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  • Utilization and Determinants of Anticancer Drugs Under China’s Nationa

    Utilization and Determinants of Anticancer Drugs Under China’s Nationa

    1Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, People’s Republic of China; 2School of Public Administration, Zhongnan University of Economics and Law, Wuhan, Hubei Province, People’s Republic of China

    Correspondence: Junnan Jiang, School of Public Administration, Zhongnan University of Economics and Law, No. 182, Nanhu Avenue, East Lake New Technology Development Zone, Wuhan City, Hubei Province, 430073, People’s Republic of China, Email [email protected]

    Purpose: The Chinese government began to take national drug price negotiation (NDPN) in 2016, aiming to enhance the accessibility and affordability of anticancer drugs. This study aims to assess the utilization and influence factors of anticancer drugs under NDPN policy in China.
    Patients and Methods: Gastric cancer patients within chemotherapy were included. Independent variables were measured by age, gender, insurance type, total medical expenditure (THE), length of stay (LOS), drug-to-total-expense ratio (DTR). The primary outcomes were negotiated drugs usage, costs and treatment outcome. Two-part model was used to identify influence factors of anticancer drugs utilization. Propensity Score Matching (PSM) was employed to evaluate the impact of negotiated drug utilization on treatment outcomes among inpatients.
    Results: The sample included 9868 gastric cancer patients from three cities. Outpatient patients demonstrated limited utilization of negotiated drugs (1.33%). Patients aged 61– 75 (β=0.923, P < 0.01) and over 75 years (β=0.946, P < 0.05) were more likely to use negotiated drugs. Key factors influencing inpatient drug utilization included medical insurance type (β=− 0.245, P< 0.01), LOS (β=− 0.122, P< 0.001), and the DTR (=0.037, P< 0.001). The use of negotiated drugs had no significant effect on treatment outcomes.
    Conclusion: Their limited utilization of negotiated drugs for outpatients arises an urgent necessity for more comprehensive insurance coverage, and the no significant outcome effect dedicated the importance to rigorously validate the effectiveness of these drugs with abundant real-world evidence in the foreseeable future.

    Introduction

    Cancer has emerged as a preeminent global health concern, claiming a substantial number of lives annually. Recently published data indicate a staggering figure of over 19.3 million newly diagnosed and registered cancer cases worldwide.1 The National Cancer Center (NCC) of China has reported a notable incidence of approximately 4,824,700 new cancer cases and 2,574,200 new cancer deaths occurred in China in 2022.2 The exorbitant pricing of pharmaceuticals has emerged as a pivotal concern within oncological therapies.3

    It is now widely recognized that efficacious negotiations on drug pricing have the potential to mitigate the escalation of costs associated with these treatments.4 The Chinese government began to take national drug price negotiation (NDPN) in 2016.5 As of January 2023, there were 430 kinds of negotiated drugs encompassed in the National Reimbursement Drug List (NRDL), which included hundreds of anti-cancer medicines. China has a huge population base and pharmaceutical market volume, and the entry of anticancer drugs into the NRDL will bring a significant increase in sales and profit returns, and also provide more real-world clinical data for the future innovation and research and development of enterprises,6 the procedures of NDPN are detailed in Table S1.

    But do drug price negotiations actually increase sales significantly? Between the implementation of the new negotiations process in 2011 through the first quarter of 2019, the net negotiated prices averaged 23.6% below the manufacturers’ list prices.7 The statutory ceiling prices for negotiation would have reduced spending by $26.5 billion on these drugs.8 The NDPN policy also improved the availability, utilization, and affordability of anticancer medicines in China.9 The utilization of the medicines increased by 11.44 defined daily doses (DDDs) immediately.10 Drug price negotiation also has extensive practice experience in Europe and the United States. In August 2022, the Inflation Reduction Act (IRA) was signed into law, allowing Medicare to negotiate the prices of a small number of medicines beginning in 2026.11 The IRA limits the Centers for Medicare & Medicaid Services (CMS) to negotiating up to 20 high-spending drugs each year, which can only qualify after being on the market for at least 9 years (13 years for biologic products).12 However, China has allowed innovative drugs launched in the same year to enter the scope of price negotiation, which undoubtedly expands the coverage of drugs under this reform. In Germany, the umbrella organization of sickness funds (GKV-SV) then negotiates a price with the manufacturer based on the Federal Joint Committee (GBA) assessment, and the prices charged by the manufacturer for its new drug in other European markets.13 China’s NDPN system is not as mature as Germany’s innovative drug pricing mechanism, and it has not yet implemented a tiered classification of drugs based on pharmacoeconomic outcomes.

    The research landscape regarding factors influencing access to anticancer medications is extensive,14 particularly in low- and middle-income countries (LMICs). Several studies have revealed that private hospitals (71%) tend to have higher availability of anticancer drugs compared to public hospitals (43%), yet access to novel anticancer agents remains challenging in both sectors.15,16 Another investigation observes that in countries such as India and Bangladesh, even generic anticancer drugs listed on the World Health Organization’s Essential Medicines List (WHO EML) are unaffordable for patients due to high out-of-pocket expenses.17 The cost and affordability of recently market-approved anticancer treatments have emerged as primary contributors to disparities in access to these medications.18 Studies highlight pronounced inequalities in cancer treatment, which are primarily associated with limited coverage by public insurance schemes and exclusion from the EML.19 Systematic evaluations of medication adherence to oral anticancer drugs have identified age,20 gender,21 out-of-pocket medical costs22 and other socioeconomic status.23

    Our study significantly contributes to the existing literature in three pivotal aspects. Firstly, distinct from prior works such as Cai10 and Zhou,6 which predominantly centered on the quantity of publicly disclosed drug purchases, our model introduces a novel dimension by incorporating patient-level drug utilization. The disparity between hospital procurement volumes and actual patient consumption underscores the importance of utilizing actual anticancer drug consumption data from both outpatient and inpatient settings for gastric cancer patients, as this better mirrors the policy’s true impact. Secondly, we integrate an assessment of the therapeutic efficacy of negotiated drugs. Beyond mere analysis of immediate negotiated drug consumption, we delve into whether these innovative medications positively influence cancer patient outcomes. To this end, we meticulously evaluate the effects of negotiated drugs on treatment outcomes, while controlling for confounding factors from other covariates.

    Material and Methods

    Data Source

    To analyze the impact of NDPN on the use of clinical anticancer drugs, this study sampled cities in three different provinces in China: Shanghai (east), Xi’an (west), and Shenyang (northeast). Random sampling of outpatient and inpatient patients with gastric cancer in tertiary hospitals was conducted from 2018 to 2020. We conducted drug usage and health expenditure data thorough Hospital Information System (HIS), sample inclusion and exclusion rules are set out in Table S2.

    Variables

    In this study, negotiated drugs related to gastric cancer treatment in NRDL at the end of 2018–2020 were used as a reference to determine whether patients used the negotiated drugs (Table S3). The expenditure of negotiated drugs was calculated by the total costs of negotiated drugs. Treatment outcomes, as assessed at the time of discharge for patients with gastric cancer, are documented by physicians based on the entirety of the treatment process. These outcomes are categorized into four distinct groups: cure, improvement in condition, no improvement in condition, and death. One indicating cure and improvement, 0 encompassing both no improvement and death.

    Independent variables comprised age, gender, insurance type (Urban Employee Basic Medical Insurance (UEBMI) and Urban and Rural Resident Basic Medical Insurance (URRBMI)), total medical expenditure (THE), length of stay (LOS), and the drug-to-total-expense ratio (DTR). THE, a comprehensive measure, encapsulates all expenses incurred by gastric cancer patients during chemotherapy, encompassing medication costs, bed charges, outpatient registration fees, and expenses related to radiological and biochemical examinations, among other miscellaneous items.24 Prior to 2019, DTR served as a pivotal metric for evaluating the medical quality of tertiary hospitals, with an annual average benchmark not exceeding 45%. While this indicator has been subsequently surpassed in 2019 by a more extensive array of metrics that encompasses adjunctive medications, essential drugs, antibiotics, outpatient pharmaceutical expenditures, and inpatient drug costs, the DTR retains its relevance in the decision-making process for selecting anticancer medications.25

    Data Analysis

    A two-part model has been devised to address the constrained lower bound in their value range-dependent variables.26 Drug consumption by patients results in a positive expenditure, whereas non-consumption yields a zero expenditure. This two-part model facilitates the modeling of the censoring mechanism (zeros) and the expenditure outcomes (nonzeros) through independent processes, thereby enabling the zeros and nonzeros to be governed by distinct probability distributions, akin to a specialized mixture model.27 A probit model is employed to elucidate the decision to opt for negotiated drugs,28 while linear regression is utilized to explain the magnitude of drug expenditures conditional on usage.

    In the present study, Propensity Score Matching (PSM) methodology was utilized to rigorously assess the influence of negotiated drug utilization on therapeutic outcomes among hospitalized patients diagnosed with gastric cancer. The propensity score is defined as the probability of an individual receiving the treatment () given their observed covariates . It is typically estimated using a logistic regression model:


    where are coefficients learned from the data. Individuals in the treatment group () are matched with individuals in the control group () who have similar propensity scores. This reduces selection bias by balancing the distribution of covariates between the two groups, mimicking a randomized controlled trial. This approach entailed the meticulous pairing of individuals from a control cohort, comprising those who did not avail of negotiated drugs, with those in an experimental group, characterized by the utilization of such drugs. The pairing was based on the similarity of participants across a comprehensive set of covariates, ensuring a balanced comparison. The balance test before and after variable matching was shown in Table S4. Nearest neighbor matching, kernel matching, and radius matching were employed to estimate the Average Treatment Effect on the Treated (ATT), thereby providing a nuanced understanding of the causal impact of negotiated drug usage on patient outcomes.

    Results

    The study encompassed a sample of 9,419 outpatient patients and 449 inpatient patients. Within the outpatient cohort, 5,921 (62.86%) were male, and 8,409 (89.28%) resided in Shanghai. The mean medical expenditure for outpatient amounted to 149.86 yuan. Only 1.33% (n=125) of outpatient records indicated the use of negotiated drug, which is noted in Table 1. Among inpatients, 334 (74.39%) were male, and the highest proportion (40.31%) hailed from Shenyang. In both outpatient and inpatient settings, the age distribution of male gastric cancer patients was concentrated in the 60–75 years age groups. In outpatient patients, women accounted for 79.6% of those under 60 years of age (Figure 1). Similarly, the majority of outpatients (79.88%) and inpatients (83.30%) were covered by URRBMI, covers urban and rural residents in China, while the UEBMI provides medical insurance for employees. Comparatively, UEBMI offers higher welfare benefits. Therefore, it is not surprising that in our sample, the average medical expenses of inpatients covered by UEBMI were 30,725.53 yuan, significantly higher than those covered by URRBMI (25,041.6 yuan). Patients had an average LOS of 7.28±4.72 days, incurring a mean medical cost of 263,585.70±268,800.55 yuan, with 46.00% DTR (SD=25.97). 40.53% (n=182) of inpatients received treatment with negotiated drugs.

    Table 1 Characteristics of Gastric Cancer Patients

    Figure 1 The age and gender distribution of outpatients and inpatients.

    Age, sex, type of medical insurance and total outpatient cost all affect whether patients with malignant tumors use negotiated drugs in outpatient treatment (Table 2). Compared to patients less than 60, older adults aged 61–75 (β=0.923, P < 0.01) and over 75 years (β=0.946, P < 0.05) were more likely to use negotiated drugs. However, results from the linear regression model showed that among outpatient patients who used negotiated drugs, medical expenditure incurred by patients over 75 years (β=−1498.625, P < 0.001) was significantly lower than that of those under 60 years. Compared patients with UERMI, patients covered by URRBMI used less negotiated drugs (β=−0.932, P < 0.001). Patients with higher outpatient care costs were more likely to use negotiated drugs (β=2.322, P < 0.001). In addition, patients with higher outpatient medical expenses negotiated a larger amount of drug use (β=3901.391, P < 0.001).

    Table 2 Influence Factors of Outpatient Negotiated Drug Usage and Expenditure-Two Part Model

    The results in Table 3 show that age, gender, type of medical insurance, LOS and THE all affect whether patients use negotiated drugs in hospitalization. Compared with men, female patients were less likely to use negotiated drugs during hospitalization (β=−0.545, P < 0.05). Compared patients with UERMI, patients covered by URRBMI used less negotiated drugs (β=−0.245, P < 0.01). Patients with more hospital days were less likely to use negotiated drugs (β=−0.122, P < 0.001). Patients with higher DTR were more likely to use negotiated drugs (β=0.037, P < 0.001). The higher the proportion of drugs, the higher the amount of negotiated drugs (β=0.041, P < 0.01).

    Table 3 Influence Factors of Inpatient Negotiated Drug Usage and Expenditure-Two Part Model

    The matching results of propensity score showed that the use of negotiated drugs had no significant effect on the treatment outcome of hospitalized patients with malignant tumors, and the P-value was not significant at the level of 0.05. Different matching methods were used to verify the robustness of the study results (Table 4).

    Table 4 Effect of Negotiating Drug Use on Treatment Outcomes in Patients with Gastric Cancer – PSM Model

    Discussion

    This study investigated the utilization of anticancer medicines after NRDLN policy based on data of gastric cancer patients in three sample cities. We found that compared with the high usage of negotiated anticancer drugs in inpatients, patients in outpatient rarely use such high-value drugs. Age, sex, type of insurance and medical costs have different effects on whether outpatient and inpatient drugs are used and the corresponding drug costs. In the short term, the use of negotiated drugs was not found to affect treatment outcomes in patients with gastric cancer.

    We identified that the use of negotiated drugs in patients with gastric cancer during outpatient treatment is very limited, and there was a substantial difference in total costs between outpatient and inpatient care. Compared with hospital admissions, which receive higher reimbursement rates, outpatient visits usually mean high out-of-pocket costs.29 Therefore, gastric cancer patients tend to allocate the use of innovative drugs (which account for a higher proportion of expenses) and other treatment items to inpatient care, while spending less during outpatient visits. Patients aged 61–75 and over 75 years were more likely to use negotiated drugs. Epidemiological literature shows that the incidence of gastric cancer in China increases with age,30,31 this implies that the release of the national negotiated drug list benefits patient age groups with higher incidence risks.32 However, as the “over 6” age group retires, they become more price-sensitive and have lower willingness to pay for new high-price drugs,33 while working-age gastric cancer patients are willing to incur more medical expenditure for their health. Differentiated reimbursement policies force patients to choose more expensive cancer drugs in the hospital.

    For inpatient treatment, working-age patients were more likely to taking negotiated anticancer drugs be compared with elders. It is easy to understand that working age patients who tend to have higher incomes and a stronger willingness to treat, have better access to health information and are able to track the latest drug negotiations published by the state.34,35 As the LOS increases, the likelihood of hospitalized patients using negotiated drugs decreases, possibly for the longer LOS tend to mean higher medical costs, and hospitalized patients may reduce the use of costly negotiated drugs when medical expenditures are considered, while current research efforts tend to separately assess the utilization of anticancer medications and LOS among patients with malignant tumors.36,37 Moreover, patients who had highest THE were more willing to take negotiate drugs. Those patients often possess a greater ability to pay, and the utilization of high-priced negotiated medications inevitably leads to an increase in THE, thereby forming a bidirectional influence. Patients taking national negotiated anticancer drugs also used adjuvant medications, including gastric and hepatic protectants, as well as traditional Chinese patent medicines. The DTR serves as an intriguing indicator, often employed by health regulatory authorities to monitor hospitals amidst the backdrop of drug abuse. Hospitalized patients with a higher DTR are more likely to utilize negotiated drugs, even after these drugs have undergone national drug negotiation processes, as their prices remain exorbitant, further elevating the DTR.

    Notably, the utilization of negotiated drugs during outpatient and inpatient care is significantly influenced by the various types of medical insurance schemes. In our study, patients supported by UEBMI will pay more for inpatient treatment than those supported by URRBMI. Similar finding has been reported from Yin.38 The disparity in insurance funding amount results in a significantly higher reimbursement ratio for UEBMI compared to URRBMI.39 In respect to financial benefits, both insurance schemes emphasize cost-sharing mechanisms for enrollees, incorporating intricate regulations pertaining to deductibles, copayments, and reimbursement ceilings. But the financial benefits conferred by UEBMI surpass those offered by URRBMI.40

    After delving into a myriad of factors influencing the utilization of negotiated drugs, we intriguingly observe that there is no compelling evidence to suggest that the adoption of newly negotiated drugs leads to marked improvements in treatment outcomes. The majority of these negotiated drugs are recent market entrants, having been launched within the past two years. Despite the favorable pharmacoeconomic reports submitted, which attest to their efficacy, there remains a dearth of large-scale clinical utilization data. Furthermore, patients in the control group are often treated with first- or second-line conventional anticancer medications, resulting in a non-significant divergence in treatment outcomes within a short timeframe. The study conducted a Health Technology Assessment (HTA) on a subset of the drugs negotiated in 2019, revealing that more efficacious targeted anticancer drugs do not necessarily yield higher negotiation prices.41 Study highlighted that the price of anticancer drugs does not necessarily reflect their therapeutic efficacy in Italy.42

    In order to effectively facilitate the implementation of negotiated drug access, the Chinese government has established a “dual-channel” drug supply system encompassing medical institutions and retail pharmacies.43 Regarding diseases undergoing payment reforms such as Diagnosis-Related Groups (DRGs), the weight of these diseases is promptly and reasonably adjusted based on the actual utilization of negotiated drugs.44 We still aspire to further alleviate the economic burden of malignancy patients through means such as commercial medical insurance and medical assistance. Additionally, there is a need to collect clinical usage data, employing real-world evidence to dynamically conduct drug price negotiations.45

    The present study is subject to the following potential limitations: Firstly, the measurement of treatment outcomes relies on the discharge status recorded in the hospital inpatient system, which has been noted to potentially introduce bias. Physicians tend to favor positive outcomes when filling in these records, while conditions such as mortality are often underestimated. Secondly, constrained by data collection limitations, our analysis focuses solely on the utilization of negotiated drugs among hospital patients in selected regions, neglecting the consumption patterns in designated retail pharmacies. While this component of consumption data may constitute a relatively small proportion, its exclusion nonetheless compromises the comprehensiveness of our data analysis. Thirdly, there is no outpatients from Xi’an, making the sample less representative, and the study timeframe (2018–2020) is likely too short to capture meaningful clinical outcomes in oncology. Consequently, this represents an area for further investigation in our subsequent research endeavors.

    Conclusion

    This study evaluated the utilization of negotiated drugs by gastric cancer patients during outpatient and inpatient treatments following the implementation of the national drug negotiation policy, along with the associated influencing factors. Our findings revealed that outpatient patients exhibited limited utilization of negotiated drugs due to constraints imposed by the modest reimbursement rates and ceiling limits of medical insurance. Factors such as the type of medical insurance, LOS, and DTR significantly influenced the use of drugs among inpatients. Notably, the short-term use of negotiated drugs did not demonstrate an impact on treatment outcomes, indicating the necessity of extending the follow-up period for cancer patients and improving clinical efficacy assessment indicators. Consequently, there is a pressing need for more comprehensive insurance coverage, such as increasing the reimbursement ratio for negotiated drugs in commercial insurance, and adopting more HTA studies based on real-world data as the basis for medical insurance payment standards, so as to jointly improve drug accessibility and affordability.

    Ethics

    Ethics approval for this study was obtained from Tongji hospital (Ethics project number: TJ-IRB20191219), and the data was obtained from the hospital with its permission and anonymized before export. To protect the privacy of the sample data, patient identification IDs and other identifying information are removed in data collection. All data involving human participants were in accordance with the 1964 Helsinki Declaration.

    Author Contributions

    Bingbing Tuo: Writing-review & editing, Visualization, Validation, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. Haokai Zhao: Writing-review & editing, Methodology, Investigation, Formal analysis, Conceptualization. Anxin Hu: Writing-review & editing, Methodology, Investigation. Junnan Jiang: Writing-review & editing, Visualization, Validation, Project administration, Methodology, Investigation, Formal analysis, Funding acquisition, Data curation, Conceptualization.

    All authors 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 study was funded by the National Natural Science Foundation of China (No.72404284), the Natural Science Foundation of Hubei Province (2024AFB422) and the Fundamental Research Funds for the Central Universities, Zhongnan University of Economics and Law, “Study on the coordination and integration mechanism of global budget on the integration of medical care and prevention of county medical alliance from the perspective of holistic governance” (2722024BQ054).

    Disclosure

    The authors declare no conflict of interest.

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  • Development and Validation of a Diagnostic Nomogram Model for Predicti

    Development and Validation of a Diagnostic Nomogram Model for Predicti

    Background

    The global demographic landscape is undergoing a significant transformation, marked by a rapid increase in the older adult population. Projections indicate that by 2050, the number of individuals aged 60 and older will double.1 This aging trend is closely linked to the rise of various geriatric syndromes, which, when coupled with cardiovascular diseases (CVDs), lead to a progressive and accelerated deterioration in patient health.2 Among these syndromes, frailty and cognitive impairment (CI) are particularly consequential in older adults with CVDs. Research has shown that the concurrent development of frailty and CI significantly elevates the risk of major adverse cardiovascular events compared to the development of either condition alone.3 In 2013, the International Academy of Nutrition and Aging and the International Association of Gerontology and Geriatrics introduced the concept of “cognitive frailty” (CF) to describe the co-occurrence of physical frailty and mild cognitive impairment, as indicated by a Clinical Dementia Rating of 0.5, in older adults who do not meet the criteria for a definitive dementia diagnosis, excluding other dimensions of frailty, such as social, psychological, and oral frailty.4

    Acute coronary syndrome (ACS) is a more severe form of coronary heart disease (CHD) with a worse prognosis, particularly among patients aged 65 and older. The negative prognostic impact of frailty or CI in patients with ACS has been well-documented.5 For instance, a study involving 2,041 patients aged 75 and older hospitalized with acute myocardial infarction (MI) revealed that 17% had CI, which was associated with higher risks of readmission and mortality.6 Moreover, moderate-to-severe CI was linked to an even greater risk of death.6 However, the specific impact of CF on ACS prognosis remains underexplored.7,8 Mone P et al investigated the 5-year cardiovascular outcomes in older adults without prior coronary artery disease, categorizing participants based on the progression of frailty and CI. They found that the group classified as having CF exhibited the highest risk of experiencing major adverse cardiovascular events, followed by individuals who developed frailty or CI first.9 Elderly ACS patients with CF experienced significantly higher rates of both in-hospital (including longer hospital stay, bleeding, ventricular arrhythmia, and a higher incidence of cardiogenic shock) and 6-month complications (including MI, stroke, Recurrent revascularization, and death).10 These findings indicate that CF increases the risk of adverse cardiovascular events. Moreover, CF might affect treatment adherence and the adoption of secondary prevention behaviors post-ACS.

    Assessing CF is challenging, given the increasing prevalence of ACS in the aging population. This assessment often involves tools like the Frail Score, which evaluates physical frailty based on several criteria, such as weight loss, exhaustion, and mobility, and the Mini-Mental State Examination (MMSE), which assesses the level of cognitive impairment based on 11 metrics, including orientation, memory, and attention. The existing diagnostic approaches for CF are complex, hindering effective diagnosis and prevention. Nomograms are simple yet effective visual tools for risk prediction that provide a solution. By integrating multiple factors into a statistical model, these tools estimate event risks, making them valuable for both cross-sectional and prospective studies in predicting disease risks.11 This study aims to develop a nomogram-based risk prediction model that quantifies the likelihood of CF in patients with ACS, enabling early identification of high-risk elderly patients for targeted personalized prevention and treatment strategies to delay or prevent CF progression.12

    Methods

    Participants

    This was a prospective observational single-center study conducted at Beijing Friendship Hospital in China. We prospectively recruited 1,267 participants aged over 65 years who were admitted to ACS from January 2020 to April 2022. The inclusion criteria were as follows: 1) elderly participants aged ≥ 65 years; 2) a primary diagnosis of ACS, including ST-Elevation MI (STEMI) and Non-ST-Elevation Acute Coronary Syndrome (NSTE-ACS); and 3) provided signed informed consent. Patients were excluded if they met any of the following criteria: 1) MI caused by other acute disease; 2) severe dementia or schizophrenia that prevented cooperation in completing the Comprehensive Geriatric Assessment; 3) severe liver dysfunction, kidney disease, or end-stage malignant tumors; or 4) totally disabled and bedridden.

    According to the pre-established inclusion and exclusion criteria, we initially excluded 221 participants who were not diagnosed with ACS at discharge. Additionally, we excluded 185 participants who had severe comorbidities or refused to complete a frailty assessment and 314 patients who had not completed the MMSE. In the end, a total of 547 patients with frailty who completed the MMSE assessment were included in the study (Figure 1).

    Figure 1 Flowchart of the recruitment process for the study population.

    Abbreviations: ACS, acute coronary syndrome; MMSE, mini-mental state examination; n, number of participants in the study.

    All participants provided informed consent, and the study received approval from the Ethics Committee of Beijing Friendship Hospital. The study was registered on ClinicalTrials.gov under the identifier NCT04580706 on March 26, 2024.

    Data Collection

    Data were prospectively collected by investigators before discharge using standardized case report forms to ensure consistency and reliability. The systematically recorded information included demographic data, baseline clinical characteristics, detailed medical history, dietary habits, comorbidities, electrocardiogram results, laboratory tests, echocardiographic findings, coronary angiographic data, treatment modalities, and duration of hospital stay. Global Registry of Acute Cardiac Events (GRACE) risk scores were calculated to estimate in-hospital and out-of-hospital mortality risk.

    Cardiovascular outcomes, including major adverse cardiac events (MACE), were monitored during hospitalization. MACE was defined as recurrent myocardial ischemia, unplanned revascularization, all-cause death, and recurrent arrhythmia.

    Assessment of Frailty and Cognitive Function

    Trained personnel conducted assessments to evaluate physical frailty and cognitive impairment at the time of admission. For the assessment of physical frailty, the FRAIL Scale was utilized. This widely recognized five-item questionnaire evaluates the following domains: fatigue, resistance, ambulation, illness, and loss of weight. Each item is scored as 0 (indicating the absence of the characteristic) or 1 (indicating the presence of the characteristic).13 The scoring system categorizes individuals based on their level of frailty: a total score ranging from 1 to 2 represents pre-frailty, indicating that the individual may be at risk for further decline in health. In contrast, a total score of 3 or higher signifies frailty, which is associated with increased vulnerability and a higher risk of adverse health outcomes.

    Cognitive function was evaluated using the MMSE, which is designed to evaluate various aspects of cognitive ability. The MMSE consists of 11 items that are categorized into five domains, each contributing to the overall score: orientation (10 points), memory registration (3 points), attention and calculation (5 points), recall (3 points), and language (10 points). The total score on the MMSE ranges from 0 to 30, with higher scores indicating better cognitive function. A cutoff score of 27 has been established for identifying cognitive impairment, particularly in populations with higher educational attainment. This suggests that individuals scoring below this threshold may exhibit signs of cognitive decline or impairment.14

    Comprehensive Geriatric Assessment

    This assessment was conducted by two trained medical staff members at the time of admission and included evaluations of comorbidities, functional status, lower extremity function, and nutritional risk. Functional status was assessed using the activities of daily living (ADL) Scale, which measures basic self-care abilities, such as bathing, dressing, and feeding, as well as the Instrumental ADL (IADL) Scale, which assesses complex activities necessary for independent living, including managing finances, preparing meals, and transportation. Lower extremity function was evaluated through the Short Physical Performance Battery (SPPB) test, which evaluates standing balance (0 to 4 points), gait speed (0 to 4 points), and chair stands (0 to 4 points).

    Nutritional risk was screened using the Mini Nutritional Assessment-Short Form, which incorporates anthropometric measurements, dietary intake evaluations, and subjective assessments of the individual’s nutritional status. All assessments were performed at the time of hospital discharge to facilitate appropriate follow-up care and interventions.

    Statistical Analysis

    All data were analyzed using SPSS version 25.0 and R version 4.4.1. Patient characteristics are presented as the mean±standard deviation (x±SD), median (interquartile range) [M (Q1, Q3)], or percentages (%). The Pearson’s χ2 test was used to assess associations between selected factors and CF status.

    The dataset, comprising a total of 547 participants, was divided into training and validation cohorts using stratified sampling at a 7:3 ratio by CF status, resulting in 382 participants in the training cohort and 165 in the validation cohort. Logistic regression analysis was conducted to identify predictive risk factors for CF within the training cohort. Significant risk factors were then used to construct a nomogram, with the length of each line representing the relative influence of the variable on CF outcomes.

    The model’s discrimination ability was evaluated using the receiver operating characteristic (ROC) curve, while calibration was assessed via the calibration curve. Decision curve analysis (DCA) was employed to determine the clinical utility and net benefits of the model.

    Results

    Baseline Characteristics of the Study Population

    Of the 547 patients enrolled, the mean age was 71 years, and 42.2% of the study population was female. The average years of education received was 9 year and the average body mass index (BMI) was 25.0 kg/m2. Approximately 81.7% of the study population was living with hypertension, and 41.9% had diabetes. Among these participants, 462(84.5%) were diagnosed with unstable angina pectoris (UAP), with a non-ST elevated MI (NSTEMI) of 55(10.1%) and ST elevated MI (STEMI) of 30(5.5%). The majority of this older population had multiple chronic conditions, and 6.1% of the cohort had four or more chronic commodities. Additionally, 248 (45.34%) patients were classified as pre-frail, and 50(9.14%) patients were identified as having physical frailty according to the FRAIL Scale.

    The overall prevalence of CF was 82(14%), with pre-frailty and frailty prevalence of 50.42% and cognitive impairment prevalence of 126 (23%). Full characteristics of the study population are shown in Table 1. Patients who had CF were older, more likely to be women, and less educated as compared to non-CF (NCF) patients. Compared to NCF subjects, subjects with CF had slightly higher systolic blood pressure (SBP) (139 [129,153] vs 133(122,144], P<0.001), significantly lower hemoglobin (Hgb) (123[115–136] vs 132[122,142] g/dL, P<0.001) and ALB (37[35,40] vs 38[36,40])g/dL, P=0.007), a significantly higher level of D-dimer (0.5[0.4,0.9] vs 0.4[0.3,0.6] ng/dL, P<0.001).

    Table 1 Characteristics of ACS Patients with and Without CF

    CF patients also had a higher prevalence of NSTEMI (19.5%) compared to NCF patients. The overall number of chronic comorbidity conditions was also higher among CF patients, with approximately 40% reporting two or more chronic medical conditions. Patients with CF had poorer cardiac function (65.8% vs 42.8%, P<0.001), higher GRACE scores (125 [112–141] vs 118[10–5,128], P<0.001). The estimated high risk of mortality, both in-hospital(26.8% vs 11.6%, P<0.001) and out-hospital (64.6% vs 49.2%, P<0.001), were much higher in CF patients. The mean length of hospital stay was 5 days, and the incidence of in-hospital MACE was 1.6%. There was no significant difference in the number of lesions or MACE.

    When evaluating measures of disability, including self-care, mobility disability, and household activities disability, patients with CF had poorer activity including ADL and IADL scores. Compared with NCF patients, the lower extremity function and mobility were poorer in patients with CF of lower SPPB scores (7 vs 10, P<0.001), and step speed of 4 m (0.6[0.5,0.8] vs 0.8[0.7,1.0]s, P<0.001). The incidence of malnutrition in the CF group was as high as 28.05%, which was higher than that observed in the NCF group. Furthermore, patients with CF consumed fewer carbohydrates and nuts of their dietary habit (Table 2).

    Table 2 The Relationship Between Cognitive Frailty, Nutrition, and Diet

    Baseline Characteristics of Patients in Training Group and Validation Group

    The laboratory and clinical data of the training and validation sets are presented in Table 3. Notably, the only significant difference between the training and testing sets was observed in SBP levels (P<0.05). Other clinical indicators did not exhibit significant differences between the two groups.

    Table 3 Baseline Characteristics of the Training Set and Validation Set

    Derivation of the Predictive Factors in the Training Set

    Univariate analysis identified years of age, sex education, income, SBP, Hgb, CCI>4, GRACE score, ADL, IADL scores, SPPB, and malnutrition were significantly associated with cognitive impairment. In multivariate regression analysis, age (1.130; 95% CI, 1.03–21.242), education (0.798, 95% CI, 0.68–90.915), SBP (1.034, 95% CI, 1.008–1.062), CCI>4 (2.275, 95% CI 1.167–4.400), SPPB (0.832, 95% CI, 0.713–0.973) and malnutrition (0.179, 95% CI, 0.072–0.434) were independently associated with CF (see Table 4). Older patients with higher SBP and CCI were more likely to have CF, while education and SPPB were identified as protective factors against cognitive frailty.

    Table 4 Potential Risk Factors Identified by Univariate and Multivariate Logistic Regression Analysis in the Training Group

    Establishment of the Diagnostic Nomogram Model

    The nomogram for CF was developed based on all the independent significant factors in the training set (Figure 2). For each independent variable, corresponding values were obtained by drawing vertical lines to the scoring scale at the top of the nomogram, which ranges from 0–100. The scores for each variable were then summed to obtain the total score, which was used to find the corresponding predicted probability values on the prediction line at the bottom of the monogram’s column graph. For a 76-year old patient with 9 years of education, a SBP of 140 mmHg, a CCI of 3, malnutrition, and a SPPB of 4, the total score was 204, indicating a greater than 81% probability of CF. It is recommended that this patient receive prevention measurement.

    Figure 2 Nomogram for predicting CF based on the training cohort (n=382).

    Abbreviations: Education, years of education; Age, the number of years; SBP, systolic blood pressure; CCI, Charlson Comorbidity Index (1, CCI of 0–1; 2, CCI of 2–3; 3, CCI of more than 3); CF, cognitive frailty; SPPB, score on the Short Physical Performance Battery assessment; MNA-SF, Mini Nutritional Assessment Short Form (1, malnutrition, 2, risk of malnutrition).

    Differentiation, Calibration, and Clinical Applicability of the Diagnostic Nomogram Model

    To validate the efficacy of our nomogram model, we employed ROC analysis. The AUC values for the CF nomogram were 0.854 (95% CI, 0.741–0.861) in the training cohort and 0.733 (95% CI, 0.500–0.898) in the validation cohort, indicating a good ability to discriminate between patients with and without CF (Figure 3). However, the wide CI in the validation cohort suggests potential instability, which may be attributed to a smaller sample size and heterogeneity.

    Figure 3 ROC curves of the nomogram for predicting CF in the training (A) n=382 and testing (B) n=165 sets.

    Abbreviations: AUC, area under the curve; CF, cognitive frailty; n, number of participants in the study; ROC, receiver operating characteristic.

    The calibration of the nomogram was assessed using the calibration curve (Figure 4), which showed agreement between the observed and predicted values, with absolute errors of 0.01 and 0.03 in the training and testing sets, respectively, indicating that there was no deviation from the perfect fit.

    Figure 4 Calibration curves for predicting CF in the training (A) n=382 and validation (B) n=165 sets.

    Abbreviations: CF, cognitive frailty; n, number of participants in the study.

    DCA was conducted for the prediction nomogram (Figure 5). The results for both the training and testing sets indicate that the nomogram is a promising tool for predicting CF.

    Figure 5 Decision curves for the proposed nomogram model in the training (A) n=382 and testing (B) n=165 sets.

    Abbreviations: n, number of participants in the study; Nomo, nomogram.

    Discussion

    CF presents significant challenges for patients with ACS, their caregivers, and clinicians due to atypical symptoms and a heightened risk of complications. This study explored the prevalence and characteristics of CF in ACS patients and developed a predictive nomogram model. Key findings include: 1) Approximately 15% of ACS patients exhibited CF, as assessed by the FRAIL Scale and MMSE. These patients were typically older, female, less educated, economically disadvantaged, and had higher SBP and glucose levels. 2) Patients with CF had a higher prevalence of multiple chronic conditions and more severe health statuses. They showed a greater incidence of NSTEMI, cardiac dysfunction, baseline disability, and higher GRACE scores compared to non-cognitive frail participants. 3) CF patients had poorer nutrition, as indicated by lower hemoglobin (Hgb) and albumin (Alb) levels, and consumed fewer carbohydrates and nuts in their diet. 4) Education, age, SBP, CCI, SPPB scores, and nutritional status were identified as independent predictors of CF. A diagnostic nomogram incorporating these factors demonstrated good accuracy and discrimination in predicting CF.

    CF is notably prevalent among post-ACS patients, particularly in older adults with a mean age of 71 years (range 68–75). The condition is associated with advancing age, lower educational attainment, female gender, reduced income, elevated blood pressure, and higher glucose levels. Cognitive impairment, frailty, and CVD share common risk factors such as diabetes, hypertension, obesity, and smoking, as well as pathophysiological pathways like systemic inflammation, oxidative stress, and neuroendocrine dysregulation. In this study, CF patients exhibited higher SBP and glucose levels, along with a greater incidence of comorbidities. The relationship between CF and CVD is complex and bidirectional. CVD can lead to CF through the role of atherosclerosis in the pathogenesis of cerebral small vessel disease, while CF can exacerbate the progression of CVD, worsening prognosis through mechanisms such as reduced treatment compliance.8,15–17

    In our study, patients with NSTEMI were more likely to experience CF. Pasquale Mone et al explored the relationship between physical and cognitive dysfunction in frail STEMI patients, finding a significant correlation between gait speed and MMSE scores (r: 0.771; p < 0.001).9 Similarly, Valerie Josephine et al studied 239 NSTEMI patients with a median age of 80.9 years, revealing that 82% were pre-frail or frail, and 39.7% had CF18. Richardson et al linked MI to brain microinfarcts in postmortem studies, suggesting that small vessel disease may contribute to cognitive decline.19

    Although CF status was not associated with the number of lesion branches, CF patients had higher GRACE scores, reflecting factors such as SBP and kidney function, and were at greater risk both during and after hospitalization. Current European Society of Cardiology guidelines for ACS management lack specific recommendations for elderly patients, particularly considering frailty and cognitive impairment, likely due to their exclusion from major clinical trials.20 Our findings highlight a strong link between CF and cardiac dysfunction. While no significant difference in in-hospital MACE was observed, likely due to short hospital stays (5 days), studies like Cammalleri’s show that ACS patients with severe cognitive and functional impairments face the highest 6-month mortality rates.21 Similarly, Hajduk et al’s multicenter study of more than 3,000 elderly ACS patients (mean age 82 years) found that moderate to severe cognitive impairment was associated with increased 6-month post-discharge mortality.6

    This study highlights a link between nutrition and CF, with lower Hgb and ALB levels observed in affected individuals. Malnutrition, characterized by imbalances in calories, protein, and other nutrients, significantly impacts body composition, physical function, and overall health.22 Inadequate intake of carbohydrates and nuts was also identified as a predictor of CF. Carbohydrates are a primary energy source, and insufficient consumption can lead to malnutrition and weight loss, which are critical factors in CF development among older adults. Notably, 58.33% of participants in this study reported no nut consumption. Nuts, a globally recommended food rich in protein, healthy fats, and satiety-promoting properties, have been associated with a reduced risk of chronic conditions, including CVD.23,24 Further mechanistic studies are needed to explore causal relationships involved.

    For clinicians, a cost-effective and simplified method for rapidly predicting CF is highly valuable. In this study, we identified education, age, SBP, CCI, SPPB scores, and nutritional status as predictive indicators of CF. These factors were used to develop a nomogram model, which demonstrated strong predictive accuracy, with an AUC of 0.854 for the training cohort and 0.733 for the validation cohort. Since these variables can be easily obtained through routine assessments, the nomogram could be utilized at the time of admission for patients with ACS to identify those with CF. Additionally, it is practical for both regular evaluation and ongoing monitoring.

    The current research has several limitations. First, although the data were of high quality, they were collected from a single center in China, potentially restricting the generalizability of the findings for the geographic constraints and heterogeneity. Second, CF was assessed using MMSE and Frail scores, which introduced variability due to differences in screening tools, cut-off values, and measurement time points. Third, although the nomogram model demonstrated good predictive accuracy in the study, it remains uncertain whether its performance might differ in populations with higher educational attainment or varying prevalence of frailty. Lastly, the conclusions are primarily based on baseline data analysis and in-hospital follow-up. Future long-time follow-up assessments are planned to address these limitations.

    Conclusions

    The present study demonstrates that in elderly patients with ACS, the coexistence of frailty and cognitive impairment is frequent and is associated with age, female, less educated, worse economic, higher SBP, and glucose. Patients with CF were more likely to have worse cardiac function and malnutrition. Intaking more carbohydrates and nuts will improve nutrition, thereby alleviating CF. This study explored a simple and practical nomogram for providing patients with an early warning about the risk of hypertension based on the associated risk factors.

    Abbreviations

    CF, Cognitive frailty; ACS, acute coronary syndrome; ROC, receiver operating characteristic; DCA, decision curve analysis; SBP, systolic blood pressure; CCI, Charlson Comorbidity Index; SPPB, Short Physical Performance Battery; CVDs, cardiovascular diseases; CI, cognitive impairment; MMSE, Mini-Mental State Examination; STEMI, ST-Elevation myocardial infarction; NSTEMI, non-ST elevated myocardial infarction; NSTE-ACS, Non-ST-Elevation Acute Coronary Syndrome; GRACE, Global Registry of Acute Cardiac Events; MACE, major adverse cardiac events; ADL, activities of daily living; IADL, Instrumental activities of daily living; SPPB, Short Physical Performance Battery; BMI, body mass index; CHO, cholesterol; Cr, creatinine; DBP, diastolic blood pressure; HbA1c, hemoglobin A1c; HDL, high-density lipoprotein; Hgb, hemoglobin; LDL, low-density lipoprotein; TG, triglycerides; UAP, unstable angina pectoris; AUC, area under the curve.

    Human Ethics Approval and Consent to Participate

    The study protocol was approved by the Ethics Committee for Clinical Research of Beijing Friendship Hospital before the performance of the analyses (code: 2022-P2-045-01). All procedures involving human participants were performed in accordance with the ethical standards of the Ethics Committee for Clinical Research of Beijing Friendship Hospital and with the Declaration of Helsinki and its later amendments.

    Acknowledgments

    We are grateful to all participating people and their families. We acknowledge all staffs for their great contributions to the success of the program.

    Funding

    This study was supported by grants from National Science and Technology Major Project (2021ZD0111000).

    Disclosure

    The authors declare that they have no competing interests.

    References

    1. Ageing and Health. World Health Organization; 2022.

    2. Damluji AA, Forman DE, Wang TY, et al. Management of acute coronary syndrome in the older adult population: a scientific statement from the American Heart Association. Circulation. 2023;147(3):e32–e62. doi:10.1161/CIR.0000000000001112

    3. Damluji AA, Ijaz N, Chung S-E, et al. Hierarchical development of physical frailty and cognitive impairment and their association with incident cardiovascular disease. JACC Adv. 2023;2:100318. doi:10.1016/j.jacadv.2023.100318

    4. Kelaiditi E, Cesari M, Canevelli M, et al. Cognitive frailty: rational and definition from an (I.A.N.A./I.A.G.G.) international consensus group. J Nutr Health Aging. 2013;17:726–734. doi:10.1007/s12603-013-0367-2

    5. Sugimoto T, Arai H, Sakurai T. An update on cognitive frailty: its definition, impact, associated factors and underlying mechanisms, and interventions. Geriatr Gerontol Int. 2022;22(2):99–109. doi:10.1111/ggi.14322

    6. Hajduk AM, Saczynski JS, Tsang S, et al. Presentation, treatment, and outcomes of older adults hospitalized for acute myocardial infarction according to cognitive status: the SILVER-AMI study. Am J Med. 2021;134:910–917. doi:10.1016/j.amjmed.2021.03.003

    7. Newman MF, Kirchner JL, Phillips-Bute B; Neurological Outcome Research Group and the Cardiothoracic Anesthesiology Research Endeavors Investigators, et al. Longitudinal assessment of neurocognitive function after coronary-artery bypass surgery. N Engl J Med. 344;2001:395–402. doi:10.1056/NEJM200102083440601

    8. Ijaz N, Jamil Y, Brown CH, et al. Role of cognitive frailty in older adults with cardiovascular disease. J Am Heart Assoc. 2024;13(4):e033594. doi:10.1161/JAHA.123.033594

    9. Mone P, Gambardella J, Pansini A, et al. Cognitive dysfunction correlates with physical impairment in frail patients with acute myocardial infarction. Aging Clin Exp Res. 2022;34(1):49–53. doi:10.1007/s40520-021-01897-w

    10. Wontor R, Lisiak M, Łoboz-rudnicka M, et al. The impact of the coexistence of frailty syndrome and cognitive impairment on early and midterm complications in older patients with acute coronary syndromes. J Clin Med. 2024;13(23):7408. doi:10.3390/jcm13237408

    11. Islam M, Alam J, Kumar S, et al. Development and validation of a nomogram model for predicting the risk of hypertension in Bangladesh. Heliyon. 2024;10(22):e40246. doi:10.1016/j.heliyon.2024.e40246

    12. Tian R, Chang L, Zhang Y, Zhang H. Development and validation of a nomogram model for predicting low muscle mass in patients undergoing hemodialysis. Ren Fail. 2023;45(1):2231097. doi:10.1080/0886022X.2023.2231097

    13. Dent E, Kowal P, Hoogendijk EO. Frailty measurement in research and clinical practice: a review. Eur J Intern Med. 2016;31:3–10. doi:10.1016/j.ejim.2016.03.007

    14. O’Bryant SE, Humphreys JD, Smith GE, et al. Detecting dementia with the mini-mental state examination in highly educated individuals. Arch Neurol. 2008;65(7):963–967. doi:10.1001/archneur.65.7.963

    15. Bucur B, Madden DJ. Effects of adult age and blood pressure on executive function and speed of processing. Exp Aging Res. 2010;36:153–168. doi:10.1080/03610731003613482

    16. Baker AB, Resch JA, Loewenson RB. Hypertension and cerebral atherosclerosis. Circulation. 1969;39:701–710. doi:10.1161/01.CIR.39.5.701

    17. Piotrowicz K, Klich‐Raczka A, Skalska A, Gryglewska B, Grodzicki T, Gasowski J. Pulse wave velocity and sarcopenia in older persons‐a systematic review and meta‐analysis. Int J Environ Res Public Health. 2022;19:19. doi:10.3390/ijerph19116477

    18. Dirjayanto VJ, Alkhalil M, Dodson J, et al. Cognitive impairment and outcomes in older adults with non-ST-elevation acute coronary syndrome. Heart. 2024;110(6):416–424. doi:10.1136/heartjnl-2023-323224

    19. Richardson K, Stephan BCM, Ince PG, et al. The neuropathology of vascular disease in the medical research council cognitive function and ageing study (MRC CFAS). Curr Alzheimer Res. 2012;9:687–696. doi:10.2174/156720512801322654

    20. Byrne AR, Rossello X, Coughlan JJ, et al. 2023 ESC guidelines for the management of acute coronary syndromes: developed by the task force on the management of acute coronary syndromes of the European Society of Cardiology (ESC). Eur Heart J. 2023;44:3720–3826. doi:10.1093/eurheartj/ehad191

    21. Cammalleri V, Bonanni M, Bueti FM, et al. Multidimensional Prognostic Index (MPI) in elderly patients with acute myocardial infarction. Aging Clin Exp Res. 2021;33:1875–1883. doi:10.1007/s40520-020-01718-6

    22. Kim H, Awata S, Watanabe Y, et al. Cognitive frailty in community dwelling older Japanese people: prevalence and its association with falls. Geriatr Gerontol Int. 2019;19:647–653. doi:10.1111/ggi.13685

    23. Becerra-Tomás N, Paz-Graniel I, Kendall CWC, et al. Nut consumption and incidence of cardiovascular diseases and cardiovascular disease mortality: a meta-analysis of prospective cohort studies. Nutr Rev. 2019;77:691–709. doi:10.1093/nutrit/nuz042

    24. Tran G, Brown RC, Neale EP. Perceptions of nut consumption amongst Australian Nutrition and Health Professionals: an online survey. Nutrients. 2022;14(8):1660. doi:10.3390/nu14081660

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  • Are You Asking These Seven Sexual Health Questions?

    Are You Asking These Seven Sexual Health Questions?

    At the 2025 Argentine Society of Infectious Diseases (SADI) Congress, held June 12-14 in Mar del Plata, Argentina, updated guidelines for the diagnosis and treatment of sexually transmitted infections (STIs) were presented. The chapter, developed by the HIV and STI Commission on a comprehensive approach to sexual health, offers step-by-step recommendations for taking a sexual history, designed for both specialist and primary care clinicians.

    Romina Mauas, MD, one of the chapter’s authors, is an outpatient physician at Hospital de Infecciosas F.J. Muñiz and a researcher at the Center for Studies for the Prevention and Control of Communicable Diseases at ISALUD University, Buenos Aires, Argentina.

    “This content is entirely new. This highlights the key questions that should never be missed when taking a medical history. It also promotes an inclusive, respectful environment free from stigma, prejudice, or moral judgment while protecting privacy, confidentiality, and individual rights,” she said.

    The chapter was co-authored with José Barletta, MD; Franco Bova, MD; Iael Altclas, MD; Adriana Basombrío, MD; Luciana Spadaccini, MD; Mara Huberman, MD; and Sergio Maulen, MD, PhD, all of whom are medical professionals.

    “This material hasn’t been available before, isn’t covered in other guidelines, and can benefit any healthcare professional in the region,” said Alejandra Cuello, speaking with Medscape Spanish. She was one of the two coordinators of the recommendations. Cuello heads the Infectious Diseases Service at the Juan D. Perón Regional Polyclinic and was an adjunct professor of infectious diseases at the National University of Villa Mercedes, both in Villa Mercedes, Argentina.

    The new guide included 21 chapters covering a wide range of topics, including urethritis, acquired syphilis, genital herpes, human papillomavirus, viral hepatitis, gonorrhea, Zika virus, sexual abuse and rape, STIs in pregnant women, and emerging STIs, such as mpox.

    “Instead of just copying the international guidelines, this version includes local epidemiology, available diagnostic methods, and treatments tailored to the regional context,” Cuello said.

    Patient Interaction

    A unique feature of the updated guidelines is that they begin with recommendations on how to explore aspects of a patient’s sexuality during consultations, an area often avoided due to “lack of knowledge, modesty, or discomfort,” Cuello noted.

    Mauas, speaking to Medscape Spanish said, “We need to be warm because we are asking intimate questions. You cannot rush into conversations about sexual practices without creating a comfortable environment. She emphasized that a lack of empathy is often the first barrier to timely and appropriate care.

    These guidelines highlighted the importance of the first interaction in building trust and obtaining the patient’s accurate sexual history. Clinicians are encouraged to pay attention to initial greetings, maintain appropriate eye contact, and use supportive body language.

    “Consultations should begin with open-ended questions. Clinicians are advised to first explore general concerns and then gradually move into more sensitive topics. Each question should be explained clearly using simple and respectful language. The approach should accommodate explicit sexual terms when necessary and be responsive to signs of anxiety or distress,” she said.

    Core Components

    The guidelines outlined seven key areas to consider in sexual health consultations.

    1. Reason for consultation. Begin by understanding the reason for the patient’s visit. Review any signs or symptoms to help guide the examination and diagnostic tests.
    2. History of STIs. Inquiring about a patient’s history of STIs is important, as this can affect the current risk assessment, choice of diagnostic tests, and interpretation of results. “Some people are aware of this; others are not because the infection may have been asymptomatic,” Mauas noted. Assess personal and partner(s) risk perception, including prior testing for HIV, viral hepatitis, and other STIs. Ask whether the patient has received postexposure prophylaxis for HIV, especially in the past 6-12 months.
    3. Sexual partners. Determine the time since the patient’s last sexual contact. When possible, estimate the number of regular and casual partners in the past 3 months or during the 3-month period. Avoid making assumptions about a person’s sexual orientation; instead, ask respectfully. “What is your sexual desire? Do you like being with a woman or a man? What is your orientation? How do you perceive or define yourself?” Mauas explained.
    4. Sexual practices. Gather information about the sites of potential exposure and specific practices, including oral, vaginal (receptive/insertive), and anal (receptive/insertive). Also ask about group sex, transactional sex (in exchange for money, drugs, or services), use of sex toys, dating apps, and recreational drug use — including alcohol and sex-related substances. “These are individual situations that need to be considered,” Mauas emphasized.
    5. STI protection. Ask about the frequency of condom use during vaginal or anal intercourse over the past 3 months. Discuss any barriers to condom use. In addition, the vaccination status for hepatitis A, hepatitis B, and human papillomavirus must be assessed.
    6. Pregnancy prevention. Discuss pregnancy planning, contraceptive use, and access to safe abortion services when relevant. If necessary, refer to the appropriate specialized health departments. “Although it depends on the specialty, we can — and should — work together with the sexual and reproductive or nonreproductive health department, depending on what the patient wants, such as whether they need counseling on contraception,” Mauas said.
    7. Other sexual health issues. Screening for problems related to sexual satisfaction, function, or psychosexual concerns. Ask about experiences of gender-based violence and offer appropriate referrals to the relevant services. These guidelines also encourage clinicians to leave room for patients to raise additional personalized concerns.

    Practical Recommendations

    The guide outlines general recommendations for consultations with key populations and priority groups at a higher risk of STIs, including transgender people, sex workers, men who have sex with men, adolescents and young adults, incarcerated individuals, people who use drugs, and migrant populations.

    The guide offered several recommendations to improve consultations, as follows.

    • Avoid making assumptions about sexual orientation. Ask open, respectful questions about sexual practices, such as the gender of sexual partners, relationship status, and whether the patient is monogamous.
    • Ask about self-identified gender at the beginning of the consultation to avoid mistakes or assumptions regarding sex or gender based on appearance. Gender-neutral languages should be used wherever possible. Ask questions such as, “Are you taking any medication?” instead of “Are you on any medication?”
    • Genital examination should be delayed unless clinically necessary. This can be postponed until a greater level of trust is established.
    • Recognize that not all individuals are sexually active or wish to initiate sexual practices.
    • Offer flexible services to accommodate different needs. For example, evening clinic hours may better serve those with nighttime work schedules.
    • Training the entire healthcare team to promote, inclusive stigma-free care is essential.

    “Anyone who chooses to work in sexual health must be properly trained — not only in clinical knowledge but also in addressing personal biases that may come from cultural or religious beliefs. Primary care providers should familiarize themselves with these guidelines and build their capacity to manage consultations. If they are unable to complete the assessment, they should be referred appropriately; however, they must not become a barrier to care. When a patient feels mistreated due to administrative or bureaucratic hurdles, they often choose not to return,” Mauas said.

    Mauas and Cuello reported having no relevant financial relationship.

    This story was translated from Medscape’s Spanish edition.

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  • From Amanda Anisimova to Alex Michelsen, Meet the rising US tennis stars targeting a dream home debut at LA 2028

    From Amanda Anisimova to Alex Michelsen, Meet the rising US tennis stars targeting a dream home debut at LA 2028

    Alex Michelsen (ATP world no. 30)

    At 6ft 4in (1.93m) and 20-years-old, Alex Michelsen is certainly one of the USA’s tennis talents to watch out for. His 2025 Australian Open run not only completed the set of major main draws, but but also saw him reach the fourth round at Melbourne Park.

    The Aliso Viejo native was close to qualifying for Paris 2024 but just missed out in the rankings, and even though he believes he didn’t quite deserve a spot there, he’s full of hunger to make his Olympic debut on home turf.

    “It would be incredible, it would one of the greatest things that I would get to experience in this life – I thought about it a lot,” Michelsen revealed to Olympics.com. “I really hope I can make the cut. I know all the American guys are going to want to play. It’s in LA, it’s close to my home…I really want to play.”

    Michelsen, an avid gamer, grew up on the Olympic video games as much as the Games themselves. “I played a lot of that in the London 2012 Olympics,” he recalls, “I just did everything. I remember watching the London 2012 Games and Fed [Roger Federer] and [Stan] Wawrinka play Nishikori [Kei] and [Soeda Go] in doubles. It was an absolutely sick match.”

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  • The association between dual sensory impairment and social participation among older adults in China: a moderated mediation model of activities of daily living and depressive symptoms | BMC Geriatrics

    The association between dual sensory impairment and social participation among older adults in China: a moderated mediation model of activities of daily living and depressive symptoms | BMC Geriatrics

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  • India bowler fined after Lord’s incident on Day 4 | ICC World Test Championship

    India bowler fined after Lord’s incident on Day 4 | ICC World Test Championship

    In addition to the fine, one demerit point has been added to Siraj’s disciplinary record, for whom it was the second offence in a 24-month period, taking his tally to two demerit points.

    When a player reaches four or more demerit points within a 24-month period, they are converted into suspension points and a player is banned.

    The moment was one of several fiery moments in a Test match likely to go down to the wire on day five.

    India need just a further 135 runs for victory, though sit precariously at 58/4, up against an imposing bowling attack, a difficult day five Lord’s surface and a boisterous London crowd ready to push their side on.

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  • The Effect of Quercus robur Bark on Oral Candidiasis Caused by Candida

    The Effect of Quercus robur Bark on Oral Candidiasis Caused by Candida

    Introduction

    Quercus rubra L. (oak) is a member of the Fagaceae family and is widely distributed in Eastern America, and European districts.1–3 Most studies have indicated that numerous plant species produce extracts with highly active bioactive compounds, such as tannins, saponins, and alkaloids.4 Oak trees are a significant source of antifungal compounds that have been evaluated for their biological properties.5,6

    Oral Candidiasis poses a significant clinical health challenge, affecting more than 300 million individuals annually.7–11 It is one of the most expedient fungal infections that can affect the oral cavity of patients. Candida can aggregate on the normal oral biota of healthy persons in the area of the oral cavity, as reported in previous studies in 45–65% of healthy infants, while in healthy adults was 30–55%.12 In addition, candidiasis, which results from systemic and local factors, can develop and lead to symptoms inside the mouth.13 More than 150 species of Candida have been found and explained previously, but oral candidiasis is caused by the overgrowth of Candida albicans in the mouth. Other species such as Candida glabrata “currently reclassified as Nakaseomyces glabratus”, Candida tropicalis, Candida parapsilosis, Pichia kudriavzevii, and Candida dubliniensis can cause infections inside the mouth.14

    The reason for including the genotype of candida was to determine precisely the type of candida species that can be given the enhancement in the recognition of the variations at the level of species of candida in the antifungal resistance and pathogenicity of candida.15

    Antifungal resistance presents a challenge for healthcare providers managing invasive fungal infections owing to the limited available options for antifungal medications. Moreover, existing drugs may be hindered by drug interactions and severe side effects, which restrict their long-term use or dosage increase. Several studies have reported a low susceptibility of Candida species to azole antifungals “which are commonly used in clinical practice”. This is especially concerning in pediatric patients, due to their developing immune systems and the limited number of antifungal agents approved for use in children.16,17

    Recent assays for the identification of Candida spp by molecular methods and antifungal resistance have provided accurate results.18 Thus, the purpose of this study was to evaluate the activity of the hot water extract of oak bark as an alternative antifungal therapy against C. albicans and C. glabrata compared with azole.

    Materials and Methods

    One case of aggressive oral candidiasis was collected from an 8-year-old patient attending a private outpatient clinic in B. Province on 11 March 2024. The author hereby declares that every action has been assessed and given approval by the ethical principles that were performed in accordance with the ethical standards laid down by the Declaration of Helsinki, 1964. Ethical approval was granted by the Scientific Committee of the College of Dentistry at Mustansiriyah University (no. 777) on March 5, 2024. The patient and his parents were informed of the details of the study and its purpose, and their agreement was obtained for the publication of the data related to the results of the sample taken. The study was conducted between [March, 2024] and [June, 2024].

    The bark of Quercus robus L. was collected from the herbal medicine market. Originally, the plant barks were collected from the stem of Q. robus trees which were cultivated in Amedi of Kurdistan, Iraq. 36° 55′ 0″ N, 44° 2′ 0″ E. The trees are 35 years old. The identity of oak bark (Q. robus) was confirmed by Prof. Dr. Huda Jasim M. Altameme senior of plant taxonomy at, the biology department, University of Babylon. A voucher specimen has been deposited at the national herbarium with reference number 9836, Babylon, Iraq.

    This sample was collected using a sterile toothbrush, immersed in sabouraud dextrose medium (SDA) (Himedia, India), and then incubated at 30°C for 24/48 h.

    Purified individual colonies on SDA were streaked on CHROMagr (Himedia, India) and incubated for 24–48 h.19 Pre-identification was conducted based on the CHROMagar colored key designed by Nadeem et al in 2010.20

    Fifteen Candida spp. isolates were genotyped using the internal transcribed spacer (ITS) barcoding region. Direct culture of polymerase chain reaction (PCR) of 15 pure colonies from colony profiles grown on SDA, which were selected randomly, and a tiny portion of each colony was taken by tip 0.2 mL and picked up directly in a cocktail of PCR. The universal primer pair was designed to target specific sequences of the ITS rRNA region of Candida spp., according to Imran and Hadeel in 2014.19

    The primer pairs used were ITS5-ITS4 (5′-GGAAGTAAAAGTCGTAACAAGG-3′) and reverse (5′-TCCTCCGCTTATTGATATGC-3). The PCR reaction (25 μL) contained 5 μL of 20× Master Mix (Promega), 2 μL (10 pemole) of each primer, and 1 μL template DNA, with molecular-grade water added to bring the total volume to 25 μL.

    The PCR mixture was subjected to amplification with a thermal cycler PCR System (Labnet, USA) under the following conditions: first denaturized at 95°C for 5 min then 30 cycles of initial denaturation at 95°C for 30s, annealing at 56°C for 90s, extension at 72°C for 60s, and extension at 72°C for 10 min.

    The PCR products were separated on an agarose gel (1.2%) (Bio Basic Canada Inc.). In addition, electrophoresis was conducted at (100 V) using Tris Borate EDTA Ethylenediamine tetra acetsacide, and the agarose gel was pre-stained with ethidium bromide (EB) (0.05%). All DNA bands were detected using a desktop gel imager (Ultraviolet UV) Transilluminator (USA).

    A disk diffusion (DD) assay following the manufacturer’s instructions was conducted using discs with a diameter of 0.4 mm of fluconazole (FLU), itraconazole (ITR), and ketoconazole (KET) (10 mg/L for each). Amphotericin (AMP) 100 and 150 μL of hot water of oak extract were placed into a well (0.5 mm). The oak barks were collected from the herbal medicine market in Babylon City. The collected oak bark samples underwent morphological identification and authorization at the herbarium of the biology department, University of Babylon, Iraq.

    Based on standard culturing methods, three CHROMagar Candida plates were used per treatment as replicates. The SDA plates were inoculated with cell suspension (1×106) of C. glabrata and C. albicans for each. The plates were left for 30 min to absorb the liquid and were incubated for 24 h at 30 °C. After 24 h of cultivation, the diameter of the inhibitory zone (dz) was calculated based on the method described by Barry et al in 1979.21 The diameters of the zones were orthogonally measured using a rural metric. The arithmetic mean of the diameters of the inhibition zones was calculated using a simple statistical method. The data from the study were analyzed using SPSS version 29 (IBM, USA). Mean values and t-tests were employed to evaluate the inhibition zones of C. glabrata and C. albicans in response to activated oak and other antifungal agents.

    Results

    Cultural Identification

    All colonies grown on SDA showed a creamy color, and some showed internal sector growth. Figure 1A, shows the detailed colony texture of SDA. CHROMagar test results: 98% of Candida isolates streaked on CHROMagar medium showed a pale reddish color which was pre-identified as C. glabrata, whereas only 20% of isolates showed an apple green color which identified C. albicans (Figure 1B).

    Figure 1 (A) Oral Candida spp. grown on SDA, (B) CHROMagar assay, eight isolates showed a pale reddish color as C. glabrata and two isolates showed apple green color as C. albicans.

    Molecular Genotyping

    The results of amplification of ITS1-5.8S-ITS2 with flanking primer sequence by ITS5/ITS primer pair showed that 12 isolates given pale reddish color gave 870 bp bands, indicating that these isolates were C. glabrata, while two isolates which gave apple green color shown 550 bp (Figure 2).

    Figure 2 Gel electrophoresis of PCR of ITS1-5.8S-ITS2 profile. 1,9=C. albicans (550 bp),2–8,10-1,13–15 C. glabrata (870 bp). 1% agarose TBE buffer, 100 volts, 45 min. M, molecular marker 100–30000 bp).

    The biological activity of antifungal drugs— FLU, ITR, nystatin (NYS), KET, and AMP—generally demonstrated lower inhibitory effects against C. glabrata with inhibition values of 0.403 mm, 0.9 mm, 0.733 mm, 1.127 mm, 0.72 mm, respectively, and C. albicans (2.1 mm 0.403 mm, 0.4 mm, 2.633 mm, 0.4 mm), respectively, compared to the oak bark extract. In contrast, the oak bark extract exhibited a high inhibitory action against both C. glabrata and C. albicans, and the average zone of inhibition was 3.067 mm and 2.290 mm, respectively, higher than the biological activity of standard antifungal discs. C. glabrata showed high resistance to antifungal agents, whereas C. albicans showed sensitivity to fluconazole and ketoconazole but resistance to other antifungal agents (Table 1 and Figure 3). The DD extract showed low inhibitory activity against both C. glabrata and C. albicans, while the hot water extract of oak bark showed high antifungal activity against both yeasts under interest (Figure 4A and B).

    Table 1 Statistical Analysis of Inhibition Zones Profile Growth of C. Glabrata and C. Albicans in vitro Under Activities of Oak and Antifungals

    Figure 3 Histograms of inhibition zones profile growth of C. glabrata and C. albicans in vitro under activities of Quercus robur bark extract (Oak) and antifungals: Fluconazole (Flu.), Itraconazole (Itr.), (Ket) (10 mg/l for each), Amphotericin (Amp.) 100, Nystatin (Nys.).

    Figure 4 (A) Biofilm of C. glabrata grown on Sabouraud Dextrose Agar., illustration of the Diameter of inhibitor activity of Oak bark extract (Oak) compared with many antifungals, (B) Biofilm of C. albicans grown on Sabouraud Dextrose Agar., illustration the Diameter of inhibitor activity of Oak bark extract (Oak) compared with many antifungals. Fluconazole (Flu.), Itraconazole (Itr.), Ketoconazole (Ket) (10 mg/l for each). Amphotericin (Amp.) 100, Nystatin (Nys.), and 150µL of hot water of Oak extract were picked up into a well 0.5 mm, after duration growth of 24h at 30°C.

    The findings of this study suggested that extracts from natural ingredients, such as Quercus robur bark, can be more effective than traditional antifungal medications against Candida species (the novelty). This is particularly beneficial and promising for developing plant-based alternatives for treating oral candidiasis, especially in patients resistant to current antifungal therapies.

    Discussion

    One way to identify the mechanisms of antifungal drug resistance is to compare resistant clinical isolates with their susceptible counterparts.22 Several studies have reported the resistance of Candida spp. to azole drug.23–25 This study proved that alternative natural plant extract products still possess antifungal activity that confers azole resistance. The results of this study focused on the role of the crude Quercus robur bark extract had antifungal activity against C. glabrata and C. albicans isolates in vitro.

    One of the mechanisms of action of Quercus robur bark extracts is that these extracts may contain bioactive compounds like phenolic acids, tannins, and flavonoids that can disrupt the walls of the cells of the candida and alter the permeability of the wall.26 The other mechanism may be the interference with the enzymatic activity of the candida. Both mechanisms can be discussed in the effectiveness of the extract against the Candida species that have resistance to azole or nystatin.27

    These results are consistent with those reported by Morales in 2021.6 They reported that oak has antimicrobial, antiproliferative, and immunomodulatory activities. In 2022, Tanase et al28 referred to the importance of active compounds in an oak extract that had high antibacterial and antifungal activities against bacteria and Candidia spp. C. albicans, which led to the failure of management of candidiasis with antifungal agents, our interpretation aligns with that of Zarrinfar et al,29 showed some resistance to azole as an antifungal agent in C. glabrata and C. krusei following extended exposure to these antifungal agents.

    Previous studies have shown that tannins in Quercus bark extracts contain significant antibacterial compounds such as vescalagin, ellagic acid, gallic acid, and castalagin.30,31 This supported our results that showed a potential antifungal effect on crude material metabolites present in Q. rubra bark extracts. This is supported by the smaller inhibition diameter zone observed in vitro compared with standard antifungal discs. Similar to findings from another study on Q. robur bark extract against C. albicans using agar diffusion.32 Elansary et al33 also confirmed the antifungal properties of bark extracts of Q. robur against Penicillium funiculosum, Aspergillus flavus, P. ochrochloron, and C. albicans, which correlated with the presence of flavan-3-ols, ellagic acid, and derivatives of caffeic acid in oak bark.33

    Many clinicians complain of the nothingness of antifungal drugs against human fungal infections, the key priorities of which are antifungal resistance reduction and the quest for innovative antibacterial and antifungal agents able to modulate the virulence of Candida spp., such as adhesiveness and biofilm formation. Many studies have reported that secondary metabolites of plants, particularly polyphenols, exhibit antibacterial and antibiofilm properties.34

    The rise in flu resistance among non-C. albicans species is particularly alarming because of the growing number of infections caused by these species globally and the increasing prevalence of resistance to this commonly used azole in many medical facilities. Furthermore, there has been a documented increase in C. glabrata resistance to echinocandins in various US institutions, with a higher proportion of these isolates showing resistance to azole.16

    The final findings and conclusions of this study are a comprehensive note of the biological activities exhibited by Quercus extract compounds. Therefore, Quercus extracts are considered valuable sources of antifungal activity. The antifungal effects of Quercus bark can be largely attributed to new synthetic antifungals or a new combination of oak bark extract and azole drugs. These studies should also focus on developing innovative techniques to combat multidrug resistance and activity of the “quorum sensing”, particularly in the formation of Candida spp. biofilm. Consequently, in future studies, greater emphasis should be placed on in vivo experiments. Further research is required to establish the relationship between chemical compounds and bioactivity as well as to elucidate their mechanisms of action. Although Quercus products are generally considered safe, additional toxicological data are required to ensure their safety profile.35

    The results of this study indicate that C. glabrata and C. albicans showed the highest rates of resistance to antifungal medications. Furthermore, C. glabrata showed a lower rate of sensitivity to ketoconazole, whereas C. albicans exhibited the highest level of sensitivity to ketoconazole and fluconazole. Future studies with larger sample sizes and more isolated colonies and Candida spp. are recommended.

    Generally, this study was limited to an isolated sample and suggested more investigation to identify the Minimum Inhibitory Concentration (MIC) value.

    Conclusion

    The oak extract may be considered an alternative treatment for oral candidiasis that is infected by different types of Candida, such as C. glabrata and C. albicans which can compare positively more than other antifungals (eg azole or nystatin), these findings are preliminary and based on a limited number of isolates. This can open the door for further exploration to develop other antifungal treatments that can be used in patients resistant to oral candidiasis.

    Acknowledgment

    The authors thank the staff of the private clinics of Babylon Province for their moral support in the present work. The authors also thank Mustansiriyah University (http://www.uomustansiriyah.edu.iq), Baghdad – Iraq, for their moral support in this study.

    Funding

    No external funding was received for this study.

    Disclosure

    The authors declare no conflict of interest.

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    29. Zarrinfar H, Kord Z, Fata A. High incidence of azole resistance among Candida albicans and C. glabrata isolates in Northeastern Iran. Curr Med Mycol. 2021;7:18–21. doi:10.18502/cmm.7.3.7801

    30. Healey KR, Zhao Y, Perez WB, et al. Prevalent mutator genotype identified in fungal pathogen Candida glabrata promotes multi-drug resistance. Nat Commun. 2016;7:11128. doi:10.1038/ncomms11128

    31. Sari S, Barut B, Özel A, Kuruüzüm-Uz A, Şöhretoğlu D. Tyrosinase and α-glucosidase inhibitory potential of compounds isolated from Quercus coccifera bark: in vitro and in silico perspectives. Bioorg Chem. 2019;86:296–304. doi:10.1016/j.bioorg.2019.02.015

    32. Andrensek S, Simonovska B, Vovk I, Fyhrquist P, Vuorela H, Vuorela P. Antimicrobial and antioxidative enrichment of oak (Quercus robur) bark by rotation planar extraction using ExtraChrom. Int J Food Microbiol. 2004;92:181–187. doi:10.1016/j.ijfoodmicro.2003.09.009

    33. Elansary HO, Szopa A, Kubica P, et al. Polyphenol profile and pharmaceutical potential of Quercus spp. bark extracts. Plants. 2019;8:486. doi:10.3390/plants8110486

    34. Arendrup MC, Perlin DS, Jensen RH, Howard SJ, Goodwin J, Hope W. Differential in vivo activities of anidulafungin, caspofungin, and micafungin against Candida glabrata isolates with and without FKS resistance mutations. Antimicrob Agents Chemother. 2012;56:2435–2442. doi:10.1128/AAC.06369-11

    35. Algabar FAA, Baqer BA. Detection of biofilm formation of (Serratia and E. coli) and determination of the inhibitory effect of Quercus plant extract against these infectious pathogens. Bionatura. 2022;7:8. doi:10.21931/RB/2022.07.01.8

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  • Was the Air India crash caused by pilot error or technical fault? None of the theories holds up – yet

    Was the Air India crash caused by pilot error or technical fault? None of the theories holds up – yet

    Over the weekend, the Indian Aircraft Accident Investigation Bureau released a preliminary report on last month’s crash of Air India flight 171, which killed 260 people, 19 of them on the ground.

    The aim of a preliminary report is to present factual information gathered so far and to inform further lines of inquiry. However, the 15-page document has also led to unfounded speculation and theories that are currently not supported by the evidence.

    Here’s what the report actually says, why we don’t yet know what caused the crash, and why it’s important not to speculate.

    What the preliminary report does say

    What we know for certain is that the aircraft lost power in both engines just after takeoff.

    According to the report, this is supported by video footage showing the deployment of the ram air turbine (RAT), and the examination of the air inlet door of the auxiliary power unit (APU).

    The RAT is deployed when both engines fail, all hydraulic systems are lost, or there is a total electrical power loss. The APU air inlet door opens when the system attempts to start automatically due to dual engine failure.

    The preliminary investigation suggests both engines shut down because the fuel flow stopped. Attention has now shifted to the fuel control switches, located on the throttle lever panel between the pilots.

    This is what the fuel switches look like, with the throttle lever above them.
    Aircraft Accident Investigation Bureau

    Data from the enhanced airborne flight recorder suggests these switches may have been moved from “run” to “cutoff” three seconds after liftoff. Ten seconds later, the switches were moved back to “run”.

    The report also suggests the pilots were aware the engines had shut down and attempted to restart them. Despite their effort, the engines couldn’t restart in time.

    We don’t know what the pilots did

    Flight data recorders don’t capture pilot actions. They record system responses and sensor data, which can sometimes lead to the belief they’re an accurate representation of the pilot’s actions in the cockpit.

    While this is true most of the time, this is not always the case.

    In my own work investigating safety incidents, I’ve seen cases in which automated systems misinterpreted inputs. In one case, a system recorded a pilot pressing the same button six times in two seconds, something humanly impossible. On further investigation, it turned out to be a faulty system, not a real action.

    We cannot yet rule out the possibility that system damage or sensor error led to false data being recorded. We also don’t know whether the pilots unintentionally flicked the switches to “cutoff”. And we may never know.

    As we also don’t have a camera in the cockpit, any interpretation of pilots’ actions will be made indirectly, usually through the data sensed by the aircraft and the conversation, sound and noise captured by the environmental microphone available in the cockpit.

    We don’t have the full conversation between the pilots

    Perhaps the most confusing clue in the report was an excerpt of a conversation between the pilots. It says:

    In the cockpit voice recording, one of the pilots is heard asking the other why did he cutoff. The other pilot responded that he did not do so.

    This short exchange is entirely without context. First, we don’t know who says what. Second, we don’t know when the question was asked – after takeoff, or after the engine started to lose power? Third, we don’t know the exact words used, because the excerpt in the report is paraphrased.

    Finally, we don’t know whether the exchange referred to the engine status or the switch position. Again, we may never know.

    What’s crucial here is that the current available evidence doesn’t support any theory about intentional fuel cutoff by either of the pilots. To say otherwise is unfounded speculation.

    We don’t know if there was a mechanical failure

    The preliminary report indicates that, for now, there are no actions required by Boeing, General Electric or any company that operates the Boeing 787-8 and/or GEnx-1B engine.

    This has led some to speculate that a mechanical failure has been ruled out. Again, it is far too early to conclude that.

    What the preliminary report shows is that the investigation team has not found any evidence to suggest the aircraft suffered a catastrophic failure that requires immediate attention or suspension of operations around the world.

    This could be because there was no catastrophic failure. It could also be because the physical evidence has been so badly damaged that investigators will need more time and other sources of evidence to learn what happened.

    Why we must resist premature conclusions

    In the aftermath of an accident, there is much at stake for many people: the manufacturer of the aircraft, the airline, the airport, civil aviation authority and others. The families of the victims understandably demand answers.

    It’s also tempting to latch onto a convenient explanation. But the preliminary report is not the full story. It’s based on very limited data, analysed under immense pressure, and without access to every subsystem or mechanical trace.

    The final report is still to come. Until then, the responsible position for regulators, experts and the public is to withhold judgement.

    This tragedy reminds us that aviation safety depends on patient and thorough investigation – not media soundbites or unqualified expert commentary. We owe it to the victims and their families to get the facts right, not just fast.

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  • DVA reduces radiation exposure during interventions

    DVA reduces radiation exposure during interventions

    Digital variance angiography (DVA) can reduce radiation doses to patients versus conventional angiography during certain interventional radiology procedures, a group in Germany has reported.

    The finding is from a comparison between the two approaches among patients undergoing treatments for narrowed or blocked arteries in the lower extremities (endovascular peripheral interventions, or EPIs). The technique also improved image quality, noted lead author Dr. Till Schürmann, of the University of Freiburg, and colleagues.

    “DVA reveals significant radiation dose reduction in lower extremity EPIs and enhances image contrast while decreasing noise,” the group wrote. The study was published on 9 July in Scientific Reports.

    DVA is an emerging motion-based x-ray imaging technique that uses software to visualize the distribution of iodinated contrast medium (ICM) in the vascular system. The technique allows for lower doses of ICM and can be used during standard-of-care angiography examinations, the researchers explained.

    To demonstrate its potential advantages, in this study, the group compared its use in 62 patients who underwent EPIs with 370 patients who underwent EPIs with normal ICM dose protocols. They evaluated the overall dose area product (DAP) for each patient from both groups in the pelvic, femoral, and leg regions (popliteal and cruropedal) and assessed image quality by calculating the contrast-to-noise ratio (CNR) in specific regions of interest (ROIs) on vessels.

    Pelvic (A), femoral and popliteal (B), and cruro-pedal (C) region. The summated digital variance angiography (DVA) image significantly enhances image quality compared to the digital subtraction angiography (DSA) series I–IV (depicting 4 out of 28 (A), 48 (B) and 28 (C) DSA images) of the low dose (LD) acquisitions. Enhancements of iodinated contrast medium (ICM) by DVA depict small vessel structures in detail while the conventional DSA offers a reduced contrast-to-noise ratio (CNR) using LD acquisitions for standalone diagnostic interpretations.Scientific Reports

    According to the analysis, overall DAP was significantly reduced in the DVA group from 3238.6 cGy·cm² to 1230.4 cGy·cm² in pelvic regions, from 1190.9 cGy·cm² to 550.8 cGy·cm² in femoral and popliteal regions, and from 827.6 cGy·cm² to 336.0 cGy·cm² in cruropedal regions.

    In addition, DVA images exhibited substantially enhanced ICM contrast and decreased background noise in all regions, the group reported. Specifically, median CNRs in ROIs in the DVA group increased significantly from 8.8 to 14.4 in pelvic regions, from 6.9 to 17.8 in femoral and popliteal regions, and from 7.8 to 17.3 in cruropedal regions.

    “DVA can significantly reduce (stochastic) health risk effects of radiation exposure for both patients and staff performing endovascular peripheral interventions,” the group wrote.

    Ultimately, standard angiography (digital subtraction angiography) remains an essential interventional tool in diagnosing and treating stenosis and occlusions in EPI, and this study adds to the growing evidence of the benefits in DVA, the researchers wrote.

    Also, they noted that a limitation of the study was that the image quality evaluation was performed objectively by calculating CNRs, rather than by a subjective qualitative assessment.

    “Subjective ratings of the image quality would also be a beneficial determinant for future analysis, especially in prospective studies where categories can be controlled more strictly,” the group concluded.

    The full study is available here.

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  • Soaring Saudi exports and trade tensions will test oil price resilience – Reuters

    1. Soaring Saudi exports and trade tensions will test oil price resilience  Reuters
    2. Oil Prices Expected to Stay Under $70  Crude Oil Prices Today | OilPrice.com
    3. OPEC+ and Trump in a standoff, oil prices may reach this level.  富途牛牛
    4. Analyst report challenges bearish oil outlook, cites strong demand  Midland Reporter-Telegram
    5. Why big global events aren’t impacting the price of oil the way they used to  MSN

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