition, self-care practices and knowledge gaps, and perceived support needs and barriers. The interviews lasted 30–60 minutes and were audio-recorded and transcribed verbatim within 48 hours. Field notes were taken to capture non-verbal cues and contextual details.

Transcripts were analysed using Braun and Clarke’s six-step thematic analysis framework. The process began with familiarisation through repeated reading of transcripts to identify initial patterns. Initial coding was performed line-by-line using NVivo 12 software, followed by grouping codes into potential themes based on shared meaning. Themes were refined through iterative discussions among the research team, clearly defined and named, and finally used to select illustrative quotes and draft the results.

To ensure methodological rigor, several strategies were employed. Two researchers independently coded 20% of the transcripts, achieving a kappa value of 0.82, indicating excellent inter-coder agreement. Discrepancies were resolved through discussion and consensus. Preliminary findings were shared with five participants for member checking to confirm accuracy and relevance. Data were cross-verified with field notes and hospital discharge records for triangulation. The research team maintained a reflective journal to document biases and assumptions throughout the study.

Most of the patients were taking diuretics. Some patients with other comorbidities were also taking other medications, such as antihypertensive drugs and antidiabetic drugs. All patients were treated and cared for in the same hospital ward, meaning they received the same care. No complications occurred during hospitalisation. There was no follow-up intervention following discharge.

The study was approved by the hospital’s ethics committee. Written informed consent was obtained from all participants, who were assured of confidentiality and the right to withdraw at any time.

Results

Through qualitative analysis, three themes were identified: 1) challenges faced (seeing in Table 1); 2) deficits in self-care during the transition (seeing in Table 2); and 3) the desire for help and support (seeing in Table 3).

Table 1 Post Admission Challenges

Table 2 Dilemma in Self-Care During the Transition

Table 3 Lack of Understanding Regarding Medication Regimen

Challenges Faced

Transition Difficulties

When participants discussed the impact of HF on their lives, most stated that the disease resulted in additional tasks. At the same time, significant changes emerged, both emotionally and in daily life. The sudden transition from hospital to home led to a certain amount of stress:

Actually, I didn’t exactly know about HF, I only had a cold before. After I got HF and had the symptoms, I didn’t know how to take care of myself. I really didn’t know this disease. I have no idea how to treat it. (P15)

I don’t know this disease as well. I sometimes have the impression of not being able to place the exact location of the discomfort in my body. I live in a rural area where there are few medical resources. I must go to the city to see the doctor. It’s really inconvenient for me. (P7)

Some of those interviewed stated that these new changes included the body’s current state and whether they could cope with self-care challenges. The transition from being healthy to being seriously ill had a substantial psychological impact on them:

When I got this disease, I felt really tired after I did the cleaning at home. I really hate that, it made me feel I’m useless. (P10)

Even though I did the treatment and felt better, it still cannot be compared with before. That made me feel like I’m no longer a normal person. (P4)

Overall, HF was a disease that sapped their energy. Some participants stated that they could formerly accomplish everything but now carefully manage their time and energy usage. They complete various activities with lower physical fitness, meaning the time spent with family and friends is shortened. Due to their diseases, the participants had to slow down their pace of life to adapt to new life situations:

Before, I could take a walk or dance after I finished dinner, but now these activities make me feel tired. Like before I could walk for around half an hour or an hour, now when I walk around 20 steps or less, I need to have a break and take a breath. You know… Like if you cannot walk for a long time, how do you expect you can dance like before? (P10)

After I got this disease, to be honest, I cannot walk too far away, my leg muscles became weaker than before, and they cannot support me for a longer time to do the labour on the farm. So, I have to give up my career due to that reason. (P3)

I used to be able to plant 20 acres of land by myself, but now I can’t do it anymore. Now my wife is farming. The main reason for the decrease in activity is my physical problems. (P14)

Some patients also described the hospital as a safe environment for them. Following transition, they were often unprepared for the sudden change in environment and felt insecure and overwhelmed. At home, patients engaged in self-care without supervision and managed their health status, creating anxiety and stress. Self-monitoring, especially while the patient is on medication, brings a certain amount of stress:

The main problem is my blood sugar level and blood pressure are hard to control. Also, every time I went to the hospital, the different doctors gave me different suggestions about how to use the medicines. It makes me feel confused. (P6)

Maybe… I will encounter more problems when I return to my work. The workplace is unlike home, where I can eat regularly and healthily. There may not be a canteen in the workplace, so I must go out to eat every day. I’d like to know how my blood sugar will fluctuate if my diet changes. (P5)

Monitoring New Body Signals

Several participants reported that after receiving a diagnosis of HF, they gained a deeper understanding of their bodies through treatment and daily self-care. Monitoring changes in the body becomes a new daily duty for patients. Some participants responded negatively and were unaware of the significance of the process, stating that they would only be monitored and treated when they were ill or exhibited symptoms:

I don’t monitor my blood pressure regularly. I only measure it when I feel uncomfortable (P1)

As for my intake and output, I generally don’t drink water when I’m not thirsty, and I will drink some water if I’m sweating in hot weather. I will take two pills if I feel uncomfortable and have chest tightness. (P14)

I care about only my heart rate and blood pressure. [I] measure [blood pressure] whenever I feel sick. (P2)

Some participants also stated that they will now actively monitor their body indicators regularly, and actively pay attention to their health:

I measure [blood pressure] four times daily and take a notebook to write down the number because it’s hard to remember all the data. Usually, the blood pressure is highest in the morning of the day. Moreover, I pay more attention to my input and output. For example, if I drink three cups of water all day, I know how much I can excrete. The doctor told me I must excrete as much water as I drink. So… I usually pay more attention to my intake and output. (P11)

Negative Social Status

Most participants had a negative attitude toward socialising, with HF having negatively affected their social and communication skills. Physical fatigue means they are unable to actively participate in family and friends’ gatherings as previously. The disease-related restrictions on living habits and diet also make them avoid certain occasions, meaning they spend more time at home:

I didn’t have any concerns before I got sick, but now I don’t go out frequently. I don’t go to drinking and smoking occasions anymore. (P9)

Before I got sick, I loved going out and spent most of my time outside. Now I feel tired physically, and there are fewer entertainment activities like going out. When I am at home, I like to be alone. (P5)

Some participants also mentioned social avoidance, preferring to close themselves off and resist communicating with others. The sense of inferiority and stigma brought about by the disease makes them eager to escape from their previous social circle and prefer being alone:

I used to be very social, but now I don’t like to talk. This is a big change… I don’t seem to be talkative anymore. (P4)

From the bottom of my heart, I don’t wanna go out or meet other people. It’s just annoying for me. (P14)

[I] go out less, and I prefer to stay by myself. Communication with others is less, and I also don’t want to join parties or other activities. (P7)

Coping with the Challenges

Some participants stated that the disease has allowed them to re-understand themselves, motivated them to change themselves, abandon some of their past bad living habits and better understand the importance of correct health concepts for their physical health:

I didn’t care about my body’s health before, but now I feel that my health is the most important thing. I didn’t have much motivation to quit smoking and drinking before. This time, I must quit immediately. Health is the most important, right? I have a better sense of health. (P9)

Although the participants faced the daily challenges of a HF diagnosis, they were dealing with their health issues. Although some patients had experienced the pain of the disease, they were still full of confidence and hope for the future:

As long as I am in good health, I can also take care of myself, and I can work again… I hope to work again. If I get better, I will still dance. (P15)

Deficits in Self-Care During the Transition

Lack of Knowledge and Education

During the interviews, most participants expressed a lack of knowledge and education about the disease, especially those who had been ill for a short period and often did not understand their condition. They did not know how to care for themselves. Some patients even demonstrated a negative and indifferent attitude, with some not understanding their current state of illness, not wanting to learn about the disease and not caring about treatment options and self-care:

I think I’m OK, I don’t need help… and I don’t wanna know the disease and what to do for follow-up appointments. (P12)

However, most patients are concerned about their bodies and are eager to understand and have this knowledge. After returning home from the hospital without professional care, learning more about HF and self-care priorities could help them better adjust to the transition and increase their confidence in self-care:

I don’t know anything about my disease. I would also like to learn [about it]… I know less about HF. (P3)

Medically, it would be wonderful to give me some information, like how to rest well and protect my body. I don’t know much about diseases. (P15)

Furthermore, participants stated that they typically used the internet to learn about related knowledge. The information on the internet is mixed; some may lack rigor or be published without any scientific basis. Patients are attempting to care for themselves after being discharged from the hospital without professional supervision. This lack of systematic and proper understanding may raise the patient’s psychological burden and have negative consequences:

The educational video… sometimes this video may cause some bad effect because there is good and bad content on the network. And I don’t know what video is suitable for me… [to] watch these contents instead has some side effects, like increasing the psychological burden. (P4)

Self-Medicating

Taking medication correctly is one of the most critical self-care tasks for Chinese patients following discharge. Many patients are often overwhelmed by abnormal conditions without complete transition care. Without the guidance of a medical professional, patients are often confused about how to administer their medications, with most wanting hospitals to provide professional assistance with medication administration:

I want to discuss issues related to my condition with a professional. For example, should I be taking a dose of the drug? (P2)

Which medications need to be adjusted? Who can I talk to about my problems? I hope to call or send a message to ask. It is more convenient to contact them through the internet, like medication guidance. (P1)

Some patients also expressed a desire for help from a specialised doctor or professional. Patients may have residences and hospitals in different cities and seek nearby medical resources when health abnormalities arise. They may receive different advice and medication regimens when visiting different hospitals and doctors. In such cases, patients often do not know whom to listen to, leading to anxiety and feeling overwhelmed:

I don’t know what I should sometimes do. Different hospitals’ doctors give different prescriptions, and I’m confused as to whom to listen to… whether there is a uniform standard. (P6)

The Desire for Help and Support

Support from Caregivers

Twelve of the 15 participants reported receiving varying degrees of care from their caregivers. Heart failure affected their physical health and made it difficult for them to participate in heavy work or daily activities. In this situation, they could not move alone or do without the help of a caregiver, meaning the caregiver has a significant role for them. The demographic characteristics of these participants, including age, gender and education, are summarised in Table 4.

I need someone to take care of me. I [can] hardly take care of myself. (P10)

My children take care of me, doing my laundry and cooking. (P4)

My mother and my husband are my caregivers. They care for my daily life, and I depend on them. (P12)

Table 4 Demographic Profile of HF Patients

Caregivers assisted in the participants’ self-care in addition to their daily routines. The patients were physically and mentally dependent on their caregivers:

I bought a blood pressure monitor, and my son helped me to measure my blood pressure. I can’t do it by myself. (P15)

In addition to taking care of the daily life of the participants, some caregivers of the participants also have to undertake the nursing tasks of the participants. They were reluctant to become more involved in self-care and were not even aware of their condition or the medications they were taking. Some patients defer to their caregivers for their daily food and medications:

[I] take my medication on time, but I don’t understand how each medication affects. My daughter knows, I listen to my daughter anyway. (P12)

Medication is on time. Then my family members are directly assigned the medication before giving it to me. (P4)

Usually, my family members remind me to take my medication, and there is no need to remember what medication to take by myself. I don’t care about the therapeutic effects of each drug. (P10)

The Need for Hospital Assistance

Most participants indicated that they often had many problems and disturbances in their daily life during the transition period due to their illness, and the lack of professional knowledge in coping left them feeling overwhelmed. Therefore, some participants wanted more support and help from the hospital, as well as professional guidance to help them transition smoothly from hospital to home and increase their self-care skills:

I think it’s better to talk with doctors about my problems face to face. I would like to learn more about my disease. (P15)

For example, why is my pulse suddenly low? What is causing my high blood pressure? How to deal with low blood pressure? Anyway, I hope the doctor can explain all of this, and I can take better care of myself after the explanation. I want to know what to do if I encounter different symptoms or situations. (P11)

Some participants indicated that the doctor who treated them in the hospital was the professional they trusted the most. They were also eager for their doctor to provide them with regular help and support long after they were discharged from the hospital:

It just feels like I want to go to a professional to talk about these things. Like, what to do if my heart rate is high? Should I increase or decrease the dosage of my medication? I want long-term regular professional guidance for my disease. I hope the hospital will take the initiative to provide a follow-up consultation. (P2)

Anyway, I will ask the attending doctor when I feel uncomfortable I must go to the hospital if I feel unwell. (P11)

Social and Government Support

Some participants mentioned the lack of caregiving staff when they described their difficulties during the transition. With the care of doctors and nurses during hospitalisation, family members were less involved. However, the caregiving responsibility shifts to family members after the patient returns home. Most patients need the assistance of caregivers, but caregivers have multiple identities and jobs simultaneously, meaning they are sometimes overwhelmed when it comes to caring for patients. Patients, therefore, prefer to have a community or other support to assist with self-directed daily caregiving:

The problem I am facing now is that there are not enough people to care for me. I have a son and a daughter-in-law, but they also need to care for two children. If I am hospitalised, my son and daughter-in-law will take care of me, and there will be no one to take care of the children. And I don’t have enough money to hire someone to care for me. (P10)

In addition to the lack of manpower, some families also have financial problems. Due to the disease, patients often lose their ability to work, and the cost of treatment and medication can be a significant expense for families. Some rural families in China have low total household income, which is further compounded when a family member loses the ability to work. Some participants are eager for support and help from government policies to ease their financial stress:

Medical bills are a bit unaffordable because the cost is so high. I wonder if I could apply for the serious illness subsidy in the community. I was wondering if it is possible to have something like this, and then I can apply it. (P10)

Now I can no longer farm. I’m a farmer, and no one can help me farm my land. Moreover, the subsidy given to me by the government is insufficient, and I have some financial difficulties. (P13)

Lack of Patient Education

We found that the so-called “patient education” (See Supplementary 1) often manifests itself in practice as a guidance sheet that is information-overloaded, full of jargon and requires patients to make complex self-judgments. Most of the interviewees said that they felt confused, anxious, and helpless to varying degrees after receiving such a single-page guidance.

Medication Adherence

Analysis revealed that the discharge guidance requires patients to “gradually increase the dosage” or “slowly reduce the dosage and discontinue” multiple medications according to their blood pressure and symptoms (as shown in P1 and P2). Such complex self-regulation requirements far exceed the capabilities of ordinary elderly patients, leading them to either not dare to make adjustments or make incorrect ones, resulting in anxiety and non-compliance. This explains why some interviewees stated that “I don’t know whom to listen to” and “I want to ask a professional”.

Diet and Lifestyle Modification

The analysis indicated that the suggestion of a “low salt and low fat” diet on the guidance sheet is too general and lacks specific and feasible operation guidelines. For example, no specific recommended daily salt intake or examples of food options are provided. This can result in the patient feeling at a loss when having to consume three meals a day after returning home. This explains why some interviewees were concerned about “what will happen when eating out” and “not knowing what to eat”.

Follow-Up Plan

Analysis revealed that the patient was required to coordinate follow-ups from multiple departments on their own and remember the re-examination items at different time points over a period of 1 year (as shown in P 2). This fragmented follow-up model imposes a heavy coordination and memory burden on patients and their families. This explains why patients want “hospitals to proactively offer follow-up consultations” and believe that “it would be great if there were someone to take care of me uniformly”.

Discussion

The aim of this qualitative phenomenological study was to investigate the lived experiences of patients with HF during the transition from hospital to home. By exploring the challenges, self-care deficits and support needs of these patients, this study provides valuable insights into the complexities of transitional care in China. The findings highlight the critical need for culturally sensitive interventions and systemic improvements to address the unique challenges faced by patients with HF.

Coping Strategies and Cultural Context

The participants in this study demonstrated diverse coping strategies in response to their HF diagnosis and the challenges of transitional care. While some patients exhibited avoidance behaviours, such as denying the significance of symptoms, these responses may reflect culturally influenced coping mechanisms rather than purely negative behaviours. In Chinese culture, patients often adopt an endurance strategy, which can be misinterpreted as avoidance but is rooted in cultural norms of resilience and self-reliance.¹⁶ This finding aligns with recent studies highlighting the importance of cultural context in understanding patient behaviours.¹⁷ For example, one study found that patients with chronic illnesses often prioritise maintaining harmony within their families over expressing personal distress, leading to similar coping behaviours.¹⁸ However, prolonged reliance on such strategies can delay symptom management and exacerbate emotional distress, underscoring the need for culturally tailored psychological support. Interventions that incorporate culturally adapted cognitive-behavioral therapy have shown promise in addressing these issues.¹⁹

Communication and Care Coordination

The study revealed significant communication breakdowns between healthcare providers and patients, contributing to confusion in self-care and medication management. While systemic issues, such as fragmented care and limited provider continuity, are primary contributors, individual factors also play a role. For example, patients’ health literacy levels and cognitive impairments can hinder effective communication.²⁰ Recent research emphasises the role of health literacy interventions in improving patient–provider communication and reducing medication errors.²¹ Similar findings have been reported in other low- and middle-income countries, where limited healthcare resources exacerbate communication challenges.²² Addressing these gaps requires a dual approach: systemic reforms to enhance care coordination and targeted interventions to empower patients with the knowledge and skills needed for self-care. For example, a study in South Korea demonstrated that structured discharge education programmes significantly reduced readmission rates among patients with HF.²³

Multidimensional Support Needs

The participants emphasised the importance of diversified support systems, including caregivers, healthcare providers and social resources. The caregiver–patient relationship, particularly in the Chinese context, is crucial but often underutilised. Recent studies have shown that caregiver training programmes can significantly improve patient outcomes by enhancing caregiver competence and reducing caregiver burden.²⁴ This is consistent with findings from Australia, where caregiver support interventions have been linked to improved patient self-care and reduced hospitalisations.²⁵ Additionally, the study highlights the need for integrated care models that bridge the gap between hospital and home, such as nurse-led transitional care programmes and community-based support networks. Similar models have been successfully implemented in Europe, where nurse-led HF clinics have been associated with reduced mortality and improved quality of life.²⁶

Study Limitations

This study has several limitations. First, the small sample size (n=18) and recruitment from a single tertiary hospital may limit the generalisability of the findings. Second, the lack of diversity in the sample, particularly the underrepresentation of rural patients, restricts the applicability of the results to broader populations. Third, reliance on self-reported data may introduce recall bias, and the absence of longitudinal follow-up limits our understanding of long-term transitional care outcomes. Future studies should aim for larger, more diverse samples and incorporate mixed-methods approaches to address these limitations. Finally, this study focuses on the common difficulties that patients will encounter psychologically and in daily life after being informed that they have HF, as well as during the process of returning home from the hospital. The study does not conduct separate research according to the types of HF. Future research could focus on whether there are differences in the difficulties experienced by patients with different forms of HF during the transition period and explore practical and feasible solutions to these problems.

Implications for Research, Practice and Policy

The findings of this study have important implications for improving transitional care for patients with HF in China. First, culturally sensitive interventions should be developed to address the unique coping strategies of Chinese patients. Second, systemic reforms, such as standardised discharge protocols and enhanced care coordination, are needed to reduce communication breakdowns and medication errors. Third, caregiver training programmes and community-based support networks should be prioritised to provide holistic support for patients and their families. Finally, future research should explore the long-term impact of transitional care interventions on patient outcomes, particularly in rural and underserved populations. These efforts should be informed by successful models from other countries, such as the UK’s integrated care pathways and Australia’s nurse-led HF management programmes.^27,28

To better operationalise these recommendations, based on the research findings concerning self-care in patients with HF transitioning from the hospital to their homes, we formulated a theoretical framework (for details, refer to Supplementary 2) to simulate the predicaments faced by patients with HF and the coping mechanisms used during the transition period. We also summarised the transitional care process for patients with HF in terms of three primary themes (see Figure 1): the post-admission challenges they face; the dilemmas in self-care during the transition; and the desire for help and support. Each theme encompasses several sub-themes that collectively highlight the emotional, physical and social complexities involved in managing HF. This condensed structure provides a succinct yet profound understanding of the participants’ experiences and the universal aspects of their transitional care journey.

Figure 1 Simulacrum of the hospital to home: The labyrinth of transition in the care of heart failure (HF) patients.

Conclusion

This study identifies three core findings regarding the transitional care experiences of Chinese patients with HF: significant post-discharge challenges (eg difficult adaptation, physical limitations and social withdrawal), critical self-care deficits (eg inadequate disease knowledge and confusion over medication management); and urgent unmet support needs (encompassing family caregiving reliance, sustained professional guidance and social/government assistance). These findings highlight the uniqueness of China’s context: rural–urban disparities exacerbate access barriers; fragmented healthcare systems hinder consistent care coordination; and over-reliance on family caregivers – shaped by cultural norms – burdens both patients and their families. To address these issues, targeted interventions are needed, including standardised discharge protocols with rural-specific adjustments, hospital-led telehealth platforms for credible health information and medication guidance, caregiver training programmes and expanded government subsidies for medical costs and community-based support services. Future research should explore multi-centre implementations of these strategies to validate their effectiveness across diverse populations, ultimately improving transitional care quality and patient outcomes in China.

Data Sharing Statement

All data generated or analyzed during this study are included in this published article.

Ethics Approval and Consent to Participate

This study was conducted in accordance with the declaration of Helsinki. This study was conducted with approval from the Ethics Committee of School of Nursing and Health, Henan University. Written informed consent was obtained from all participants, and participant informed consent included the publication of anonymous responses/direct quotes.

Consent for Publication

The manuscript is not submitted for publication or consideration elsewhere.

Acknowledgments

This dissertation was completed with the invaluable assistance of many individuals and organizations. I extend my deepest gratitude to the President, Vice President, Nursing Director, Nursing Supervisor, Chief Nurse, and staff at my hospital employer in China for their unwavering support. I am particularly grateful to Dr. Sheilla M. Trajera for her guidance and support during the dissertation process. My heartfelt thanks also go to the panelists, Dr. Toni-An B. Lachica and F. Lachica. Lastly, I thank my spouse Ma Hongjun, my parents, and my children, Ma Haosen and Ma Ruoyu, for their unwavering love and encouragement.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Funding

An empirical study on the construction and health management of digital virtual wards for elderly patients with heart failure in rural areas under the perspective of rural revitalization(26B330001).

Disclosure

The authors declare that they have no competing interests in this work.

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