Category: 8. Health

Antimicrobial resistance (AMR) is one of the gravest public health threats of our time—yet it remains largely invisible. In 2019, drug-resistant infections were linked to 4.95 million deaths globally, with 1.27 million of these directly caused by resistant pathogens, making AMR a leading global killer (The Lancet, 2022). This “silent pandemic” is not only a medical emergency; it is rapidly becoming an economic crisis.

Pakistan stands at the epicentre of this growing catastrophe. According to new national estimates, AMR was directly responsible for 59,200 deaths in the country in 2019 and contributed to an additional 221,300 fatalities—making it the third leading cause of death in Pakistan. By 2022, the number of drug-resistant infections rose to 1.15 million, with 64,690 deaths directly caused by AMR and over 306,000 deaths associated with it. These figures reveal a rapidly escalating burden that extends far beyond hospitals and clinics.

The Fleming Fund Country Grant Pakistan (FFCGP) emerged as a key player in the fight against AMR, investing in laboratory capacity, expanding surveillance systems across human and animal health sectors, and enabling critical research. Among its most consequential contributions is the first-ever national economic burden analysis of AMR in Pakistan—a groundbreaking study that has provided evidence to shape both policy and resource allocation. The findings are alarming: In 2022 alone, AMR cost Pakistan an estimated US$3.5 billion, or nearly 1% of the national GDP. These costs accrue from longer hospital stays, the need for expensive second- and third-line treatments, repeat diagnostic testing, and vast productivity losses due to premature deaths and disability. The economic burden is projected to rise to US$4.32 billion in 2023 and US$5.04 billion by 2025, amounting to 1.35% of GDP—a great loss Pakistan can hardly afford.

The World Health Organization has set bold targets: a 10% reduction in AMR-related deaths, 80% access to essential antimicrobials, and a ban on the use of last-resort antibiotics in agriculture

Behind these numbers are real human consequences. Drug-resistant infections disproportionately impact the poor, pushing families deeper into poverty. Treating a severe resistant infection can cost up to PKR 700,000 (US$3,100) per patient—an unaffordable sum for most households in a country where 38.3% of the population (93 million people) lives in multidimensional poverty. With limited financial protection and high out-of-pocket health spending, AMR doesn’t just threaten lives, it destroys livelihoods. Deepening this crisis is the unchecked misuse of antibiotics: over-the-counter sales of antimicrobials without prescription, poor diagnostic practices, limited awareness, and weak regulatory enforcement. Alarmingly, up to 70% of common infections in Pakistan no longer respond to first-line antibiotics, leading doctors to rely on more toxic and expensive last-resort medications. This fuels a dangerous cycle of resistance, illness, and financial strain.

Despite the clear and growing threat, Pakistan’s policy response remains vastly under-resourced. The proposed allocation for implementing the National Action Plan on AMR in 2025 is just PKR 923 million (US$3.29 million)—a figure that is less than one-thousandth of the anticipated annual economic loss due to AMR. This gap reflects a serious underestimation of the crisis and a lack of political urgency.

Globally, the World Health Organization has set bold targets: a 10% reduction in AMR-related deaths, 80% access to essential antimicrobials, and a ban on the use of last-resort antibiotics in agriculture. Pakistan must align with these global goals and commit to substantial investment, stronger governance, and robust public awareness.

AMR is dismantling health systems, undermining decades of medical progress, and draining national economies. For Pakistan, this is no longer a future threat—it is a present and growing emergency. Without swift, coordinated action and bold leadership, AMR may prove to be the defining health and development challenge of our generation. Further, shrinking donor support is leading to the closure of donor-supported programmes like the Fleming Fund Country Grant Pakistan, which calls for urgent action at national and international levels.

‘Instead of one pill, I prescribed ‘6 pills’

He said, “A 35-year-old consulted me today, as he wanted me to prescribe an aspirin pill to prevent a stroke. His father, aged 60, had recently suffered from stroke (paralysis), and he was concerned about his higher risk of getting a stroke in future. Instead of one pill (aspirin), I prescribed ‘6 pills’ (mentioned in the recommendations section of my prescription).”

So what did Dr Kumar actually prescribe to the man, who at the time, ‘weighed 80 kg, had a BMI (body mass index) of 26.2 with mildly elevated total and LDL cholesterol, normal homocysteine and cardiac evaluation’?

7-8 hours of sleep to 9-10K steps a day

As per the prescription he shared on X, Dr Kumar advised the man to follow these habits and come back for a ‘review after three months’:

1. Regular sleep: 7-8 hours a night.

2. Brisk walking or running: 30-40 minutes a day. Aim for 9-10K steps per day.

3. Healthy diet: Avoid soft drinks, sugar, and ultra-processed packaged foods. Reduce carb intake and increase fruits (within limits), vegetables, and nuts (a handful/day), poultry, fish, and eggs.

4. Reduce working hours: from current 13-14 hours to 8-9 hours.

5. Reduce stress.

6. Complete abstinence from alcohol.

Can aspirin prevent a stroke?

Aspirin is in a group of medications called salicylates. It works by stopping the production of certain natural substances that cause fever, pain, swelling, and blood clots. Sharing details of daily aspirin therapy, Mayo Clinic said that taking an aspirin a day can be a lifesaving option and may lower the risk of heart attack and stroke, but it’s not for everyone.

Per Mayo Clinic, daily aspirin therapy may be used in two ways:

⦿ Primary prevention

This means that you’ve never had a heart attack or stroke. You’ve never had coronary bypass surgery or coronary angioplasty with stent placement. You’ve never had blocked arteries in your neck, legs or other parts of the body. But you take a daily aspirin to prevent such heart events. The benefit of aspirin for this use has been debated.

⦿ Secondary prevention

This means that you had a heart attack or stroke, or you have known heart or blood vessel disease. You’re taking a daily aspirin to prevent a heart attack or stroke. The benefit of daily aspirin therapy in this situation is well established.

Note to readers: This report is based on user-generated content from social media. HT.com has not independently verified the claims and does not endorse them.

This article is for informational purposes only and not a substitute for professional medical advice.

Introduction

Diffuse large B-cell lymphoma (DLBCL) is an aggressive B-cell lymphoma, the most common pathological type of NHL, accounting for approximately 30% to 40% of all NHL cases across different geographical regions.^1,2 The median age at initial diagnosis of DLBCL is over 60 years, and 30% of patients are over 75 years old. The incidence of DLBCL increases with age.^3,4 Epidemiological studies indicate that DLBCL has a complex and multifactorial etiology, including genetic characteristics, clinical features, and immune disorders, in addition to risk factors related to viruses, environment, high weight in youth, and occupational exposure.^5,6 Although the prognostic significance of the International Prognostic Index (IPI) has been validated in many subtypes of NHL since 1993, its prognostic value in DLBCL remains controversial.

ABO blood group antigens, which play an important role in the physiology and pathology of cells, are defined by carbohydrate moieties on the extracellular surface of red blood cell membrane.^7,8 Our previous research has elaborated on the relationship between ABO blood group and lymphoma, and summarized the current knowledge of the underlying pathogenic mechanisms of the association.⁹ It has been observed that ABO blood group is not only associated with the risk and prognosis of lymphoma, but may also be associated with the pathological classification of lymphoma patients.⁹ However, we did not specifically compare DLBCL with other lymphoma subtypes in our previous research. Given this background, we conducted a retrospective study specifically focusing on a representative pathological type, namely DLBCL, with the aim of investigating whether ABO blood group correlates with the risk of onset and prognosis of this disease. This study provides preliminary and exploratory evidence supporting ABO blood group as a potential biomarker for DLBCL. Its cost-effective and readily accessible nature warrants further validation in larger-scale studies, which may offer novel perspectives for future understanding of DLBCL-specific disease risk stratification and prognostic assessment.

Materials and Methods

We retrospectively analyzed 220 patients with newly diagnosed DLBCL at two medical institutions between January 2012 and December 2022. The research was conducted in full compliance with the guidelines set forth in the Declaration of Helsinki and obtained official authorization from the Institutional Review Board of the First Affiliated Hospital of Henan University of Science (No. 2024–1592 Fast). All patients with DLBCL participating in this study met the following inclusion criteria: (1) A diagnosis of DLBCL was confirmed by specialized pathologists according to the World Health Organization (WHO) classification. (2) No prior anti-cancer treatment had been administered. (3) Data on ABO blood group was accessible. (4) Sufficient clinical, laboratory, and follow-up records were available. Exclusion criteria include: (1) Transformed from other types of lymphoma to DLBCL. (2) Suffering from other tumors or having a history of tumor. (3) Suffering from other severe systemic diseases.

The baseline clinical data of patients were collected, including gender, age, Eastern Cooperative Oncology Group performance status (ECOG PS), primary tumor location, extranodal invasion details (sites and count), B symptoms, treatment modalities and response, ABO blood group, Ann Arbor stage, serum lactate dehydrogenase (LDH) levels, baseline serum CRP levels, serum β₂-Microglobulin (β₂-MG) levels, cellular origin, and IPI score. Overall survival (OS) is defined as the duration extending from the date of first diagnosis until either the occurrence of death from any cause or the last recorded date, when patient data is censored.

Additionally, we randomly selected age- and sex-matched hospitalized patients as controls (case-control ratio = 1) from the same institutions. Controls were diagnosed with non-malignant, non-hematological, and non-immunological disorders based on surgery or other routine clinical management (eg, hernia, cholelithiasis, osteoarthritis, cataract). Computerized randomization ensured equal numbers of controls per institution relative to DLBCL cases. ABO blood group data for controls were retrieved from hospital information systems (HIS) or laboratory databases using identical procedures as cases.

Within the DLBCL patient cohort, associations between ABO blood types and baseline clinical/laboratory variables were evaluated using Chi-square test or Fisher’s exact test for categorical data. When performing multiple pairwise comparisons among different blood groups for a specific variable, the Bonferroni correction was applied, adjusting the significance level to α’ = α / [k(k-1)/2], where k represented the number of blood groups, to account for all possible pairwise comparisons. The Log rank test and Kaplan-Meier method was applied for a univariate survival analysis. Variables demonstrating a univariate association with OS at P < 0.2 were included in multivariate Cox proportional hazards regression models. Hazard ratios (HRs) with 95% CIs were reported for significant predictors. A two-tailed P < 0.05 was deemed indicative of statistical significance. The statistical software package SPSS 26.0 (SPSS Inc., Chicago, IL, USA) was used for statistical calculations.

Result

Patient Characteristics

A total of 220 patients diagnosed with DLBCL, including 101 males and 119 females, with a median age of 60 years, were enrolled in the study. The clinical characteristics of the patients are listed in Table 1. Of the enrolled patients, 166 (75.5%) exhibited an optimal performance status (ECOG PS 0–1). B symptoms were present in 76 patients (34.5%). Involvement of at least two extranodal sites was displayed by 81 patients (36.8%). Elevated LDH levels were observed in 111 (50.5%) patients. The serum CRP levels were available for 108 patients, and the serum β₂-MG data were available for 158 patients. Localized disease (stage I/II) was observed in 73 patients (33.2%). High-risk disease (IPI ≥ 3) was present in 79 patients (35.9%). Ki-67 antigen levels were available for 195 patients. Among the 220 patients with DLBCL, 115 (73.2%) originated from the non-germinal center B cell-like (GCB) subtype. The ABO blood group exhibited no significant association with patient age, gender, ECOG PS, B symptoms, the number of extranodal sites, LDH levels, CRP levels, serum β₂-MG levels, Ann Arbor stage, IPI score, Ki-67 levels, or cellular origin (all P > 0.05, Table 1).

Table 1 Basic Characteristics of DLBCL Patients in Distinct ABO Blood Type Groups

The Effect of ABO Blood Group on Risk of DLBCL

In the DLBCL cohort, the distribution of ABO blood types was as follows: blood type A in 66 patients (30.0%), blood type B in 56 patients (25.5%), blood type AB in 24 patients (10.9%), and blood type O in 74 patients (33.6%). A control group comprising 220 individuals with nonmalignant conditions was randomly selected for comparison. The distribution of ABO blood types within the control group was as follows: blood group A accounted for 65 patients (29.5%), blood group B accounted for 72 patients (32.8%), blood group AB accounted for 17 patients (7.7%), and blood group O accounted for 66 patients (30.0%). No statistically significant disparity was observed in the distribution of ABO blood groups between DLBCL patients and the control cohort (P = 0.301, Supplementary Table 1).

Upon conducting a gender-stratified comparative analysis, we identified a statistically significant disparity among female patients with DLBCL compared to the control group (P = 0.012, Figure 1). Conversely, an analysis of the ABO blood group distribution among male DLBCL patients relative to the control group revealed no statistically significant differences (P = 0.757, Figure 1).

Figure 1 Distribution of ABO blood types among DLBCL patients and controls by gender. Significant difference observed in females (P = 0.012, chi-square test); no significant difference observed in males (P = 0.757, chi-square test). Abbreviation: DLBCL, diffuse large B cell lymphoma.

In the study comparing female patients with DLBCL to a female control group without the disease, the prevalence rate of DLBCL were observed to be 54.5%, 34.3%, 70.0%, and 54.1% respectively in individuals with blood type A, B, AB, and O. To account for multiple pairwise comparisons across blood groups, Bonferroni correction was applied, yielding an adjusted significance threshold of α = 0.05/[4(4−1)/2] = 0.0083. Subsequent pairwise analysis demonstrated a significantly lower DLBCL risk in individuals with blood type B compared to blood type AB (P = 0.005, Table 2). No statistically significant differences in DLBCL risk were observed between other blood group pairs (P > 0.0083, Table 2).

Table 2 DLBCL and the Distribution of ABO Blood Groups in Females

The Effect of ABO Blood Group on Survival of Patients with DLBCL

By the conclusion of the final follow-up period, a cumulative total of 77 (35.0%) patients had unfortunately passed away. The deaths were due to tumor progression (n = 69), severe pulmonary infections (n = 5), cardiovascular disease (n = 1), and other causes (n = 2). The 3-year OS rates for blood type A, B, AB, and O groups were 51.0%, 58.8%, 74.9%, and 74.0%, respectively (P = 0.458, Figure 2). Upon stratifying by age groups, we observed that among patients with DLBCL aged over 60 years, the 3-year OS rates for blood type A, B, AB, and O groups were 32.0%, 23.7%, 87.5%, and 69.0%, respectively, yielding a statistically significant difference (P = 0.043, Figure 3a). Considering that DLBCL patients with blood type B had the shortest 3-year OS rate, we categorized those aged over 60 into two distinct groups: blood type B and non-B (A, AB, and O). Patients with blood type B demonstrated a significantly reduced 3-year OS rate compared to those with non-B blood types (23.7% vs 53.6%, P = 0.030, Figure 3b). In contrast, among DLBCL patients aged 60 years or younger, no significant difference in survival rates was observed between individuals with blood type B and those with non-B blood types, with 3-year OS rates of 83.3% and 73.7%, respectively (P = 0.196, Figure 3c). Given that the 3-year OS rates of patients aged over 60 years with A and B blood types were shorter than those with AB and O blood types, we conducted a further comparison between blood type AB/O and blood type A/B to investigate the impact of ABO blood type on survival outcomes. The analysis revealed that the OS for patients with A/B blood types was significantly shorter compared to those with AB/O blood types (P = 0.014, Figure 3d). Notably, the 106 DLBCL patients aged over 60 years shared a similar clinical background (all P > 0.05, Supplementary Table 2).

Figure 2 The Kaplan-Meier curves for OS in patients with DLBCL according to ABO blood type (P = 0.458 by Log rank test). Abbreviation: OS, overall survival; DLBCL, diffuse large B-cell lymphoma; A, blood type A; B, blood type B; AB, blood type AB; O, blood type O.

Figure 3 The Kaplan-Meier curves for OS in patients with DLBCL according to ABO blood type. (a): OS in patients aged >60 years stratified by blood types A, B, AB, and O c. (b): OS in patients aged >60 years comparing blood type B vs non-B (A, O, and AB) (P = 0.030 by Log rank test). (c): OS in patients aged ≤60 years comparing blood type B vs non-B (A, O, and AB) (P = 0.196 by Log rank test). (d): OS in patients aged >60 years comparing blood types A/B vs AB/O (P = 0.014 by Log rank test). Abbreviation: OS, overall survival; DLBCL, diffuse large B-cell lymphoma; A, blood type A; B, blood type B; AB, blood type AB; O, blood type O; A/B, blood type A and blood type B; AB/O, blood type AB and blood type O.

Univariate and Multivariate Cox Regression Analysis

Table 3 presented the findings from both univariate and multivariate regression analyses regarding potential predictors of OS in patients with DLBCL aged over 60 years. The univariate analysis indicated that Ann Arbor stage, LDH levels, IPI score, and ABO blood type were significant prognostic factors influencing OS in patients with DLBCL (P < 0.05). Blood type B was linked to a significantly shorter OS when compared to non-B blood types (HR 2.013, 95% CI 1.056–3.839, P = 0.034). In the multivariate analysis, IPI score ≥ 3 (HR 2.247, 95% CI 1.226–4.120, P = 0.009), elevated LDH levels (HR 1.890, 95% CI 1.015–3.520, P = 0.045), and blood type B (HR 2.050, 95% CI 1.069–3.933, P = 0.031) emerged as adverse factors for OS.

Table 3 Univariate and Multivariate Analysis of Prognostic Factors for OS in DLBCL Patients Aged Over 60 years

Discussion

In the present study, we found that females with blood type B might exhibit a reduced risk of DLBCL compared to those with blood type AB. The prognostic implications of ABO blood group distinctions were not apparent across the entire cohort of DLBCL patients. However, our analysis found notable prognostic significance associated with ABO blood group specifically among DLBCL patients aged over 60 years. Among these patients, those with blood type B experienced a significantly shorter OS compared to patients with non-B blood groups.

The ABO gene is located on chromosome 9q34 and encodes two alleles (ie, A and B) for specific glycosyltransferases that catalyze the covalent linkage of N-acetyl-D-galactosamine or D-galactose to a common precursor side chain (ie, the H antigen), eventually forming A and B antigens respectively.^10,11 Unlike the A and B alleles, the O variant encodes a non-functional glycosyltransferase, so the H antigen remains unmodified.¹² In recent years, researchers have found a possible association between ABO blood group and the development of cancers. Studies have indicated that individuals with blood type A may be at an increased risk of tumorigenesis, whereas those with blood type B appear to have a reduced risk.^13–17 Previous investigations did not observe statistically significant results regarding the correlation between ABO blood group and the risk of DLBCL.^18,19 This study provided evidence that among female patients, individuals with blood type B may have exhibited a decreased risk of developing DLBCL in comparison to those with AB blood types.

Epidemiological studies have shown that the incidence of DLBCL is significantly higher among males compared to females.²⁰ This disparity may be linked to the presence of estrogen in the female population. Studies propose that estrogen potentially exhibits antitumor properties, capable of inhibiting the proliferation and dissemination of tumor cells through a variety of mechanisms.²¹ It has been reported that the use of high-dose oral contraceptives for pregnancy prevention or exposure to estrogen via postmenopausal hormone replacement therapy may reduce the risk of aggressive lymphoma.²² Furthermore, B-cell lymphomas treated with estrogen receptor β were shown to have effectively inhibit tumor growth in vivo.²³ These findings provided additional evidence that estrogen played a significant role in the development and progression of lymphoma. The study suggested that, compared to females with blood type AB, those with blood type B might exhibit a reduced risk of developing DLBCL. The study suggested that, compared to females with blood type AB, those with blood type B might exhibit a reduced risk of developing DLBCL. We hypothesize that this may be partially mediated by the higher estrogen levels typically found in individuals with blood type B, though this remains speculative in the absence of direct hormonal measurements. Further research is warranted to substantiate this hypothesis.

There were few studies exploring the prognostic relationship between ABO blood groups and DLBCL, and the results were inconsistent. A study in Turkey revealed that there was no significant correlation between ABO blood groups and the prognosis of patients with DLBCL.¹⁹ This finding was consistent with the result of this study conducted among the entire cohort of DLBCL patients. Nevertheless, what distinguished it was that our subgroup analysis identified blood type B as a negative prognostic factor specifically for patients older than 60 years. Osada et al reported that DLBCL patients with blood type B had a shorter OS than those with non-B blood types, and this trend was more significant among male DLBCL patients.¹⁸ A large-scale, population-based study on DLBCL series showed that male patients had worse prognosis outcomes than female patients.²⁴ Although our study observed similar results in DLBCL patients aged over 60 years, we did not find any relationship between gender and the survival of DLBCL patients.

The underlying mechanisms of how the ABO blood group may interact with the development and progression of cancers, including lymphoma, are still poorly understood. Several plausible hypotheses have been formulated to elucidate the link between ABO blood group and cancer risk. It is hypothesized that the absence of blood group antigen expression – particularly A and B antigens – may enhance tumor malignancy by increasing cellular motility and migration, thereby correlating with adverse clinical outcomes and poorer overall prognosis.^25–27 Studies have indicated that the reduction or absence of ABO blood group antigen expression might be related to the deletion of ABO allele or relative down-regulation of the glycosyltransferase necessary for blood group antigen synthesis caused by hypermethylation of the ABO promoter region.^28–32 The absence of ABO blood group antigens has been observed in hematological malignancies, including Hodgkin’s lymphoma (HL).^33,34 We hypothesize that analogous mechanisms may be present in patients aged over 60 years with DLBCL, which could lead to the reduction or absence of B-type antigens, ultimately resulting in unfavorable prognostic outcomes. The glycosylation of ABO blood group antigens can lead to conformational changes in proteins that not only affect intercellular signaling, cell adhesion, and immune surveillance, but also stimulate tumor growth and metastasis.^35–40 Some studies have reported that the ABO gene locus is associated with circulating levels of tumor necrosis factor-alpha, soluble intercellular adhesion molecule (ICAM)-1, E-selectin, and P-selectin.^41–43 These adhesion molecules play a crucial role in the recruitment processes associated with chronic inflammation. Chronic inflammation is linked to tumor growth, invasion, and migration.^44–46 Chronic inflammation is also associated with lymphatic malignancies.⁴⁷ For example, the lymphomas that appear in mice deficient in GM-CSF and IFNγ are caused by infections and subside after antibiotic treatment.⁴⁸ Although this study did not find a significant association between ABO blood group antigens and CRP, there may be other inflammatory cytokines that serve as intermediaries linking ABO blood group antigens to DLBCL. It is possible that ABO blood group antigens influence tumor progression and metastasis by altering the inflammatory state of the host. ABO glycosyltransferase can regulate plasma von Willebrand factor (vWF) levels, affecting the risk of venous thromboembolism.^49,50 vWF plays an important role in inhibiting angiogenesis, promoting wound healing, and inducing tumor cell apoptosis; particularly, angiogenesis and apoptosis are also involved in tumorigenesis.^51–54 Therefore, ABO blood group may contribute to the development of tumors by regulating plasma vWF levels.⁹ In this study, we observed a case of patients with DLBCL and blood type B who died from a pulmonary embolism. We observed one blood type B patient dying from pulmonary embolism, suggesting thromboembolic events as another potential mechanism.

This study has several limitations. First, Retrospective design inherently restricts causal inference and may introduce unmeasured confounders. Second, Absence of data on estrogen levels precludes validation of the proposed biological hypotheses. Third, the relatively small sample size with regionally constrained recruitment limits population-level generalizability and increases susceptibility to selection bias. Last, reduced statistical power after Bonferroni correction for multiple comparisons may have obscured subtle associations between other blood group.

Conclusion

In summary, our research found that females with blood type B may have a lower risk of developing DLBCL compared to females with blood type AB. Furthermore, blood type B may serve as a poor prognostic factor for patients over the age of 60 who have DLBCL. To better understand the role of ABO blood groups in DLBCL, future studies are recommended in a large number of different populations (Asian, Caucasian, African) as well as in various regions.

Data Sharing Statement

The original contributions presented in the study are included in the article/supplementary material. Further inquiries can be directed to the corresponding authors.

Ethics Approval and Consent to Participate

The studies involving humans were approved by the ethics committee of The First Affiliated Hospital of Henan University of Science and Technology. The studies were conducted in accordance with the local legislation and institutional requirements. All participants confirmed their informed consent by responding to yes/no inquiries. All information collected from this study was treated with utmost confidentiality.

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 supported by the Doctoral Research Funds of Henan University of Science and Technology.

Disclosure

The authors report no conflicts of interest in this work.

References

1. Swerdlow SH, Campo E, Pileri SA, et al. The 2016 revision of the world health organization classification of lymphoid neoplasms. Blood. 2016;127(20):2375–2390. doi:10.1182/blood-2016-01-643569

2. Armitage JO, Gascoyne RD, Lunning MA, Cavalli F. Non-Hodgkin lymphoma. Lancet. 2017;390(10091):298–310. doi:10.1016/S0140-6736(16)32407-2

3. Sehn LH, Salles G. Diffuse large b-cell lymphoma. N Engl J Med. 2021;384(9):842–858. doi:10.1056/NEJMra2027612

4. Liu Y, Barta SK. Diffuse large B-cell lymphoma: 2019 update on diagnosis, risk stratification, and treatment. Am J Hematol. 2019;94(5):604–616. doi:10.1002/ajh.25460

5. Cerhan JR, Kricker A, Paltiel O, et al. Medical history, lifestyle, family history, and occupational risk factors for diffuse large B-cell lymphoma: the interlymph non-hodgkin lymphoma subtypes project. J Natl Cancer Inst Monogr. 2014;2014(48):15–25. doi:10.1093/jncimonographs/lgu010

6. De Roos AJ, Schinasi LH, Miligi L, et al. Occupational insecticide exposure and risk of non-hodgkin lymphoma: a pooled case-control study from the interlymph consortium. Int J Cancer. 2021;149(10):1768–1786. doi:10.1002/ijc.33740

7. Mohandas N, Narla A. Blood group antigens in health and disease. Curr Opin Hematol. 2005;12(2):135–140. doi:10.1097/01.moh.0000153000.09585.79

8. Storry JR, Olsson ML. The ABO blood group system revisited: a review and update. Immunohematology. 2009;25(2):48–59. doi:10.21307/immunohematology-2019-231

9. Qin L, Gao D, Wang Q, et al. ABO blood group and the risk and prognosis of lymphoma. J Inflamm Res. 2023;16:769–778. doi:10.2147/JIR.S401818

10. Yamamoto F. Molecular genetics of ABO. Vox Sang. 2000;78(2):91–103. doi:10.1111/j.1423-0410.2000.tb00045.x

11. Yamamoto F, Cid E, Yamamoto M, Blancher A. ABO research in the modern era of genomics. Transfus Med Rev. 2012;26(2):103–118. doi:10.1016/j.tmrv.2011.08.002

12. Lowe JB. The blood group-specific human glycosyltransferases. Baillieres Clin Haematol. 1993;6(2):465–492. doi:10.1016/s0950-3536(05)80155-6

13. Poole EM, Gates MA, High BA, et al. ABO blood group and risk of epithelial ovarian cancer within the Ovarian Cancer Association Consortium. Cancer Causes Control. 2012;23(11):1805–1810. doi:10.1007/s10552-012-0059-y

14. Sheng L, Sun X, Zhang L, Su D. ABO blood group and nasopharyngeal carcinoma risk in a population of Southeast China. Int J Cancer. 2013;133(4):893–897. doi:10.1002/ijc.28087

15. Li X, Xu H, Ding Z, Jin Q, Gao P. Association between ABO blood group and HCV-related hepatocellular carcinoma risk in China. Medicine (Baltimore). 2016;95(49):e5587. doi:10.1097/MD.0000000000005587

16. Li X, Xu H, Gao P. ABO blood group and diabetes mellitus influence the risk for pancreatic cancer in a population from China. Med Sci Monit. 2018;24:9392–9398. doi:10.12659/MSM.913769

17. Huang JY, Wang R, Gao YT, Yuan JM. ABO blood type and the risk of cancer – Findings from the Shanghai Cohort Study. PLoS One. 2017;12(9):e0184295. doi:10.1371/journal.pone.0184295

18. Osada Y, Ito C, Nishiyama-Fujita Y, et al. Prognostic impact of ABO blood group on survival in patients with malignant lymphoma. Clin Lymphoma Myeloma Leuk. 2020;20(2):122–129. doi:10.1016/j.clml.2019.09.607

19. Ulu BU, Başcı S, Bakırtaş M, et al. Could blood groups have prognostic significance on survival in patients with diffuse large B cell lymphoma. Leuk Res. 2022;115:106810. doi:10.1016/j.leukres.2022.106810

20. Morton LM, Wang SS, Devesa SS, Hartge P, Weisenburger DD, Linet MS. Lymphoma incidence patterns by WHO subtype in the United States, 1992-2001. Blood. 2006;107(1):265–276. doi:10.1182/blood-2005-06-2508

21. Pierdominici M, Maselli A, Locatelli SL, et al. Estrogen receptor β ligation inhibits Hodgkin lymphoma growth by inducing autophagy. Oncotarget. 2017;8(5):8522–8535. doi:10.18632/oncotarget.14338

22. Lee JS, Bracci PM, Holly EA. Non-Hodgkin lymphoma in women: reproductive factors and exogenous hormone use. Am J Epidemiol. 2008;168(3):278–288. doi:10.1093/aje/kwn119

23. Yakimchuk K, Hasni MS, Guan J, Chao MP, Sander B, Okret S. Inhibition of lymphoma vascularization and dissemination by estrogen receptor β agonists. Blood. 2014;123(13):2054–2061. doi:10.1182/blood-2013-07-517292

24. Székely E, Hagberg O, Arnljots K, Jerkeman M. Improvement in survival of diffuse large B-cell lymphoma in relation to age, gender, international prognostic index and extranodal presentation: a population based swedish lymphoma registry study. Leuk Lymphoma. 2014;55(8):1838–1843. doi:10.3109/10428194.2013.853297

25. Hakomori S. Antigen structure and genetic basis of histo-blood groups A, B and O: their changes associated with human cancer. Biochim Biophys Acta. 1999;1473(1):247–266. doi:10.1016/s0304-4165(99)00183-x

26. Le Pendu J, Marionneau S, Cailleau-Thomas A, Rocher J, Le Moullac-Vaidye B, Clément M. ABH and Lewis histo-blood group antigens in cancer. APMIS. 2001;109(1):9–31. doi:10.1111/j.1600-0463.2001.tb00011.x

27. Dabelsteen E, Gao S. ABO blood-group antigens in oral cancer. J Dent Res. 2005;84(1):21–28. doi:10.1177/154405910508400103

28. Stellner K, Hakomori S, Warner GS. Enzymic conversion of “H1-glycolipid” to A or B-glycolipid and deficiency of these enzyme activities in adenocarcinoma. Biochem Biophys Res Commun. 1973;55(2):439–445. doi:10.1016/0006-291x(73)91106-6

29. Orlow I, Lacombe L, Pellicer I, et al. Genotypic and phenotypic characterization of the histoblood group ABO(H) in primary bladder tumors. Int J Cancer. 1998;75(6):819–824. doi:10.1002/(sici)1097-0215(19980316)75:6<819::aid-ijc1>3.0.co;2-y

30. Iwamoto S, Withers DA, Handa K, Hakomori S. Deletion of A-antigen in a human cancer cell line is associated with reduced promoter activity of CBF/NF-Y binding region, and possibly with enhanced DNA methylation of A transferase promoter. Glycoconj J. 1999;16(10):659–666. doi:10.1023/a:1007085202379

31. Kominato Y, Hata Y, Takizawa H, Tsuchiya T, Tsukada J, Yamamoto F. Expression of human histo-blood group ABO genes is dependent upon DNA methylation of the promoter region. J Biol Chem. 1999;274(52):37240–37250. doi:10.1074/jbc.274.52.37240

32. Gao S, Bennett EP, Reibel J, et al. Histo-blood group ABO antigen in oral potentially malignant lesions and squamous cell carcinoma–genotypic and phenotypic characterization. APMIS. 2004;112(1):11–20. doi:10.1111/j.1600-0463.2004.apm1120103.x

33. Scott GL, Rasbridge MR. Loss of blood group antigenicity in a patient with Hodgkin’s disease. Vox Sang. 1972;23(5):458–460. doi:10.1111/j.1423-0410.1972.tb03836.x

34. Bianco T, Farmer BJ, Sage RE, Dobrovic A. Loss of red cell A, B, and H antigens is frequent in myeloid malignancies. Blood. 2001;97(11):3633–3639. doi:10.1182/blood.v97.11.3633

35. Greenwell P. Blood group antigens: molecules seeking a function. Glycoconj J. 1997;14(2):159–173. doi:10.1023/a:1018581503164

36. Pinho SS, Reis CA. Glycosylation in cancer: mechanisms and clinical implications. Nat Rev Cancer. 2015;15(9):540–555. doi:10.1038/nrc3982

37. Stowell SR, Ju T, Cummings RD. Protein glycosylation in cancer. Annu Rev Pathol. 2015;10:473–510. doi:10.1146/annurev-pathol-012414-040438

38. Xu Y, Chang R, Xu F, et al. N-glycosylation at asn 402 stabilizes n-cadherin and promotes cell-cell adhesion of glioma cells. J Cell Biochem. 2017;118(6):1423–1431. doi:10.1002/jcb.25801

39. Läubli H, Borsig L. Altered cell adhesion and glycosylation promote cancer immune suppression and metastasis. Front Immunol. 2019;10:2120. doi:10.3389/fimmu.2019.02120

40. Reily C, Stewart TJ, Renfrow MB, Novak J. Glycosylation in health and disease. Nat Rev Nephrol. 2019;15(6):346–366. doi:10.1038/s41581-019-0129-4

41. Melzer D, Perry JR, Hernandez D, et al. A genome-wide association study identifies protein quantitative trait loci (pQTLs). PLoS Genet. 2008;4(5):e1000072. doi:10.1371/journal.pgen.1000072

42. Kiechl S, Paré G, Barbalic M, et al. Association of variation at the ABO locus with circulating levels of soluble intercellular adhesion molecule-1, soluble P-selectin, and soluble E-selectin: a meta-analysis. Circ Cardiovasc Genet. 2011;4(6):681–686. doi:10.1161/CIRCGENETICS.111.960682

43. Barbalic M, Dupuis J, Dehghan A, et al. Large-scale genomic studies reveal central role of ABO in sP-selectin and sICAM-1 levels. Hum Mol Genet. 2010;19(9):1863–1872. doi:10.1093/hmg/ddq061

44. Fernandes JV, Cobucci RN, Jatobá CA, et al. The role of the mediators of inflammation in cancer development. Pathol Oncol Res. 2015;21(3):527–534. doi:10.1007/s12253-015-9913-z

45. Singh R, Mishra MK, Aggarwal H. Inflammation, Immunity, and Cancer. Mediators Inflamm. 2017;2017:6027305. doi:10.1155/2017/6027305

46. Greten FR, Grivennikov SI. Inflammation and cancer: triggers, mechanisms, and consequences. Immunity. 2019;51(1):27–41. doi:10.1016/j.immuni.2019.06.025

47. Grivennikov SI, Greten FR, Karin M. Immunity, inflammation, and cancer. Cell. 2010;140(6):883–899. doi:10.1016/j.cell.2010.01.025

48. Enzler T, Gillessen S, Manis JP, et al. Deficiencies of GM-CSF and interferon gamma link inflammation and cancer. J Exp Med. 2003;197(9):1213–1219. doi:10.1084/jem.20021258

49. Ibrahim-Kosta M, Bailly P, Silvy M, et al. ABO blood group, glycosyltransferase activity and risk of venous thromboembolism. Thromb Res. 2020;193:31–35. doi:10.1016/j.thromres.2020.05.051

50. Ward SE, O’Sullivan JM, O’Donnell JS. The relationship between ABO blood group, von Willebrand factor, and primary hemostasis. Blood. 2020;136(25):2864–2874. doi:10.1182/blood.2020005843

51. Starke RD, Ferraro F, Paschalaki KE, et al. Endothelial von Willebrand factor regulates angiogenesis. Blood. 2011;117(3):1071–1080. doi:10.1182/blood-2010-01-264507

52. Franchini M, Frattini F, Crestani S, Bonfanti C, Lippi G. von Willebrand factor and cancer: a renewed interest. Thromb Res. 2013;131(4):290–292. doi:10.1016/j.thromres.2013.01.015

53. O’Sullivan JM, Preston R, Robson T, O’Donnell JS. Emerging roles for von willebrand factor in cancer cell biology. Semin Thromb Hemost. 2018;44(2):159–166. doi:10.1055/s-0037-1607352

54. Ishihara J, Ishihara A, Starke RD, et al. The heparin binding domain of von Willebrand factosr binds to growth factors and promotes angiogenesis in wound healing. Blood. 2019;133(24):2559–2569. doi:10.1182/blood.2019000510

Introduction

Klebsiella pneumoniae (KP) is a highly adaptable opportunistic pathogen and a major contributor to global mortality associated with antimicrobial resistance.¹ Taxonomically, it is a member of the family Enterobacteriaceae and genus Klebsiella. It is a Gram-negative, facultatively anaerobic bacillus characterized by the presence of a prominent capsule, frequent occurrence of pili, and the absence of both spores and flagella.² Based on virulence and pathogenic features, KP strains are broadly classified into two distinct types: classical KP (cKP) and hypervirulent KP (HvKP). Compared to cKP, HvKP exhibit potent virulence and are capable of causing community-acquired infections in otherwise healthy individuals. These infections involve multiple organ systems and can manifest as pneumonia, liver abscesses, endophthalmitis, and meningitis.³ According to systematic reviews, KP is a leading etiological agent of Gram-negative meningitis and bacteremia in low-and middle-income countries.⁴ Infections caused by HvKP are typically acute in onset, characterized by rapid progression to disseminated systemic infections, and associated with significant morbidity and poor prognostic outcomes. According to the 2017 Infectious Diseases Society of America (IDSA) recommendations, intraventricular drainage and intrathecal antibiotic administration may be implemented for meningitis patients with severe central nervous system (CNS) infections.⁵ In this case, the primary genetic markers of the hvKP strain were associated with rmpA and siderophore systems.

Case Presentation

The patient was a 63-year-old female with a four-year history of diabetes mellitus. She had been receiving drug treatment and was able to maintain a relatively normal lifestyle, although glycemic control remained poor. Before acute deterioration, for 72 hours, the patient developed prodromal symptoms including fatigue and anorexia. She presented to the emergency department with a 24-hour history of progressive delirium, altered mental status, and tympanic fever, and was subsequently hospitalized for urgent evaluation and treatment. Initial laboratory tests showed leukocytosis, with a white blood cell (WBC) count of 20.81×10⁹ /L (normal range: 4.0–9.5×10⁹ /L) and neutrophil predominance at 90.6% (normal range: 40.0–75.0%). Blood glucose was significantly elevated at 24.13 mmol/L (normal range: 4.1–5.9 mmol/L), and C-reactive protein (CRP) level was significantly elevated at 328.25 mg/L (normal range: ≤10 mg/L). Blood gas analysis indicated a pH of 7.49 (normal range: 7.35–7.45), PaO₂ of 83 mmHg (normal range: 80–100 mmHg), PCO₂ of 19 mmHg (normal range: 35–45 mmHg), HCO₃⁻ of 13.2 mmol/L (normal range: 21–27 mmol/L), and substantially elevated levels of lactic acid at 2.9 mmol/L (normal range: 0.9–1.7 mmol/L). Procalcitonin (PCT) was significantly elevated at 23.15 ng/mL (normal range: 0–0.05 ng/mL). Brain MRI scans revealed multiple intracranial infectious lesions accompanied by pneumocephalus (Figure 1A). Chest CT scans revealed bilateral lung inflammation, multiple pulmonary abscesses, and small bilateral pleural effusions (Figure 1B and C). Abdominal CT revealed cavitary changes in the right hepatic lobe (Figure 1D).

Figure 1 Imaging findings suggest multiple infectious lesions. (A) Brain MRI scan: multiple intracranial infectious lesions accompanied by pneumocephalus. Arrow points to the high signal areas in the temporal lobes. (B) Chest CT: multiple areas of consolidation in the right lung, with an arrow indicating one such consolidation. (C) Chest CT: mediastinal window shows consolidation with cavity in the right lung. Arrow indicates the cavity. (D) Abdominal CT: liver Abscess and arrow points to the liver lesion.

The patient was diagnosed with sepsis and admitted to the intensive care unit (ICU) for further treatment. Empiric antibiotic therapy was initiated with intravenous meropenem (2.0 g every 8 hours, administered for over 3 hours) in combination with linezolid (600 mg every 12 hours). Shortly thereafter, the patient exhibited progressive neurological deterioration, characterized by deepening coma, bilateral anisocoria, and respiratory distress. Mechanical ventilation was employed to manage dyspnea. Subsequently, a lumbar puncture was performed to access the cerebrospinal fluid (CSF), which appeared purulent and turbid (Figure 2D1), with an opening pressure of 375 mmH₂O (equivalent to approximately 3.68 kPa). Biochemical analysis of the CSF revealed the following abnormalities: elevated glucose 1.11 mmol/L, increased levels of chlorine at 119.3 mmol/L, elevated levels of protein at 10.36 mg/L, and significantly elevated nucleated cell count of 85000 × 10⁶/L (Table 1).

Table 1 Susceptibility Test Result of the Bronchoalveolar Lavage Fluid and Cerebrospinal Fluid Culture Was Obtained on October 14, 2022 (Day 2)

Figure 2 Cerebrospinal fluid (CSF) samples demonstrating varying degrees of appearance. (D1) Appearance of CSF on day 1. (D2–D5) The appearance of CSF following CSF exchange therapy and intrathecal injection was gradually cleared from day 2 to day 5.

On the second day of hospitalization, the patient demonstrated a deteriorated condition. The glasgow coma scale (GCS) score decreased from 7 to 4. Due to the high viscosity of the CSF, drainage was ineffective, prompting the placement of a lumbar cisternal drainage catheter via subarachnoid puncture to facilitate CSF replacement therapy. Daily CSF exchange therapy was initiated, involving the removal of 10 mL of CSF followed by the infusion of an equal volume of normal saline, for a total of approximately 30 mL per day. To further reduce inflammatory response and enhance antibiotic concentration, intrathecal injection of 3 mg dexamethasone combined with 50 mg amikacin was conducted following each CSF exchange. Concurrent intravenous anti-infective therapy was continued with meropenem (2.0 g every 8 hours) and linezolid (600 mg every 12 hours). This combined regimen of CSF exchange and intrathecal injections was continued for five consecutive days, CSF, during which the CSF was gradually cleared (Figure 2D1–D5).

On the fourth day after admission, KP was isolated from blood, bronchoalveolar lavage fluid (BALF), and CSF cultures (Table 2), with a positive string test indicative of a hypervirulent phenotype (Figure 3A and B). Whole-genome sequencing (WGS) further confirmed the hypervirulent phenotype of the KP strain, multilocus sequence typing (MLST) analysis confirmed that the isolate belongs to sequence type 65 (ST65-K1), identifying key virulence determinants including the rmpA transcriptional activator, aerobactin synthesis gene cluster (iucABCD), salmochelin siderophore system (iroBCDE), enterobactin biosynthesis genes (entABCDEFS), iron uptake-related genes (fepABCDG), type 3 fimbrial genes (mrkABCDFHIJ), type 1 fimbrial genes (fimABCDEFGHIK), and K1 capsular serotype-associated loci. Collectively, the clinical presentation and laboratory findings were consistent with the diagnosis of a disseminated infection due to HvKP (Table S1).

Table 2 Laboratory Data in Cerebrospinal Fluid Laboratory During Treatment

Figure 3 Klebsiella pneumoniae (KP) identification. (A) Shows a petri dish containing a bacterial culture on a blood agar plate. An arrow points to a specific colony morphology. (B) Blood agar plate showing positive string test for the KP isolated from the patient.

By the eighth day of hospitalization, the patient exhibited improvement in neurological functions, presenting with lethargy but able to open her eyes spontaneously. The motor function of the upper extremities was partially preserved, with the ability to perform simple command-based movements. However, due to persistent severe pulmonary infection, a tracheostomy was performed (Figure 4A and B). Ongoing treatment included intravenous antimicrobial therapy, which was de-escalated to ceftriaxone (2 g IV once daily) combined with moxifloxacin (0.4 g IV once daily), based on antimicrobial susceptibility testing. Supportive care comprised albumin infusion, parenteral nutrition, and symptomatic management.

Figure 4 Repeat chest CT on day 8 reveals bilateral cavitary infectious lung lesions. (A) Demonstrating right lower lobe consolidation (arrow). (B) Showing cavitation within the consolidated area and progression of the infection (arrow).

Following comprehensive treatment, the patient exhibited marked improvement in consciousness level, including regained spontaneous eye-opening and command-following movements of the upper extremities. Successful weaning from invasive mechanical ventilation was achieved on day 11 of hospitalization. Repeat brain MRI on day 11 demonstrated complete resolution of the previously identified purulent meningoencephalitis lesions (Figure 5A and B), while concurrent thoracic and abdominal CT scans revealed significant therapeutic response with >80% reduction in pulmonary and hepatic abscesses volumes (Figure 5C and D). A multidisciplinary team implemented a stepwise decannulation protocol on day 20, resulting in the successful removal of the tracheostomy tube and the initiation of structured neurorehabilitation. The patient was discharged on hospital day 33 after successful clinical cure. At discharge, final neurological examination revealed a GCS score of 15, preserved language function, and full muscle strength (grade V) in all four limbs, without residual neurological deficits. At the six-month follow-up, the patient could independently perform all activities of daily living.

Figure 5 Repeat imaging involving brain MRI, chest and abdominal CT scans on day 11. (A and B) Brain MRI shows that intracranial infection lesions have been cleared. (C) Chest CT shows that the right lung abscess has significantly reduced in size (arrow indicates lesion). (D) Abdominal CT shows that the liver abscess has significantly reduced in size (arrow indicates lesion).

Discussion

Etiologically, HvKP is primarily associated with community-acquired infections. It is significantly prevalent among Asian, Pacific Islanders, and Hispanic populations. While HvKP typically affects individuals with diabetes or a compromised immune system, it has also been shown to affect healthy individuals. Typically, the disease is invasive, with liver abscesses representing the most prevalent initial presentation, followed by metastatic infections such as endophthalmitis, pulmonary abscesses, meningitis, splenic abscesses, and necrotizing fasciitis. These infections progress rapidly, resulting in exacerbated neurological functioning and suboptimal prognostic outcomes.⁶ Additionally, studies have reported cases of post-traumatic systemic invasive infections due to HvKP.⁷ Studies indicate that diabetes is an independent risk factor for systemic HvKP infections, a phenomenon potentially attributable to the reduced immunity under hyperglycemic conditions.⁸

For instance, the patient in this case report had pre-existing diabetes, resulting in rapidly progressing disseminated infections involving the brain, lungs, and liver following HvKP infection. Key virulence factors for KP include capsular serotypes (K1 and K2), hypermucoviscous phenotype, virulence plasmids, lipopolysaccharides, iron acquisition systems, and fimbriae.^9,10 Hypermucoviscous KP strains expressing K1 and K2 capsular serotypes are strongly associated with treatment-resistant liver abscesses and recurrent invasive infections. HvKP exhibits enhanced iron acquisition capabilities, capsule production, and biofilm formation compared to cKP. These pathological mechanisms contribute to its enhanced invasiveness.¹¹ The ST65-K1 hypervirulent Klebsiella pneumoniae (hvKP) strain described in this study carries key virulence determinants, including the capsular hypermucoviscosity regulator rmpA and siderophore gene clusters. The rmpA gene drives excessive capsular polysaccharide expression, conferring a hypermucoid phenotype that promotes invasive dissemination. Concurrently, the siderophore clusters enable high-affinity ferric iron (Fe³⁺) scavenging, breaching host nutritional immunity in iron-restricted organs such as the liver, thereby confirming the diagnosis of the HvKP infection. Research has shown that HvKP-related mortality increases significantly with invasion of multiple organs (such as liver, brain, lungs), with reported mortality rates of 45% for KP meningitis.^12,13 Empirical antibiotic regimens for KP infections recommend cephalosporins combined with aminoglycosides. For intracranial infections, third-generation cephalosporins—such as ceftriaxone or cefotaxime—with high CSF penetration capability are recommended as first-line treatment options. Additionally, carbapenem agents—such as imipenem and meropenem—are recommended in cases where extended-spectrum β-lactamase (ESBL) production is suspected.¹⁴ Meropenem is recommended as the first-line therapy for severe infections involving multiple sites,¹⁵ particularly in critically ill diabetic patients undergoing intensive care.¹⁶ For HvKP, antibiotics with strong tissue penetration are highly recommended, coupled with abscess drainage in cases where the procedure is clinically feasible. In this case, percutaneous drainage was not conducted given the small size (3 cm) of the liver abscess size.¹⁷ HvKP-related intracranial infections progress rapidly, characterized by significantly high mortality rates, and an undefined optimal treatment duration. Studies indicate that survival and favorable neurological outcomes are associated with initial GCS scores ≤7 at the time of antibiotic initiation.¹⁸ Aztreonam, aminoglycosides, and carbapenems are the primary therapeutic options for KP meningitis, although they exhibit varying efficacy. According to the 2023 statistics from the CHINET China Bacterial Resistance Surveillance Network (www.chinets.com), KP ranks as the second most common pathogen among clinical isolates, accounting for 14.22% of cases. Notably, carbapenem resistance rates have exceeded 20%. Key resistance mechanisms identified include ESBLs, carbapenemases such as KPC, and metallo-β-lactamases, including the NDM.¹⁹ HvKP-induced community-acquired meningitis with septic shock is associated with a high hospitalization rate, with a 28-day mortality.²⁰ In this case, intrathecal amikacin and dexamethasone were administered based on the results from the susceptibility test. Intrathecal administration of amikacin enables direct attainment of therapeutic concentrations in the CSF, thereby enhancing antimicrobial efficacy.²¹ Additionally, findings from meta-analyses indicate that intrathecal dexamethasone exhibits significant efficacy in reducing capillary permeability, inflammation, cerebral edema, and intracranial pressure, while enhancing antibiotic activity.²²

The patient in this case presented with an acute-onset, a history of diabetes mellitus, and disseminated invasive infection. The disease progressed rapidly, resulting in impaired consciousness and respiratory failure. Based on clinical manifestations and genomic sequencing, the diagnosis was confirmed to be HvKP invasive syndrome complicated by severe intracranial infection. Due to the high viscosity of the CSF, preventing drainage through conventional methods, an integrated approach involving CSF exchange and intrathecal injections with amikacin and dexamethasone was used to treat the patient. This approach was therapeutically efficacious, resulting in improved clinical outcomes and subsequent discharge of the patient in stable condition.

Conclusion

Efficacious treatment of HvKP-related intracranial infections necessitates early recognition, potent antibiotic therapy with high tissue penetration ability, and quick CSF drainage. In this case, CSF exchange, combined with intrathecal injection with amikacin and dexamethasone, significantly improved clinical outcomes. This case represents the first reported application of this integrated regimen for HvKP meningitis, highlighting its significant therapeutic potential for broader clinical utility. However, this case provides an example but does not establish a generalizable standard of care, and that further studies or reports are needed to validate safety and outcomes.

Abbreviations

KP, Klebsiella pneumoniae; cKP, classical KP; HvKP, Hypervirulent KP; IDSA, Infectious Diseases Society of America; CNS, central nervous system; WBC, white blood cell; CRP, C-reactive protein; PCT, Procalcitonin; ICU, intensive care unit; CSF, cerebrospinal fluid; GCS, glasgow coma scale; BALF, bronchoalveolar lavage fluid; WGS, whole-genome sequencing; MLST, multilocus sequence typing; ESBL, extended-spectrum β-lactamase.

Data Sharing Statement

Data on the case clinical information, informed consent form, and images are available for review from the corresponding author upon request.

Ethical Approval

The publication of de-identified case details was expressly authorized under the original study approval by theAffiliated Lu’an Hospital of Anhui Medical University Institutional Review Board (Approval No. 2025LLKS-KY-042).

Consent for Publication

Written informed consent was obtained from patient and her families for the publication of case details and images. The complete signed consent form is archived at the Institutional Review Board (IRB) of Affiliated Lu’an Hospital of Anhui Medical University under approval number (Approval No. 2025LLKS-KY-042).

Acknowledgments

The authors thank the patient’s family for their consent to participatein this study as well as the medical, nursing, radiologist, and laboratory staff who were involved in the patient’s care.

Funding

The authors declare that financial support was received for the research in publication of this article. This research is supported by the Lu’an City Science and Technology Bureau Research Project (No.2024lakj013).

Disclosure

The authors report no conflicts of interest in this work.

References

1. Murray CJL, Ikuta KS, Sharara F, et al. Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis. Lancet. 2022;399(10325):629–655. doi:10.1016/s0140-6736(21)02724-0

2. Bengoechea JA, Sa Pessoa J. Klebsiella pneumoniaeinfection biology: living to counteract host defences. FEMS Microbiol Rev. 2018;43(2):123–144. doi:10.1093/femsre/fuy043

3. Zhu J, Wang T, Chen L, Du H. Virulence factors in hypervirulent Klebsiella pneumoniae. Front Microbiol. 2021;12. doi:10.3389/fmicb.2021.642484

4. Hallmaier-Wacker LK, Andrews A, Nsonwu O, et al. Incidence and aetiology of infant gram-negative bacteraemia and meningitis: systematic review and meta-analysis. Arch Dischildhood. 2022;107(11):988–994. doi:10.1136/archdischild-2022-324047

5. Tunkel AR, Hasbun R, Bhimraj A, et al. 2017 infectious diseases Society of America’s Clinical Practice guidelines for healthcare-associated ventriculitis and meningitis*. Clinl Infect Dis. 2017;64(6):e34–e65. doi:10.1093/cid/ciw861

6. Namikawa H, Oinuma KI, Yamada K, Kaneko Y, Kakeya H, Shuto T. Predictors of hypervirulent Klebsiella pneumoniae infections: a systematic review and meta-analysis. J Hosp Infect. 2023;134:153–160. doi:10.1016/j.jhin.2023.02.005

7. Chen H-Q, Mo Z-H, Wei W-X. Case report: trauma-induced Klebsiella pneumoniae invasive syndrome presenting with liver abscess, lung abscess, endophthalmitis, and purulent meningitis. Front Med. 2025;11. doi:10.3389/fmed.2024.1513831

8. Li L, Yuan Z, Chen D, Xie X, Zhang B. Clinical and microbiological characteristics of invasive and hypervirulent Klebsiella pneumoniae infections in a teaching hospital in China. Infect Drug Resist. 2020;Volume 13:4395–4403. doi:10.2147/idr.S282982

9. Dong N, Yang X, Chan EW-C, Zhang R, Chen S. Klebsiella species: taxonomy, hypervirulence and multidrug resistance. eBioMedicine. 2022;79. doi:10.1016/j.ebiom.2022.103998

10. Wyres KL, Lam MMC, Holt KE. Population genomics of Klebsiella pneumoniae. Nat Rev Microbiol. 2020;18(6):344–359. doi:10.1038/s41579-019-0315-1

11. Fang CT, Lai SY, Yi WC, Hsueh PR, Liu KL, Chang SC. Klebsiella pneumoniae genotype K1: an emerging pathogen that causes septic ocular or central nervous system complications from pyogenic liver abscess. Clinl Infect Dis. 2007;45(3):284–293. doi:10.1086/519262

12. Yang X, Wang Y, Zhao S, et al. Clinical characteristics and prognosis of Klebsiella pneumoniae meningitis in adults. Heliyon. 2024;10(7). doi:10.1016/j.heliyon.2024.e28010

13. Sun R, Zhang H, Xu Y, Zhu H, Yu X, Xu J. Klebsiella pneumoniae-related invasive liver abscess syndrome complicated by purulent meningitis: a review of the literature and description of three cases. BMC Infect Dis. 2021;21(1). doi:10.1186/s12879-020-05702-3

14. Siu LK, Yeh K-M, Lin J-C, Fung C-P, Chang F-Y. Klebsiella pneumoniae liver abscess: a new invasive syndrome. Lancet Infect Dis. 2012;12(11):881–887. doi:10.1016/s1473-3099(12)70205-0

15. Committe ADAPP. 16. Diabetes care in the hospital: standards of medical care in diabetes—2022. Diabetes Care. 2022;45(Supplement_1):S244–S253. doi:10.2337/dc22-S016

16. Zerem E, Hadzic A. Sonographically guided percutaneous catheter drainage versus needle aspiration in the management of pyogenic liver abscess. Am J Roentgenol. 2007;189(3):W138–W142. doi:10.2214/ajr.07.2173

17. Russo TA, Marr CM. Hypervirulent Klebsiella pneumoniae. Clin Microbiol Rev. 2019;32(3). doi:10.1128/cmr.00001-19

18. Fang CT. Klebsiella pneumoniae meningitis: timing of antimicrobial therapy and prognosis. Qjm. 2000;93(1):45–53. doi:10.1093/qjmed/93.1.45

19. Han X, Yao J, He J, et al. Clinical and laboratory insights into the threat of hypervirulent Klebsiella pneumoniae. Int J Antimicrob Agents. 2024;64(3):107275. doi:10.1016/j.ijantimicag.2024.107275

20. Jung J, Park K-H, Park SY, et al. Comparison of the clinical characteristics and outcomes of Klebsiella pneumoniae and Streptococcus pneumoniae meningitis. Diagn Microbiol Infect Dis. 2015;82(1):87–91. doi:10.1016/j.diagmicrobio.2015.02.006

21. Jones RN, Sader HS, Beach ML. Contemporary in vitro spectrum of activity summary for antimicrobial agents tested against 18 569 strains non-fermentative gram-negative bacilli isolated in the SENTRY antimicrobial surveillance program (1997–2001). Int J Antimicrob Agents. 2003;22(6):551–556. doi:10.1016/s0924-8579(03)00245-0

22. Gao Y, Su J, Ma Y, et al. Efficacy and safety of intrathecal dexamethasone combined with isoniazid in the treatment of tuberculous meningitis: a meta-analysis. BMC Neurol. 2024;24(1). doi:10.1186/s12883-024-03701-4

Published in the journal Brain Communications the study by academics from the University of Bath and the University of Bristol, reports that Fastball EEG, a three-minute passive test that records electrical activity in the brain while participants view a stream of images, can reliably identify memory problems in people with Mild Cognitive Impairment (MCI) — a condition that can lead to Alzheimer’s. This follows the group’s previous study in 2021 that demonstrated Fastball was sensitive to memory impairment in Alzheimer’s disease.

Crucially, the research team has demonstrated for the first time that the test can be administered in people’s homes, outside of a clinical environment. Researchers say this opens the door to wider screening and monitoring using accessible, low-cost technology.

With the development of the breakthrough Alzheimer’s drugs, donanemab and lecanemab, an early diagnosis is more important than ever before. The drugs are clinically proven to be the most effective in the early stages of Alzheimer’s. Despite this, in England, it is estimated that as many as 1 in 3 people do not currently have a dementia diagnosis, delaying treatments, support and research opportunities to tackle the condition.

The study was led by Dr George Stothart, a cognitive neuroscientist in the Department of Psychology at the University of Bath. He said:

“We’re missing the first 10 to 20 years of Alzheimer’s with current diagnostic tools. Fastball offers a way to change that — detecting memory decline far earlier and more objectively, using a quick and passive test.”

How the test works

Fastball is a passive EEG test that monitors the brain’s automatic responses to images — without requiring participants to follow instructions or recall information. This makes it more objective and accessible than traditional memory tests.

Key findings:

• Detected early memory issues in people with MCI likely to develop Alzheimer’s.
• Delivered reliable results in real-world home settings.
• Showed reduced memory responses even in patients who later progressed to dementia.

Researchers say Fastball could be scaled for use in GP surgeries, memory clinics, or at home — helping deliver earlier, more accurate diagnoses.

Dr Stothart added: “There’s an urgent need for accurate, practical tools to diagnose Alzheimer’s at scale. Fastball is cheap, portable, and works in real-world settings.”

The study was funded by the Academy of Medical Sciences and supported by dementia research charity BRACE.

Chris Wiliams, CEO of BRACE Dementia Research, said: “Fastball is an incredible tool that could offer anyone who, for whatever reason, cannot access a dementia diagnosis in a clinical setting.

BRACE has been supporting the development of Fastball for several years, and we are excited to see what Dr Stothart’s team will achieve over the next few years with ongoing support from the charity.”

What is perimenopause?

Perimenopause is defined as the transitional phase that can last anywhere from 8 to 10 years before menopause, which is marked by 12 consecutive months without a menstrual period. During this time, fluctuations in estrogen and progesterone levels create hormonal chaos that triggers various symptoms. Unfortunately, many women misattribute these symptoms to stress, overwork, or mental health issues, as per the National Institute of Mental Health.

How do you know if it is PMS or perimenopause?

The key difference between PMS and PMM lies in duration and unpredictability. PMS usually arises predictably, following ovulation and is alleviated by menstruation. PMM, however, often feels like an ongoing battle with no apparent cause or solution, radically altering women’s lives, as per Harvard Health.

How does mood change during perimenopause?

The hormonal shifts of perimenopause impact neurotransmitters like serotonin and dopamine, which influence mood, focus, and motivation, as per the Journal of Midlife Health. As a result, many women experience heightened emotions such as irritability, anxiety, and sadness.

These emotional fluctuations can be invisible to others, leading women to feel misunderstood and unappreciated. They may be dismissed as “overreacting” or “too sensitive.” “The impact on relationships and work productivity can be profound, while medical professionals sometimes fail to connect the symptoms to hormonal changes, prescribing antidepressants or sleep aids instead. This dismissive attitude can foster feelings of shame, frustration, and isolation,” menopause coach Tammana Singh tells Health Shots.

What are the symptoms of hormonal changes in women?

Recognising the signs of perimenopause can help you take control of your health and overall well-being. Menopause coach Tammana Singh shares seven key indicators:

1. Heightened anxiety or depressive spells: Unexplained emotional lows and anxiety attacks may become more frequent.
2. New or worsening PMS symptoms: If your PMS seems to be intensifying or changing, it might be a sign of perimenopause.
3. Night sweats and insomnia: Experiencing sudden sweating during the night or difficulty sleeping can significantly disrupt rest.
4. Brain fog or forgetfulness: Mental clarity may decrease, resulting in forgetfulness or difficulty concentrating.
5. Sudden weight gain: Weight gain, particularly around the abdomen, can signal hormonal changes.
6. Migraines or joint pain: Increased headaches or joint discomfort may indicate shifts in hormone levels.
7. Irregular or heavier periods: Changes in menstrual cycle regularity or flow can be a telling sign.

How to manage hormonal changes during perimenopause?

Awareness is crucial when navigating this transitional phase. Understanding that hormonal changes drive these symptoms allows women to seek appropriate help rather than blaming themselves.

Here are some methods to consider:

1. Track your hormonal patterns: Using apps, journals, or simple calendar notes can help you connect mood changes with variations in your menstrual cycle, as per the Journal of Medical Internet Research. Look for patterns that emerge over time.
2. Rethink self-care: The approach to self-care during this phase requires more than just surface-level solutions, as per the American Psychological Association. Focus on restorative practices such as:

• Deep breathing exercises
• Journaling
• Professional therapy
• Gentle movements like yoga or tai chi can help regulate cortisol and estrogen levels.

3. Build a menopause-ready lifestyle: Healthy lifestyle choices can alleviate some perimenopausal symptoms. Consider:

• Introducing foods rich in phytoestrogens (flaxseeds, sesame seeds, tofu).
• Maintaining good sleep hygiene—consistent sleep schedules, a comfortable sleep environment, and practices that promote relaxation.
• Starting a strength-training regimen to support muscle and bone health.

4. Get informed support: Seek out professionals well-versed in hormonal health, such as:

• Functional medicine practitioners
• Integrative gynaecologists
• Specialists knowledgeable about Ayurveda
• Therapists who can guide you through lifestyle shifts based on current research

Hormonal changes may challenge us, but they also open the door to deeper body awareness and self-acceptance.

Specialty

Please chooseI’m not a medical professional.Allergy and ImmunologyAnatomyAnesthesiologyBiostatisticsCardiac/Thoracic/Vascular SurgeryCardiologyCritical CareDentistryDermatologyDiabetes and EndocrinologyEmergency MedicineEpidemiology and Public HealthFamily MedicineForensic MedicineGastroenterologyGeneral PracticeGeneticsGeriatricsHealth PolicyHematologyHIV/AIDSHospital-based MedicineI’m not a medical professional.Infectious DiseaseIntegrative/Complementary MedicineInternal MedicineInternal Medicine-PediatricsMedical Education and SimulationMedical PhysicsMedical StudentNephrologyNeurological SurgeryNeurologyNuclear MedicineNutritionObstetrics and GynecologyOccupational HealthOncologyOphthalmologyOptometryOral MedicineOrthopaedicsOsteopathic MedicineOtolaryngologyPain ManagementPalliative CarePathologyPediatricsPediatric SurgeryPharmacologyPhysical Medicine and RehabilitationPlastic SurgeryPodiatryPreventive MedicinePsychiatryPsychologyPulmonologyRadiation OncologyRadiologyRheumatologySubstance Use and AddictionSurgeryTherapeuticsTraumaUrologyMiscellaneous

Introduction

Chronic obstructive pulmonary disease (COPD) is a debilitating condition that is characterized by poorly reversible airflow limitation, difficulty breathing during physical activities^1–4 decreased exercise capacity,⁵ and limitations in daily activities.^6–9 According to the Italian National Statistics Institute (ISTAT) and the Global Burden of Diseases initiative,^10–12 in Italy, approximately 3.5 million adults are affected by COPD and 2.5% of all Disease Adjusted Life Years lost were attributable to COPD in 2021.¹³ However, these figures may underestimate the actual prevalence of COPD because the disease is often diagnosed only in its advanced stages.^11,14 According to the Medicines Utilization Monitoring Center report recently published by the Italian Medicines Agency, some patients discontinue treatment early after initiating maintenance therapy,¹¹ emphasizing the need for improved COPD management in terms of appropriate diagnosis, pharmacological treatment, and treatment adherence.¹⁵ The management of COPD presents several challenges, including misdiagnosis, delayed diagnosis, failure to implement fundamental measures to slow disease progression (eg, tobacco cessation, vaccinations, and lifestyle changes), uncertainty in selecting the most appropriate drug for treatment, and poor adherence to therapy.^16,17 The Global Initiative for Chronic Obstructive Lung Disease (GOLD 2023–2025) recommend a comprehensive approach to COPD management, including accurate diagnosis and severity assessment, smoking cessation, and individualized pharmacological and non-pharmacological interventions, with a focus on managing exacerbations.^15,18 An e-Delphi study of 600 general practitioners (GPs) in Italy reported that although most GPs were familiar with the GOLD 2023 report and COPD reimbursement requirements, only 34% had access to spirometry. There was no consensus on the initial treatment options, and re-evaluation of triple therapy necessitated a specialist referral.¹⁹

Effective COPD management cannot be limited to expert care alone, especially when prevention and long-term monitoring are essential for optimal outcomes. To address the challenges in COPD management, the Italian Medicines Agency (AIFA) introduced Nota 99, which conforms to the GOLD report 2022 and confers GPs the responsibility of diagnosing and prescribing appropriate medication for mild to moderate COPD. Given the considerable prevalence of COPD, this act recognizes the critical role of GPs in managing COPD. Nota 99 allows GPs to prescribe any inhaled therapy, except for the single-device inhaler triple therapies, while maintaining specialist care for individuals with severe pulmonary obstruction or recurrent exacerbations.¹¹

Given this new scenario, ASTER, an Italian observational prospective multicenter trial, was designed to provide the first meaningful insights into COPD management by GPs following the Nota 99, describing the characteristics of patients, treatment patterns (primary outcome), and clinical outcomes (secondary outcome) over a 6-month observation period.

Materials and Methods

Trial Design and Oversight

ASTER was an observational, multicenter, prospective cohort study conducted in Italy that focused on patients with COPD who were managed by GPs following standard protocols of clinical practice. Consecutive patients at each participation center who provided the written informed consent and privacy form and met the eligibility criteria were enrolled in the study. The study was conducted in 30 centres distributed throughout Italy in order to obtain results reasonably albeit not formally representative of the management of COPD in general medicine in Italy according to the Nota 99. This study was conducted in compliance with the Guidelines for Good Pharmacoepidemiology Practice (GPP)²⁰ and the regulatory elements of observational research in Italy.²¹

Eligible patients were aged 40–80 years and had spirometry-confirmed COPD (post-bronchodilator Forced Expiratory Volume in one second (FEV₁) to Forced Vital Capacity (FVC) ratio <0.70) with an FEV₁ of ≥50% of the predicted value. Patients were enrolled if they had ≤1 exacerbation requiring antibiotics and/or oral corticosteroids; had no emergency room (ER) visits or hospitalizations for COPD in the past year; and, according to the prescription limits for GPs before Nota 99, they could have been treated in the last 3 months before enrollment exclusively with a short or long-acting bronchodilator or an ICS/LABA; and had a COPD Assessment Test (CAT) score ≥10 at the enrollment appointment. Patients were excluded if they were unable to undergo spirometry according to Nota 99, had received LABA/LAMA combinations within the previous 3 months, had low treatment adherence as judged by the clinician, inability to properly use an inhaler, were pregnant or breastfeeding, had a current asthma diagnosis, could not read or write in Italian, or were already enrolled in another clinical trial.

Each patient was assessed during the enrollment visit, which coincided with the reconfirmation of diagnosis and therapy prescription. Patients were then followed up with specific visits at 3 and 6 months, as outlined by standard clinical practice. During the enrollment visit, the GP collected the patient’s history of respiratory disease and symptoms including those within the previous year, occupational and tobacco smoke exposure, COPD anamnesis, and previously prescribed COPD therapies as well as comorbidities and related therapies. The GPs provided the COPD Assessment Test (CAT)²² to the patients and completed the modified Medical Research Council Dyspnea Scale (mMRC)²³ questionnaires. At the 3- and 6-month follow-up visits, the GP collected data on the incidence, severity, and treatment of exacerbations and adjusted the treatment as needed. Additionally, at the 6-month visit, the GP collected information on functional parameters if spirometry was performed according to clinical practice, provided the CAT questionnaire to the patient, and completed the mMRC questionnaire.

Primary and Secondary Effectiveness Analyses

The primary endpoint of the study was to describe treatment patterns during the 6-month observation period, including the proportion of patients taking different COPD medications and any changes in treatment patterns. The secondary endpoints were demographic and clinical features, FEV₁ at enrollment and after 6 months, patient-reported outcomes (CAT and mMRC scores) at enrollment and after 6 months, and the number of COPD exacerbations and exacerbations per patient during the observation period.

Statistical Consideration

The sample size was determined based on feasibility considerations, including the duration of the enrollment period and the number of participating centers. It was estimated that approximately 400 patients can be enrolled over an 8-month period from 40 Italian study centers. Given an expected drop-out rate of approximately 20% over the 6-month observation period, 320 patients were expected to be available for the primary analysis; accordingly, simulations were performed to estimate the achievable precision of the 95% confidence interval (95% CI) of the expected proportions for 320 evaluable patients. This descriptive study had no defined formal hypotheses and no statistical significance testing was performed; data was analyzed using epidemiological methods. Descriptive statistics were provided for all variables and endpoints. All analyses were performed using the SAS software (SAS Institute, Cary, North Carolina, USA).

Results

Participant Disposition and Characteristics

Initially, 385 patients were enrolled in the ASTER study, and 41 of these who did not meet the eligibility criteria were excluded (Figure 1), resulting in 344 (89.4%) eligible patients. Of these eligible patients, 332 (96.5%) completed the study, whereas 12 (3.5%) were lost to follow-up (n = 10) or excluded due to consent withdrawal (n = 2).

Figure 1 Study flowchart. Note: N, total number of patients.

The majority of the eligible patients were men (61.9%) and predominantly Caucasian (98.8%) (Table 1). Most patients had either primary (18.9%) or secondary education (71.7%) and were unemployed or retired (73.6%). At enrollment, 49.3% of the patients were active smokers, 41.7% had previously smoked, and 9.0% had never smoked. The majority of patients (83.7%) had comorbidities at enrollment, with arterial hypertension (58.3%), diabetes (24.0%), and cardiac ischemic disease (16.7%) being the most common (Table 1). Moreover, 50% of patients were regularly treated with ≥3 medications for concomitant diseases. The most prevalent COPD symptoms were cough (82.6%), shortness of breath (66.3%), and phlegm (48.0%). More than half of the patients (54.1%) had mild to moderate dyspnea (mMRC grade ≤2) at enrollment (Table 2). Further, 77.6% of the patients reported experiencing the same COPD symptoms in the year before enrollment as they did at the time of diagnosis.

Table 1 Characteristics of the Patients at Enrollment

Table 2 Disease Characteristics at Enrollment (Eligible Patients)

Of the eligible patients, 196 (57%) were classified as incident patients—symptomatic individuals not previously diagnosed with COPD by spirometry but likely prescribed treatments such as LAMA, LABA, or ICS/LABA by their GP without a confirmed diagnosis—while 148 (43%) were classified as prevalent patients with a prior COPD diagnosis (Table S1). Incident patients had a higher FEV₁ (mean, 2.0 vs 1.7), were slightly younger (mean age, 67.2 vs 69.2 years), were more likely to be employed (25.4% vs 17.4%) and had fewer comorbidities (80.6% vs 87.8%) than prevalent patients. In addition, incident patients experienced severe dyspnea less frequently (mMRC grade ≥2: 40.3% vs 53.4%) and had a lower incidence of poor quality of life (CAT score of 21–30: 14.3% vs.19.6%) than prevalent patients.

Primary Endpoint results

At enrollment, 20.9% of patients were treated with LAMA, 13.7% with an ICS/LABA combination, 2.9% with LABA, and 62.5% (30 prevalent and 185 incident patients) were not receiving any treatment (Figure 2). At the 3-month follow-up, 56.7% of patients were being treated with LABA/LAMA, 21.2% with LAMA, and 12.2% with ICS/LABA (Table S2). At the 6-month follow-up, 53.5% of the patients were being treated with a LABA/LAMA combination, 19.2% with LAMA, and 11.3% with an ICS/LABA combination. Current therapy at 6 months was not notably different between prevalent and incident patients, with the only exception of the ICS/LABA combination was being used more frequently in prevalent patients than in incident patients (16.2% vs 7.7%) (Table S3).

Figure 2 Treatment pattern of COPD medications for eligible patients at enrollment (baseline) and at the 6-month follow-up. Abbreviations: ICS, inhaled corticosteroid; LAMA, long-acting muscarinic antagonist; LABA, long-acting beta-agonist; N, total number of patients at each visit; n = number of patients in each category.

Secondary Endpoint results

Overall, lung function improved over the 6-month observational period, as evidenced by the increase in pre-bronchodilator FEV₁ (Table 3). When the pre-bronchodilator FEV₁ at 6 months was compared with that at enrollment in 206 patients, a mean increase of 140 mL was observed (Table 3), and one-quarter of the patients exhibited an increase of at least 300 mL.

Table 3 Summary of Secondary Endpoint Results for Eligible Patients at Enrollment and at the 6-month Follow-up

At enrollment, 45.9% of patients with COPD reported a significant level of dyspnea, with an mMRC score ≥2. At the 6-month follow-up, this value was reduced to 23.5% (Table 3). The mMRC scores at enrollment and at the 6-month follow-up are summarized in Table S4. Overall, the mMRC score decreased by at least one point in 40% of the patients and remained unchanged in 53.9%.

In terms of the impact of COPD on patients’ lives, the patients’ health status and quality of life improved noticeably over the 6-month study period, as evidenced by a mean decrease of 3.6 points in the CAT score (Table 3). Notably, the CAT score decreased by at least 6 points in one-quarter of the patients.

During the observation period, 3.9% (n = 13/332) of the patients experienced 14 exacerbations (10 mild and 4 moderate), resulting in an approximate annualized exacerbation rate of 7.8%. This represents a meaningful drop from the 23.2% incidence rate in the year before recruitment, indicating an absolute reduction of 15.4% and a 34% reduction in the annualized relative risk over the 6-month period (Table 3). Notably, none of these reported exacerbations required admission to the ER or hospitalization.

Discussion

To the best of our knowledge, the ASTER study was the first COPD study conducted in a GP setting in Italy, providing real-world evidence of clinical practice for patients with COPD managed according to Nota 99, which confers GP with a critical responsibility in the COPD management. The study findings highlight the importance of treatment pathways, and the public health implications of appropriate COPD management.

The findings of the ASTER study provide a detailed overview of the evolving treatment patterns for patients with COPD. Over the course of the study, there was a noticeable shift towards combination therapy, with a substantial number of patients switching from monotherapy with LABA or LAMA to LABA/LAMA combination therapy. Similarly, the majority of patients who were initially treated with ICS/LABA combination therapy, switched to LABA/LAMA therapy. This shift towards LABA/LAMA therapy as well as the observed improvements in the CAT and mMRC scores suggests the effectiveness of these treatments in managing symptoms and improving the quality of life of patients with COPD. These real-world results are consistent with prior randomized controlled studies that demonstrated the effectiveness of LAMA/LABA therapy for patients with COPD.^24,25 Overall, the results of the ASTER study suggest that the implementation of Nota 99 may positively influence clinical practices on COPD treatment. The absence of severe exacerbations requiring hospitalization suggests that enhanced patient management and treatment regimens are effective in preventing severe episodes. This is also consistent with previous research indicating that treatment with LABA/LAMA therapy is more effective than monotherapy in preventing all COPD exacerbations.²⁶ Although no formal hypothesis was established, our findings indicate that intervention according to Nota 99, as implemented in the ASTER study, has the potential to avoid an exacerbation episode for every six patients correctly diagnosed and treated over a year.

The ASTER study emphasizes the pivotal role played by Italian GPs in COPD management. With resources and clear guidelines, GPs can effectively diagnose, treat, and monitor patients with COPD, reducing the disease’s impact and improving long-term outcomes. Continuous training and resources are essential for GPs to provide optimal care. Comparative analyses with practices in other countries^27–29 reveal that Nota 99 promotes structured COPD management, allowing for a proactive rather than reactive strategy by providing clear guidance on the correct diagnostic process, prevention, and management of COPD. According to the ASTER study, 94.4% of newly diagnosed patients with COPD were untreated at the time of enrollment, highlighting that COPD is often overlooked. Improved diagnostic procedures in primary care are essential. Active research and surveillance by GPs can help develop precise diagnostic tools and protocols, ensuring accurate and prompt treatment. Routine case findings and early detection strategies are critical to improve COPD management outcomes.

Although the ASTER study provides valuable insights, it has the following limitations. As a real-life, non-interventional study with prospective data collection, there are inherent biases to consider. Information and selection biases may have influenced the outcome as respondents may have been influenced by GPs or their own beliefs about meeting GP expectations. Additionally, the inclusion criteria required patients to be able to read and write in Italian and fill out questionnaires on their own, which may have disqualified some patients and reduced the generalizability of the findings. Furthermore, GPs’ participation in the trial may have encouraged them to adhere more rigorously to treatment recommendations, potentially diverging from “real-world” treatment practices (known as the Hawthorne effect). However, efforts were made to mitigate these biases, including consecutive patient enrollment and regional diversity in site selection.

The study’s findings may have limited applicability to the broader Italian patient population with COPD because of the study’s recruitment strategies and specific eligibility criteria. Despite the efforts taken to choose locations from various geographic regions and ensure representative sampling, the enrolled patients may not fully represent Italy’s COPD patient community. As a result, the findings should be interpreted with caution, taking into account potential selection bias.

Conclusion

The proactive identification of patients with COPD in a general practice setting may allow for early detection, effective treatment, and better clinical outcomes. In ASTER study, the application of AIFA’s Nota 99, which empowers GPs to initiate the most effective therapy when needed, was associated with meaningful improvements in patient outcomes in this study. This suggests that GPs in Italy should actively identify patients with COPD, especially those who may not pay attention to their symptoms because of lack of awareness. Such a proactive approach could result in earlier interventions, more effective disease management, and, eventually, improved patient outcomes. However, future studies using public health system administrative registries or large clinical databases could confirm the ASTER results, accurately define their dimensions, and reduce potential biases, verifying if the promising outcomes are consistent in general medical practice in Italy.

Abbreviations

AIFA, Italian Medicines Agency; ASTER, Italian observational prospective multicenter study; CAT, COPD Assessment Test; CI, Confidence Interval; COPD, Chronic obstructive pulmonary disease; GPP, Good Pharmacoepidemiology Practice; ER, Emergency room; FEV₁, Forced expiratory volume in 1 second; FVC, Forced vital capacity; GOLD, Global Initiative for Chronic Obstructive Lung Disease; GP, General practitioner; ICS, Inhaled corticosteroids; ISTAT, Italian Institute of Statistics; LABA, Long-acting beta-agonists; LAMA, Long-acting muscarinic antagonists; mMRC, modified Medical Research Council; SABA, Short-acting beta-agonists; SAMA, Short-acting muscarinic antagonists; Nota 99, Italian Medicine Agency’s guideline for managing mild-to-moderate COPD by GPs.

Data Sharing Statement

Anonymized individual participant data and study documents can be requested for further research from https://www.gsk-studyregister.com/en/.

Ethics Approval and Informed Consent

This study complies with the Declaration of Helsinki. Informed consent was obtained before initiating this study. The ethics committee of each participating study center has received approval through the Coordinator Research Ethics Committee (Comitato Etico Lazio 1, Rome, Italy), and the individual study centers have received approval from the following ethical committees: Comitato Etico Interaziendale – ASL Alessandria; Comitato Etico Area Vasta Centro – USL Toscana Centro; Comitato Etico Area Vasta Sud Est – USL Toscana Sud Est; Comitato Etico Interprovinciale Area 1 ASL BT; CESC delle Province di Verona e Rovigo; Comitato Etico di Brescia; CET Regione Abruzzo; Comitato Etico – ARES Sardegna; CET Regionale dell’Umbria; Comitato Etico Regione Marche; Comitato Etico Lazio 1; Comitato Indipendente di Etica Medica – ASL Brindisi; Comitato Etico Regione Calabria Area Centro; Comitato Etico Campania Centro; Comitato Etico di Messina; Comitato Etico Indipendente – ASL Bari; CET Marche – AOU delle Marche.

Acknowledgments

The authors gratefully acknowledge the contributions of all the 30 Italian general practitioners (GPs) who participated as principal investigators and sub-investigators in this study. The authors also extend their sincere thanks to Alessandra Dal Collo for support in administrative matters. The authors would like to express their gratitude to the General Medicines Medical Science Liaisons (MSLs) team for their scientific support provided to the GPs. In addition, the authors thank IQVIA Solutions Italy SRL for their contributions to the conduct of clinical operations, data management, and statistical analysis. The authors also thank Dr. Rakesh Ojha, PhD, a medical writer and an employee of GSK, India, for his manuscript writing and project management support.

Author Contributions

All authors contributed to the study conception or design and/or data analysis and interpretation. All authors were involved in the writing, reviewing, and final approval of the manuscript and agreed to be accountable for all aspects of the work.

Funding

This analysis was funded by GSK (study number 217466). GSK also funded all expenses related to the development and publication of this manuscript.

Disclosure

M.V., C.S., D.C., and B.G. are employees of GSK and hold stock options. G.G. and U.A. have no conflicts of interest to declare. R.P. has received consulting fees from GSK Italy and holds stock options from GSK SpA. The authors report no other conflicts of interest in this work.

References

1. Meek PM. Dyspnea. mechanisms, assessment, and management: a consensus statement. Am J Respir Crit Care Med. 1999;159(1):321–340.

2. Chronic obstructive pulmonary disease (COPD). WHO.2024. Available from: https://www.who.int/news-room/fact-sheets/detail/chronic-obstructive-pulmonary-disease-(copd). Accessed on 25, November 2024.

3. Devine JF. Chronic obstructive pulmonary disease: an overview. Ame Health Drug Benefits. 2008;1(7):34–42.

4. Cushen B, Morgan R, Summer R. Chronic obstructive pulmonary disease. In: Reference Module in Biomedical Sciences. International Encyclopedia of Public Health. 2nd; 2017:28–35. Available from: https://www.sciencedirect.com/science/article/abs/pii/B9780128036785000734?via%3Dihub

5. Broxterman RM, Hoff J, Wagner PD, Richardson RS. Determinants of the diminished exercise capacity in patients with chronic obstructive pulmonary disease: looking beyond the lungs. J Physiol. 2020;598(3):599–610. doi:10.1113/JP279135

6. Lahaije AJ, van Helvoort HA, Dekhuijzen PN, Heijdra YF. Physiologic limitations during daily life activities in COPD patients. Respir Med. 2010;104(8):1152–1159. doi:10.1016/j.rmed.2010.02.011

7. Roche N. Activity limitation: a major consequence of dyspnoea in COPD. Eur Respir Rev. 2009;18(112):54–57. doi:10.1183/09059180.00001309

8. Eisner MD, Blanc PD, Yelin EH, et al. COPD as a systemic disease: impact on physical functional limitations. Am J Med. 2008;121(9):789–796. doi:10.1016/j.amjmed.2008.04.030

9. Kapella MC, Larson JL, Covey MK, Alex CG. Functional performance in chronic obstructive pulmonary disease declines with time. Med Sci Sports Exerc. 2011;43(2):218–224. doi:10.1249/MSS.0b013e3181eb6024

10. COPD. A disease still underestimated by Europeans: absence of perceived risk, according to Eurisko survey. Available from: https://www.chiesi.com/en/copd-a-disease-still-underestimated-by-europeans-absence-of-perceived-risk-according-to-eurisko-survey/. Accessed on 25, November 2024.

11. AIFA publishes nota 99 for the prescription of medicines against COPD. Available from: https://www.aifa.gov.it/en/-/aifa-pubblica-la-nuova-nota-99-per-la-prescrizione-dei-farmaci-per-la-bpco. Accessed on 25, November 2024.

12. Italian Institute of Statistics (ISTAT). Annual report 2023. Available from: https://www.istat.it/wp-content/uploads/2023/11/Annual-Report-2023-Summary.pdf. Accessed on 25, November 2024.

13. Global Burden of Disease Collaborative Network. Global burden of disease study 2021 (GBD 2021) results. Seattle, United States: Institute for Health Metrics and Evaluation (IHME), 2021. Available from: https://vizhub.healthdata.org/gbd-compare/. Accessed April 2025.

14. Celli BR, MacNee W, Agusti A. ATS/ERS task force. Standards for the diagnosis and treatment of patients with COPD: a summary of the ATS/ERS position paper. Eur Respir J. 2004;23(6):932–946. doi:10.1183/09031936.04.00014304

15. Global Initiatives for Chronic Obstructive Lung Disease. Pocket guide to COPD diagnosis, management, and prevention: a guide for health care professionals; 2023. Available from: https://goldcopd.org/wp-content/uploads/2023/03/POCKET-GUIDE-GOLD-2023-ver-1.2-17Feb2023_WMV.pdf. Accessed on 25, November 2024.

16. Martinez FJ, O’Connor GT. Screening, case-finding, and outcomes for adults with unrecognized COPD. JAMA. 2016;315(13):1343–1344. doi:10.1001/jama.2016.3274

17. Khan KS, Jawaid S, Memon UA, et al. Management of chronic obstructive pulmonary disease (COPD) exacerbations in hospitalized patients from admission to discharge: a comprehensive review of therapeutic interventions. Cureus. 2023;15(8):e43694. doi:10.7759/cureus.43694

18. Global Initiative for Chronic Obstructive Lung Disease. Global strategy for prevention, diagnosis, and management of COPD: 2024 report. Available from: https://goldcopd.org/2024-gold-report/. Accessed 16 December 2024.

19. Marconi E, Lombardo FP, Micheletto C, et al. Perception and knowledge of general practitioners on COPD management according to the GOLD23 document and reimbursement criteria for drugs prescription: an e-Delphi study. Curr Med Res Opin. 2024;40(10):1821–1826. doi:10.1080/03007995.2024.2399279

20. Public Policy Committee, International Society of Pharmacoepidemiology. International society of pharmacoepidemiology. guidelines for good pharmacoepidemiology practice (GPP). Pharmacoepidemiol Drug Saf. 2016;25(1):2–10. Available from: Guidelines for good pharmacoepidemiology practice (GPP) – – 2016 – Pharmacoepidemiology and Drug Safety Wiley Online Library. Accessed on 25 Nov 2024]. doi:10.1002/pds.3891

21. Guidelines for the classification and conduct of observational studies on medicines. Available from: https://www.aifa.gov.it/en/-/linea-guida-per-la-classificazione-e-conduzione-degli-studi-osservazionali-sui-farmaci. Accessed on 25, November 2024.

22. Jones PW, Harding G, Berry P, Wiklund I, Chen WH, Kline Leidy N. Development and first validation of the COPD assessment test. Eur Respir J. 2009;34(3):648–654. doi:10.1183/09031936.00102509

23. Perez T, Burgel PR, Paillasseur JL, et al. Modified medical research council scale vs baseline dyspnea index to evaluate dyspnea in chronic obstructive pulmonary disease. Int J Chron Obstruct Pulmon Dis. 2015;10:1663–1672. doi:10.2147/COPD.S82408

24. Skolnik NS, Nguyen TS, Shrestha A, Ray R, Corbridge TC, Brunton SA. Current evidence for COPD management with dual long-acting muscarinic antagonist/long-acting β₂-agonist bronchodilators. Postgrad Med. 2020;132(2):198–205. doi:10.1080/00325481.2019.1702834

25. Rodrigo GJ, Price D, Anzueto A, et al. LABA/LAMA combinations versus LAMA monotherapy or LABA/ICS in COPD: a systematic review and meta-analysis. Inter J Chronic Obstruct Pulmon Dis. 2017;12:907–922. doi:10.2147/COPD.S130482

26. Chen C-Y, Chen W-C, Huang C-H, et al. LABA/LAMA fixed-dose combinations versus LAMA monotherapy in the prevention of COPD exacerbations: a systematic review and meta-analysis. Therape Adv Resp Dis. 2020;14:1753466620937194. doi:10.1177/1753466620937194

27. Perera B, Barton C, Osadnik C. General practice management of COPD patients following acute exacerbations: a qualitative study. Br J Gen Pract. 2023;73(728):e186–e195. doi:10.3399/BJGP.2022.0342

28. Molin KR, Egerod I, Valentiner LS, Lange P, Langberg H. General practitioners’ perceptions of COPD treatment: thematic analysis of qualitative interviews. Int J Chron Obstruct Pulmon Dis. 2016;11:1929–1937. doi:10.2147/COPD.S108611

29. Leemans G, Vissers D, Ides K, Van Royen P. Perspectives and attitudes of general practitioners towards pharmacological and non-pharmacological COPD management in a Belgian primary care setting: a qualitative study. Int J Chron Obstruct Pulmon Dis. 2023;18:2105–2115. doi:10.2147/COPD.S423279

Introduction

Nontuberculous mycobacteria (NTM) are environmental pathogens with over 190 identified species,¹ primarily affecting individuals with preexisting lung disease or immunodeficiency.² There is a rising trend in incidence of infection and mortality globally, including among younger populations. Among children, the infection may occur with or without pre-existing lung disease.³ Risk factors among adults have been well studied, but there are fewer pediatric studies in this area of study.⁴ Past research has found that immunodeficiency, the developing immune system, and chronic lung disease heighten the risk of NTM infections in the pediatric population.⁵ NTM infections are especially prevalent because of their ability to inhabit common soil and water sources such as water distribution systems, allowing repeated environmental exposures to invade the lungs through bioaerosols.⁵ It is also thought that different species and subspecies of mycobacteria containing genetic differences manifest themselves differently in infection and clinical response.⁶ For example, two of the most common NTM species Mycobacterium avium and Mycobacterium abscessus differ in their infections with the former being characterized by slow growth, greater general prevalence, and weaker biofilm formation,⁷ while the latter is associated with significant morbidity/mortality, is clinically resistant to most antibiotics, and shows greater general immune responses throughout the course of infection.⁸ Infections from different types of these bacteria can vary by geographic location⁵ with Mycobacterium abscessus being commonly observed in East Asia and Mycobacterium avium complex and Mycobacterium kansasii occurring most commonly in many parts of the US. In Europe, Asia, and partially in Australia, increases in latitude generally see higher rates of Mycobacterium avium complex.

NTM pulmonary disease is frequently misdiagnosed as tuberculosis due to similar symptoms, leading to delays in appropriate treatment. One of the most common signs of NTM infection in healthy children is cervical lymphadenitis, but its clinical presentation is indistinguishable from that of cervical lymphadenitis in regular tuberculosis.⁹ Pulmonary infection, while less commonly associated may be more difficult to treat. This is especially problematic in countries with high tuberculosis rates, where NTM testing methods are resource limited.^10–12 Industrialized nations often report higher NTM incidence than tuberculosis, although pediatric prevalence globally is not well studied.^13,14

This study was conducted to investigate pediatric pulmonary NTM infections among the non-cystic fibrosis population. The global incidence of NTM infections is increasing, and more studies are needed to better understand the disease among the pediatric population.¹⁵ Unlike Cystic Fibrosis patients, who are known to have higher susceptibility to pulmonary infections,¹⁶ the risk factors and clinical manifestations in non-cystic fibrosis pediatric population remains poorly understood. This study aims to investigate the epidemiology, clinical comorbid condition, and five year clinical outcomes of non CF pulmonary NTM infections in distinct pediatric age groups. We hypothesize that there are important differences in these key areas among pediatric age groups. This may lead to the identification of characteristics that could guide clinical decision-making and potentially improve patient outcomes.

The study further hypothesizes that: i) BMI percentiles mediate susceptibility to NTM infections in children, ii) common comorbidities are expected to be significant risk factors for pediatric pulmonary NTM infections, iii) pediatric pulmonary NTM may predispose patients to future lung disease.

Methods

The TriNetX Clinical Data Platform

We utilized the TriNetX research platform to select our patient cohorts from a total of 152,714,105 collected, de-identified patient records on the Global Collaborative Network containing 127 health-care organizations from the following 17 countries: United States, Canada, United Kingdom, Germany, France, Italy, Spain, Netherlands, Denmark, Australia, Singapore, Japan, Brazil, Mexico, Israel, South Korea, and Switzerland. TriNetX deidentifies and aggregates electronic health record (EHR) data from health-care systems, primarily drawing from large academic medical institutions across the USA. It organizes diagnoses under specific ICD codes and stores information such as demographics, medications, lab results, procedures, and vital signs. The platform provides a secure, web-based access to patient-level analyses and interpretation. It reports updated population-level data while ensuring Health Insurance Portability and Accountability Act (HIPAA) compliance.

Data Collection and Stratification

From the TriNetX Global Collaborative Network, the pediatric patient population was stratified into four groups: i) 0–2 years, ii) 3–5 years, iii) 6–12 years, and iv) 13–18 years based on age. The inclusion criteria were: i) subjects with pulmonary NTM infection, and ii) ages 0–18 years. The exclusion criteria were: i) Cystic Fibrosis, ii) Tuberculosis, iii) smoking history, iv) cutaneous non-mycobacterial infections, and v) adult patients. The total cohort (0–18 years) consisted of 2,344 NTM cases from a larger population base of over 23 million pediatric patients collected on July 13, 2024. The distribution among the four groups was expressed both numerically and as a percent of patients in each respective age group with NTM.

Data Analysis

Data analysis focused on patient demographics, clinical characteristics, comorbidities, and outcomes of the 2,344 NTM cases, with particular attention to odds ratios and lab values associated with these infections. Descriptive analysis for this data included prevalence, mean values, and standard deviation within the age cohorts. Demographic information included age, sex, ethnicity, and race. Comorbidities were identified in our analysis. Clinical data were collected including mean values for BMI and oxygen saturation.

Statistical analysis was performed to compare the prevalence and outcomes of NTM across the different age groups, and to evaluate the different comorbidities experienced by each age group. Specifically, the six most common five-year outcomes were compared across the cohorts, assessing risk difference, confidence interval, risk ratio, odds ratio, and statistical significance to determine risk levels between pairs of groups. The analysis was conducted through the built-in analytics tools in the TriNetX software where a p value of <0.05 was defined as statistically significant. Our patients were selected using the inclusion and exclusion criteria outlined in Table 1. Descriptive statistics (mean, SD, proportion) were reported for demographics and clinical features. Comparative analysis across age groups was conducted using Chi-square tests for categorical variables and Student’s t-test or ANOVA for continuous variables. To evaluate associations between NTM and clinical outcomes across age groups, we conducted: Logistic regression analysis for binary outcomes to generate odds ratios (OR), Binomial regression to estimate risk ratios (RR) when appropriate. All models were adjusted for key covariates including age, sex, race, and comorbidity burden. Point estimates were reported with 95% CI.

Table 1 Inclusion and Exclusion Criteria Entered into TriNetX

Ethics

The University of California, Riverside IRB determined that the current study was exempt from further ethics review as it did not fit under the federal definition of human subjects research [DHHS 45 CFR46.102(e), 46.102(l)] or clinical investigation [FDA 21 CFR 50.3(c), 56.102(c)].

Results

Demographics

The demographic data provided insight into the prevalence and distribution of pediatric pulmonary NTM infections among the age cohorts, and with respect to sex, race and ethnicity. The study cohort comprised 2,344 cases stratified across four age groups: 0–2 years, 3–5 years, 6–12 years, and 13–18 years. The majority of NTM cases were observed in the 6–12 year age group at 1074 (734/100,000), followed closely by the 13–18 year age group at 760 (848/100,000). The 3–5 year age group had 401 patients (1261/100,000) and the 0–2 group had 109 patients (689/100,000) (Table 2). There were gender differences in the prevalence of pediatric pulmonary NTM lung infections (Table 3). There was a higher mean prevalence of NTM infections amongfemales compared to males 53.31% vs 46.29% among all age groups. There was no identified gender for 4.17% of the cohort. The majority of the cohort was identified as white 57.8%, followed by Black/African American, 8.88%, Asian, 4.49%, Native American, 2.83%, Native Hawaiian, 1.19%, another race, 8.52%, and unspecified race 21.6%. BMI percentiles were above the 50th percentile for all age groups, and this was statistically significant (p < 0.05) (Table 4).

Table 2 Age Demographics of Our Study Cohort, Including the Number of Patients in Each Age Cohort

Table 3 Sex Demographics of Our Study Cohort, Stratified by Age

Table 4 BMI Percentiles of Each Age Cohort

Laboratory Findings

The data indicated a varying prevalence of NTM infections across the age groups, with the highest prevalence observed in children aged 6–12 years at 1,074 cases (0.007339%). Lab values, particularly those related to immune function, revealed a trend towards higher inflammatory markers among older children, possibly reflecting a more robust immune response or delayed diagnosis. There was an elevated mean white blood cell count in the 13–18 age group at 18.5×10³/μL compared to the expected range of 4.0×10³/μL to 11.0×10³/μL (Table 5). Similarly, CRP mean levels for this age group were significantly above the expected value of 1 mg/L at 26.8 mg/L. In the 3–5 year and 13–18 year cohorts, basophil levels were above the expected 0–1% at 2.68% and 1.83%, respectively. Ferritin levels were higher in the 6–12 year and 13–18 year groups at 546 ng/mL and 1758 ng/mL, respectively, compared to the normal range of 10–200 ng/mL. Among younger children, there were lower levels of inflammatory markers, which may suggest an underdeveloped immune response or early-stage infection.

Table 5 Comparison of Selected Inflammatory Markers by Age Cohort

Comorbid Conditions

Comorbidities such as acute pharyngitis, pneumonia, asthma, malignancy, and immunodeficiency were identified. (Table 6 and Figure 1). The most common comorbidity among the groups was acute pharyngitis in the 13–18 age group at 30% of the cohort. There was a higher burden of NTM infections among the older pediatric group, ages 13 to 18 years. This group also had the highest proportion of each comorbidity: 18% pneumonia, 22% asthma, 12% malignancy, and 11% immunodeficiency. The overall proportion of individuals with comorbidities was lower in the 6–12 year age group, still with acute pharyngitis leading at 19%, pneumonia at 12%, asthma at 13%, malignancy at 6%, and immunodeficiency at 7%. The 3–5 year old cohort had the following comorbid conditions: 11% acute pharyngitis, 7% pneumonia, 11% asthma, 5% malignancy, and 4% immunodeficiency. The 0–2 age groups saw a notable increase in acute pharyngitis, pneumonia, and malignancy at 18%, 9%, and 13%, respectively. The age 0–2 year old group had the highest percent of malignancy. Asthma and immunodeficiency data was not recorded for this age group likely due to reduced diagnosis of these issues at such ages. The most prevalent comorbidity was acute pharyngitis at 78% across all age groups, and no other comorbidity rose above 46%.

Table 6 Comparison of the Top Five Most Common Comorbidities by Age Cohort

Figure 1 The five most common comorbidities associated with NTM infection as a percent of each age cohort. *indicates P < 0.05.

Discussion

The findings of this study demonstrates an age-based differential presentation of Pulmonary NTM infection among the cohort studied. This study highlights the need for age-specific approaches to the diagnosis and management of pediatric pulmonary NTM infections. Our study adds novel data regarding the global prevalence of NTM pulmonary infections among a Pediatric population. The varying prevalence and outcomes across age groups suggest that different factors, such as immune development and environmental exposure, play significant roles in the susceptibility to and progression of these infections. It is important to understand the mechanisms of these differences. Further studies will be completed to better understand the age based differential of disease prevalence.¹⁷ The top five comorbidities we identified were acute pharyngitis, unspecified pneumonia, asthma, malignancy and immunodeficiency. The presence of these comorbidities also correlated with a higher burden of NTM infection in the older pediatric groups, suggesting that these children might have prolonged exposure to risk factors or delayed diagnosis.¹⁸ This increased susceptibility is thought to be related to damaged respiratory mucosa, promoting NTM attachment and infection.¹⁹ Our observed comorbidity of asthma drew our attention to the fact that children with underlying chronic lung diseases may have a higher likelihood of severe outcomes, including prolonged hospitalizations and the need for intensive care.²⁰ There was a higher odds ratio (OR) of developing more severe lung disease, such as pneumonia, pulmonary fibrosis, lung abscess, bronchiectasis, interstitial lung disease upon NTM infection among 0–2 year olds compared to older age groups (Table 7). This is also supported by several reports of some of these outcomes occurring in various age groups.^21,22 Immunodeficiency, whether congenital or acquired, tends to be associated with a more complicated clinical course and higher mortality rates, and we also observed it as a comorbidity.²³ Specifically, this immunosuppression allows for extrapulmonary NTM disease to develop and spread by escaping the body’s immune cells and entering the lymphatic system and bloodstream.²⁴ The finding of lung or mediastinal abscess as a five year outcome heightens our clinical concern among this cohort, especially when considering clinical uncertainty in treatment of NTM.²⁵ The analysis of racial and ethnic data was limited in this study due to potential incomplete availability of documentation of some demographics in the electronic health records, which may have introduced bias in the interpretation of these variables. However, our demographic data supports our initial hypothesis that even a mildly elevated BMI may increase susceptibility for pediatric NTM.²⁶ While current literature supports lower BMI as a significant risk factor for NTM infection,²⁷ one possible explanation is the susceptibility of the host in states of malnutrition. Individuals with higher BMI are more likely to be diagnosed with chronic inflammatory or autoimmune conditions²⁸ which are commonly treated using immunosuppressive corticosteroids,²⁹ potentially increasing the risk for NTM infection.^30,31 In addition to BMI, other physical conditions and comorbidities, particularly chronic lung diseases and immunodeficiency, underscore the need for vigilant screening and management in at-risk populations. The significant odds ratios associated with future 5-year outcomes in older children (Table 7) suggest that more aggressive diagnostic and therapeutic strategies may be warranted in these age groups.³² Our findings show that the majority of NTM cases were observed in the 6–12 year age group and the highest percent of cases were observed in the 3–5 year age group. This finding shows that school-aged children and adolescents are more likely to be diagnosed with NTM infections, potentially due to increased exposure to environmental reservoirs of NTM, such as water and soil, and higher rates of outdoor activities compared to toddlers.³³ Abnormal inflammatory marker values among the 13–18 age group were also a notable age cohort-based finding. Particularly, the elevated white blood cell count, ferritin levels, and CRP in older children suggest a more pronounced inflammatory response in the adolescent age group with NTM infections. These findings are distinct from the data that has been found from a previous study done in Wisconsin. In the Wisconsin study, the isolates were based on statewide data, rather than a global database, and this study included non Pulmonary infections. Our study is the first to our knowledge to analyze a global database, with a focus on Pediatric non CF Pulmonary infections. The data in the Wisconsin study included Cystic Fibrosis patients. Since CF is a known risk factor for Pulmonary NTM, our study design focused on non CF patients.³² From our demographic data, we also found that there were significant differences in the gender of infected patients. This trend aligns with existing adult literature that suggests females may have a higher susceptibility to pulmonary infections due to differences in immune response, hormonal influences, or behavioral factors, such as a greater likelihood of engaging in activities that increase exposure to NTM.³⁴ There were statistically significant differences in NTM infection rates among different racial groups, which has to our knowledge not been studied utilizing a global EHR database. The available data from diverse populations shows that certain racial and ethnic groups might be disproportionately affected by NTM infections, potentially due to disparities in healthcare access, environmental exposures, or genetic predispositions.³⁵ This finding highlights the need for more comprehensive data collection and medical record documentation in future studies to better understand the role of race and ethnicity in the epidemiology of pediatric pulmonary NTM infections.

Table 7 Pulmonary Health Outcomes by Age Cohort

Limitations

This study has several limitations, including its retrospective nature and reliance on data from the TriNetX platform, which may introduce selection bias. Additionally, the reliance on electronic health record data may result in incomplete or inaccurate documentation of clinical characteristics and outcomes. The platform’s retrospective nature may introduce selection bias, affecting the generalizability of the results. Additionally, differences in cohort sizes can impact comparison results. TriNetX also anonymizes data by replacing counts of 1–10 with “10” to protect patient privacy, which limits the statistical analysis of rare outcomes. Furthermore, patients who move to non-TriNetX facilities are lost and not included in the outcome comparisons. There may also be comorbidities that were documented in patients’ records in institutions not participating in TriNetX. The study also did not account for the potential impact of socio-economic factors, geographic location, or variations in healthcare access, which could influence the prevalence and outcomes of NTM infections.^36,37 Despite these limitations, our study has provided an extensive analysis of global data in this area of study, utilizing a novel EHR based database.^38,39 Additionally, more advocacy is needed to ensure that NTM is properly documented, species-wise in the EHR to ensure that future epidemiological studies can be done effectively.

Conclusions

Our study uniquely provides an analysis of global prevalence of non CF Pediatric Pulmonary NTM infections. The study contributes to current knowledge in the field and identifies selected future five year outcomes. We also compared the associated risk for the specific age cohorts studied. This study thus adds to current understanding of the incidence and characteristics of Pediatric NTM non CF pulmonary disease. Future studies to develop treatment strategies and age based considerations are therefore important in the management of Pediatric pulmonary NTM infection.

Disclosure

The authors report no conflicts of interest in this work.

References

1. Daley C, Laccarino J, Lange C, Cambau E. Treatment of nontuberculous mycobacterial pulmonary disease: an official ATS/ERS/ESCMID/IDSA clinical practice guideline. Clin Infect Dis. 2020;71(4:e1–36. doi:10.1093/cid/ciaa241

2. Bai A, Belda O, Dosanjh A. Pulmonary nontuberculous mycobacterial infection in infants: a systematic review. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC68721029/#. Accessed August 22, 2025.

3. Ratnatunga C, Lutzky V, Kupz A, Doolan D, Reid D. The rise of non-tuberculosis mycobacterial lung disease. Front Immunol. 2020. 11. doi:10.3389/fimmu.2020.00303

4. Loebinger M, Quint J, van der Laan R, Chawla R. Risk factors for nontuberculous mycobacterial pulmonary disease. Chest. 2023;164(5):1115–1124. doi:10.1016/j.chest.2023.06.014

5. Honda JR, Virdi R, Chan ED, Sun X, Yarden O, Li S. Global environmental nontuberculous mycobacteria and their contemporaneous man-made and natural niches. Front Microbiol. 2018;9:9. doi:10.3389/fmicb.2018.02029

6. Lamb G, Starke J. Mycobacterium abscessus infections in children: a review of current literature. J Pedia Infect Dis Soc. 2018;7(3):e131–e144. doi:10.1093/jpids/piy047

7. Belardinelli JM, Li W, Avanzi C, Angala SK, Lian E. Unique features of mycobacterium abscessus biofilms formed in synthetic cystic fibrosis medium. Front Microbiol. 2021;12. doi:10.3389/fmicb.2021.743126

8. Sampaio EP, Elloumi HZ, Zelazny A, et al. Mycobacterium abscessus and M. avium trigger toll-like receptor 2 and distinct cytokine response in human cells. Am J Respir Cell Mol Biol. 2008;39(4):431–439. doi:10.1165/rcmb.2007-0413OC

9. Lopez-Varlea E, Garcia-Basteiro A, Santiago B, Wagner D, van Ingen J, Kampmann B. Non-tuberculous mycobacteria in children: muddying the waters of tuberculosis diagnosis. Lancet Resp Med. 2015;3(3):244–256. doi:10.1016/S2213-2600(15)00062-4

10. Bonnet M, Chamroeun San K, Pho Y, Sok C. Nontuberculous mycobacteria infections at a provincial reference hospital, Cambodia. Emerging Infectious Diseases. 2017;23(7):1139–1147. doi:10.3201/eid2307.170060

11. Chindam A, Vengaldas S, Srigiri V, Syed U. Challenges of diagnosing and treating non-tuberculous mycobacterial pulmonary disease [NTM-PD]: a case series. J ClinTubercul Other Mycobacter Dis. 2021;25:100271. doi:10.1016/j.jctube.2021.100271

12. Wu ML, Aziz D, Dartois V, Dick T. NTM drug discovery: status, gaps and the way forward. Drug Discovery Today. 2018;23(8):1502–1519. doi:10.1016/j.drudis.2018.04.001

13. Ryu YJ, Koh WJ, Daley, Daley CL. Diagnosis and treatment of nontuberculous mycobacterial lung disease: clinicians’ perspectives. Tubercul Resp Dis. 2016;79(2):74. doi:10.4046/trd.2016.79.2.74

14. Pennington KM, Vu A, Challener D, et al. Approach to the diagnosis and treatment of non-tuberculous mycobacterial disease. J Clin Tuberc Mycobact Dis. 2021;24:100244. doi:10.1016/j.jctube.2021.100244

15. Raju RM, Raju SM, Zhao Y, Rubin EJ. Leveraging advances in tuberculosis diagnosis and treatment to address nontuberculous mycobacterial disease. Emerging Infectious Diseases Journal – CDC. 2016;22(3). doi:10.3201/eid2203.151643

16. Lyczak J, Cannon C, Pier G. Lung infections associated with cystic fibrosis. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC118069/. Accessed May 28, 2025.

17. Adjemian J, Frankland TB, Daida YG, et al. Epidemiology of nontuberculous mycobacterial lung disease and tuberculosis, Hawaii, USA. Emerging Infectious Diseases Journal – CDC. 2017;23(3). doi:10.3201/eid2303.161827

18. Mauch RM, Mansinho AA, Rocha PM, et al. Nontuberculous mycobacterial infections in a Brazilian pediatric population: a seven-year survey. Pathog Glob Health. 2020;114(2):104–108. doi:10.1080/20477724.2020.1725330

19. Bhattacharya J, Mohandas S, Goldman D. Nontuberculous mycobacterial infections in children | pediatrics in review | American academy of pediatrics. Available from: https://publications.aap.org/pediatricsinreview/article-abstract/40/4/179/35278/Nontuberculous-Mycobacterial-Infections-in?redirectedFrom=fulltext. Accessed May 28, 2025.

20. Fritscher L, Marras T, Bradi A. Nontuberculous mycobacterial infection as a cause of difficult-to-control asthma – chest. Available from: https://journal.chestnet.org/article/S0012-3692(11)60010-X/abstract. Accessed May 28, 2025.

21. Park B, Park J. Atypical presentation of nontuberculous mycobacterial pulmonary infection in a patient with interstitial lung abnormality: a case report – European journal of radiology open. Available from: https://www.ejropen.com/article/S2352-0477(21)00033-2/fulltext. Accessed May 28, 2025.

22. Yin H, Gu X, Wang Y, et al. Clinical characteristics of patients with bronchiectasis with nontuberculous mycobacterial disease in Mainland China: a single center cross-sectional study. BMC Infect Dis. 2021;21(1):1216. doi:10.1186/s12879-021-06917-8

23. Ford T, Silcock R, Holland S. Overview of nontuberculous mycobacterial disease in children. J Paedia Child Health. 2025;57(1):15–8. doi:10.1111/jpc.15257

24. Cinicola B, Ottaviano G, Hashim I. Prevalence and characteristics of non-tuberculous mycobacteria (NTM) infection in recipients of allogeneic hematopoietic stem cell transplantation: a systematic review and meta-analysis. Journal of Clinical Immunology. 2025. doi:10.1007/s10875-023-01615-3

25. Kuhajda I, Zarogoulidis K, Tsirgoggiani K. Lung abscess-etiology, diagnostic and treatment options. Available from: https://atm.amegroups.org/article/view/7152/7940. Accessed May 28, 2025.

26. Andersen CJ, Murphy KE, Fernandez ML. Impact of obesity and metabolic syndrome on immunity. Adv Nutr Bethesda Md. 2016;7(1):66–75. doi:10.3945/an.115.010207

27. Kang JY, Han K, Kim. Severity of underweight affects the development of nontuberculous mycobacterial pulmonary disease; a nationwide longitudinal study | scientific Reports. Available from: https://www.nature.com/articles/s41598-022-21511-x. Accessed May 28, 2025.

28. Obesity as a risk and severity factor in rheumatic diseases (autoimmune chronic inflammatory diseases) – PMC. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC4227519/. Accessed May 28, 2025.

29. Coutinho A, Chapman. The anti-inflammatory and immunosuppressive effects of glucocorticoids, recent developments and mechanistic insights – PMC. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC3047790/. Accessed May 28, 2025.

30. Liu V, Winthrop K, Lu Y. Association between inhaled corticosteroid use and pulmonary nontuberculous mycobacterial infection – PMC. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC6321990/. Accessed May 28, 2025.

31. Mohseni M, van der Valk ES, Van der Hurk MJB, Savas M, Boon MR, van Rossum EFC. Corticosteroid use and long-term changes in weight and waist circumference: the lifelines cohort study. J Clin Endocrinol Metab. 2025;dgaf166. doi:10.1210/clinem/dgaf166

32. Vonasek BJ, Gusland D, Tans-Kersten J, Misch EA, Gibbons-Burgener SN. Nontuberculous mycobacterial infection in Wisconsin children and adolescents. J Clin Tuberc Mycobact Dis. 2024;36:100456. doi:10.1016/j.jctube.2024.100456

33. Meoli A, Deolmi M, Iannarella R, Esposito S. Non-tuberculous mycobacterial diseases in children. Pathogens. 2020;9(7):553. doi:10.3390/pathogens9070553

34. Chan ED, Slender IMD. Older women appear to be more susceptible to nontuberculous mycobacterial lung disease. Gend Med. 2010;7(1):5–18. doi:10.1016/j.genm.2010.01.005

35. Henkle E, Hedberg K, Schafer S, Novosad S, Winthrop KL. Population-based incidence of pulmonary nontuberculous mycobacterial disease in oregon 2007 to 2012. Ann Am Thorac Soc. 2015;12(5):642–647. doi:10.1513/AnnalsATS.201412-559OC

36. Zhao Z, Hu H, Wang M. Risk factors and mental health status in patients with non-tuberculous mycobacterial lung disease: a single center retrospective study. Available from: https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2022.912651/full. Accessed May 28, 2025.

37. O’Connell J. Nontuberculous respiratory infections among the homeless. Available from: https://pubmed.ncbi.nlm.nih.gov/1810003/. Accessed May 28, 2025.

38. Ku J, Henkle E, Carlson K. Validity of diagnosis code–based claims to identify pulmonary NTM disease in bronchiectasis patients. Available from: https://wwwnc.cdc.gov/eid/article/27/3/20-3124_article. Accessed May 28, 2025.

39. Mejia-Chew C, Yaeger L, Montes K. Diagnostic accuracy of health care administrative diagnosis codes to identify nontuberculous mycobacteria disease: a systematic review. Available from: https://academic.oup.com/ofid/article/8/5/ofab035/6278496. Accessed May 28, 2025.