Nevin Manimala

Biometrics. 2025 Oct 8;81(4):ujaf157. doi: 10.1093/biomtc/ujaf157.

ABSTRACT

Effective treatment of medical conditions begins with an accurate diagnosis. However, many conditions are often underdiagnosed, either being overlooked or diagnosed after significant delays. Electronic health records (EHRs) contain extensive patient health information, offering an opportunity to probabilistically identify underdiagnosed individuals. The rationale is that both diagnosed and underdiagnosed patients may display similar health profiles in EHR data, distinguishing them from condition-free patients. Thus, EHR data can be leveraged to develop models that assess an individual’s risk of having a condition. To date, this opportunity has largely remained unexploited, partly due to the lack of suitable statistical methods. The key challenge is the positive-unlabeled EHR data structure, which consists of data for diagnosed (“positive”) patients and the remaining (“unlabeled”) that include underdiagnosed patients and many condition-free patients. Therefore, data for patients who are unambiguously condition-free, essential for developing risk assessment models, are unavailable. To overcome this challenge, we propose ascertaining condition statuses for a small subset of unlabeled patients. We develop a novel statistical method for building accurate models using this supplemented EHR data to estimate the probability that a patient has the condition of interest. We study the asymptotic properties of our method and assess its finite-sample performance through simulation studies. Finally, we apply our method to develop a preliminary model for identifying potentially underdiagnosed non-alcoholic steatohepatitis patients using data from Penn Medicine EHRs.

PMID:41321243 | DOI:10.1093/biomtc/ujaf157

Epidemiol Psychiatr Sci. 2025 Dec 1;34:e56. doi: 10.1017/S2045796025100310.

ABSTRACT

AIMS: Depression among middle-aged and older adults is a critical public health priority. Clarifying the dynamic evolution of depression is essential for establishing prevention and intervention strategies; however, relevant research is limited. The aim of this study was to elucidate the transition patterns underlying different depressive symptoms (DS) states.

METHODS: Data from the China Health and Retirement Longitudinal Study were utilised in this study, which included participants aged ≥45 years with multiple DS assessments via the Center for Epidemiological Studies Depression Scale. Multi-state Markov models were employed to estimate transition probabilities and intensities between DS states, the total length of stay and mean sojourn time in each state and the hazard ratios (HRs) of factors.

RESULTS: Among 19,991 participants (average follow-up: 7.3 years), the 10-year cumulative probabilities of transition from non-DS to depressive states increased by 19.4% in males and 31.8% in females. Mild DS was the most unstable state, with the highest transition intensities (males: 1.029; females: 0.970) and shortest sojourn time (males: 0.959 years; females: 1.022 years). Sex and age strongly influenced depressive state transitions. Compared to participants without chronic disease, those with ≥3 chronic diseases had a higher risk of developing mild DS (HR = 1.685, 95% Confidence Interval [CI]: 1.530-1.856) and transitioning to death from both the non-DS (HR = 2.905, 95% CI: 2.293-3.681) and severe-DS (HR = 3.429, 95% CI: 1.290-9.112) states, but a lower likelihood of recovery from mild DS (HR = 0.821, 95% CI: 0.749-0.900) and severe DS (HR = 0.730, 95% CI: 0.630-0.847). Compared to no participation in social activities, frequent participation was associated with a lower risk of progression to the mild-DS state (HR = 0.851, 95% CI: 0.785-0.920) and a greater likelihood of recovery from severe DS (HR = 1.169, 95% CI: 1.034-1.322). Being underweight was associated with an increased risk of mild-DS onset (HR = 1.338, 95% CI: 1.129-1.587) and transitioning to death from both the non-DS and mild-DS states, compared with individuals of normal weight.

CONCLUSIONS: Our study revealed a continuous population shift towards depressive states and identified the mild-DS state as a critical intervention state owing to its instability. In addition to sex and age, modifiable factors, including chronic disease conditions, social activity participation and weight status, significantly influenced DS-state transitions, offering actionable insights for precision prevention strategies.

PMID:41321236 | DOI:10.1017/S2045796025100310

Disaster Med Public Health Prep. 2025 Dec 1;19:e335. doi: 10.1017/dmp.2025.10264.

ABSTRACT

OBJECTIVE: Building collapses, debris removal, new construction, and increased stove use for heating have elevated air pollution in regions affected by the February 6, 2023, Kahramanmaraş earthquake. This study examines the relationship between carbon monoxide (CO) poisoning and air pollution in these areas 1 year after the disaster.

METHODS: A retrospective analysis of 151 patients from 10 hospitals in 8 cities was conducted, including data on demographics, clinical symptoms, sources of CO exposure, vital signs, laboratory findings, air pollution levels, and outcomes.

RESULTS: Indoor stove use was the primary source of CO exposure. The average Air Quality Index (AQI) was 55 (IQR 44-56), and particulate matter (PM_2.5) levels averaged 17.5 μg/m³ (IQR 10-27), exceeding EPA (Environmental Protection Agency) thresholds. AQI levels post-earthquake were significantly higher than pre-earthquake in Kahramanmaraş (AQI₁ = 48.5 [IQR 48-55], AQI₂ = 55 [IQR 55-80]; P = 0.007), Hatay (AQI₁ = 40.5 ± 13.7, AQI₂ = 56 [IQR 51-60.5]; P <0.001), and Gaziantep (AQI₁ = 44 [IQR 41-56], AQI₂ = 55 [IQR 54-55.5]; P = 0.014). Leukocytosis (P = 0.004) and myocardial injury (P <0.001) in CO poisoning cases varied significantly across provinces.

CONCLUSIONS: In conclusion, elevated AQI and PM_2.5 levels likely worsened myocardial injury in CO poisoning cases due to combined outdoor and indoor pollution effects. These findings emphasize the need for air quality monitoring and mitigation in disaster regions.

PMID:41321219 | DOI:10.1017/dmp.2025.10264

Disaster Med Public Health Prep. 2025 Dec 1;19:e336. doi: 10.1017/dmp.2025.10265.

ABSTRACT

OBJECTIVE: To develop an evaluative framework for assessing the emergency response capabilities of higher education institutions to major emerging infectious diseases, enabling institutions to identify preparedness gaps and prioritize improvements across the outbreak lifecycle.

METHODS: The Haddon Matrix was used as the foundation for the framework. A Delphi study with a Likert scale was conducted, followed by the Analytic Hierarchy Process (AHP) to determine the importance of the indicators.

RESULTS: A consensus was reached on the evaluation system, comprising 3 primary indicators: prevention and preparedness, response and handling, and recovery and rehabilitation. These indicators were further divided into 11 secondary and 34 tertiary indicators. Expert authority coefficients were 0.82 and 0.80, and Kendall’s coefficients were 0.32 and 0.161 (P < 0.001). AHP highlighted prevention and preparedness as the highest-priority domain (weight = 0.426), followed by recovery and rehabilitation (0.326). High-priority items included safety knowledge dissemination, emergency command systems, primary prevention, and timely warning and monitoring.

CONCLUSIONS: Integrating the Haddon matrix, Delphi consensus, and AHP, this study delivers a validated, prioritized framework to assess universities’ MEID response capability across phases. External validity beyond Shanghai remains to be established; cross-regional applicability should be empirically tested through multi-site validation, broader stakeholder representation, and evaluation of technology-enabled components, particularly in resource-limited settings.

PMID:41321216 | DOI:10.1017/dmp.2025.10265

Ann Pharmacother. 2025 Dec 1:10600280251384651. doi: 10.1177/10600280251384651. Online ahead of print.

ABSTRACT

BACKGROUND: Critically ill patients receiving continuous renal replacement therapy (CRRT) commonly experience hypotension necessitating fluids, ultrafiltration (UF) adjustment, or vasopressors. There is limited evidence evaluating 25% albumin on vasopressor requirements in this population.

OBJECTIVE: To evaluate the impact of 25% albumin on vasopressor requirements for critically ill patients requiring CRRT.

METHODS: This single-center, retrospective, intrapatient comparator study included adults admitted to the Cardiothoracic Surgery Intensive Care Unit (CTICU) who received 25% albumin intravenously every 6 or 8 hours for ≥2 consecutive doses while on CRRT and vasopressors. The primary endpoint was the absolute change in average vasopressor dosage from 48 hours before to 48 hours after the first albumin administration in norepinephrine equivalents (NEE, mcg/kg/min). A multivariable interrupted time series model was conducted. Notable secondary endpoints included absolute change in UF rate and 48-hour fluid balance.

RESULTS: Of 252 patients reviewed, 60 were included. The median absolute change in average vasopressor dosage from 48 hours prealbumin to 48 hours postalbumin was -0.005 mcg/kg/min (Q1: -0.035, Q3: 0.021, P = 0.24), with a median percentage change in average dosage of -9.5% (Q1: -33.2, Q3: 34.4). The multivariable regression analysis reported a 0.0038 mcg/kg/min increase in vasopressor dosage (P = 0.02) and a 0.0044 mcg/kg/min decrease in vasopressor dosage (P = 0.001) for every 4-hour increase in time in the 48 hours before and after albumin, respectively. From 48 hours prealbumin to 48 hours postalbumin, UF rate increased numerically (10.6 mL/hr [interquartile range (IQR) -24.0, 49.8]), and 48-hour fluid balance decreased numerically (-467.4 mL/48 hr [IQR -3124.5, 1306.3]).

CONCLUSION AND RELEVANCE: In CTICU patients receiving CRRT and vasopressors, 25% albumin resulted in no statistically significant difference in average vasopressor requirements in the 48 hours prealbumin compared to the 48 hours postalbumin in the unadjusted model. However, multivariable regression demonstrated a significant association between albumin administration and reduced vasopressors during the 48-hour period following albumin.

PMID:41321209 | DOI:10.1177/10600280251384651

Ann Afr Med. 2025 Dec 2. doi: 10.4103/aam.aam_551_25. Online ahead of print.

ABSTRACT

INTRODUCTION: Metabolic syndrome (MetS), defined by central obesity, dyslipidemia, hyperglycemia, and hypertension, is a major risk factor for type 2 diabetes and cardiovascular disease. Despite its clinical importance, the underlying pathophysiology of MetS remains incompletely understood. Serum ferritin, a marker of iron storage, oxidative stress, and metabolic dysfunction, has been associated with insulin resistance and lipid abnormalities. This study aimed to investigate the relationship between serum ferritin levels and MetS, along with its individual components.

MATERIALS AND METHODS: This cross-sectional study included 230 participants, with cases diagnosed with MetS based on International Diabetes Federation criteria and age-matched controls. Clinical, anthropometric, and biochemical parameters, including serum ferritin levels, were assessed. Data analysis was performed using Stata MP-17, with statistical significance set at P ≤ 0.05.

RESULTS: Individuals with MetS exhibited significantly higher waist and hip circumferences, blood pressure (BP), triglycerides, serum ferritin levels, and poorer glycemic control compared to controls (P < 0.001). Serum ferritin showed a positive correlation with body mass index (BMI), fasting glucose, triglycerides, BP, total leukocyte count, and neutrophils, and a negative correlation with lymphocyte count, indicating a strong association between elevated ferritin levels, metabolic dysregulation, and systemic inflammation.

CONCLUSION: Elevated serum ferritin is significantly associated with increased BMI, central obesity, dyslipidemia, and impaired glucose regulation in individuals with MetS. Its correlations with lipid and inflammatory markers suggest ferritin may serve as a surrogate biomarker for metabolic and cardiovascular risk.

PMID:41321203 | DOI:10.4103/aam.aam_551_25

Acta Anaesthesiol Scand. 2026 Jan;70(1):e70156. doi: 10.1111/aas.70156.

ABSTRACT

Shedding of the endothelial glycocalyx may be a pathophysiological mechanism in septic shock, to which intravenous (IV) fluid therapy may contribute. We aimed to investigate the effects of restrictive versus standard IV fluid therapy on glycocalyx shedding in adult intensive care unit (ICU) patients with septic shock. In this preplanned sub-study of the CLASSIC trial, ICU patients with septic shock were randomized to restrictive or standard IV fluid therapy at one Danish and one Swedish ICU between February 2020 and October 2021. Plasma markers of glycocalyx shedding were measured at four timepoints: within the first hour after randomization (T0), the following morning (T1), the morning after (T2), at ICU discharge or up to 90 days after randomization (T3). The primary outcome was the change in plasma hyaluronan levels from T0 to T1. A total of 54 patients were included, below the planned sample size of 200, leading to important differences between groups. Mean hyaluronan levels decreased by 11 ng/mL (95% CI 35-41) more in the restrictive group compared to the standard group from T0 to T1. The interaction effect between group and time was non-significant (p value: 0.872). In this underpowered sub-study we found no statistically significant difference in endothelial glycocalyx shedding between adult ICU patients with septic shock randomized to restrictive versus standard IV fluid therapy. We consider these findings hypothesis-generating; further research is needed to confirm these results. EDITORIAL COMMENT: In this substudy of the CLASSIC trial, glycocalyx degredation products and related substances were measured serially in sepsic study participants randomized to restrictive or usual fluid treatment protocols. No differences between treatment glycocalyx degredation product and related substance levels were observed. Trial Registration: ClinicalTrials.gov identifier: NCT04282252.

PMID:41321198 | DOI:10.1111/aas.70156

Diabetes Obes Metab. 2025 Dec 1. doi: 10.1111/dom.70301. Online ahead of print.

ABSTRACT

AIMS: To comprehensively assess the efficacy and safety of liraglutide on metabolic and hepatic outcomes in patients with non-alcoholic fatty liver disease (NAFLD), with or without type 2 diabetes mellitus (T2DM), based on randomised controlled trials (RCTs).

MATERIALS AND METHODS: Electronic databases (PubMed, Web of Science, Cochrane Library and Embase) were systematically searched for randomised RCTs evaluating liraglutide in the treatment of NAFLD. Outcome measures included body mass index (BMI), glycated haemoglobin A1c (HbA1c), fasting plasma glucose (FPG), aspartate aminotransferase (AST), alanine aminotransferase (ALT), gamma-glutamyl transferase (GGT), alkaline phosphatase (ALP), total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C) and adverse events (AEs).

RESULTS: Eight RCTs (with an overall moderate risk of bias as assessed by the Cochrane Risk of Bias tool) involving 478 participants were included in the analysis. The meta-analysis results demonstrated that liraglutide significantly improved BMI (standardised mean difference [SMD]: -0.85; 95% confidence interval [CI]: -1.04 to -0.66), FPG (SMD: -1.22; 95% CI: -1.97 to -0.46), and GGT (SMD: -1.10; 95% CI: -1.48 to -0.72; p < 0.00001) in patients with NAFLD, regardless of T2DM comorbidity. Furthermore, liraglutide showed positive effects on ALT (SMD: -0.44; 95% CI: -0.80 to -0.08) and TG (SMD: -1.08; 95% CI: -1.97 to -0.19) specifically in patients with NAFLD comorbid with T2DM. However, the effect of liraglutide on HbA1c was not statistically significant (SMD: 0.14; 95% CI: -0.39 to 0.67). Regarding safety, liraglutide was associated with a higher incidence of adverse events, primarily gastrointestinal disorders such as nausea and diarrhoea, though these were mostly transient.

CONCLUSIONS: Liraglutide demonstrates beneficial effects on BMI, FPG and GGT in patients with NAFLD with or without comorbid T2DM. It also shows positive effects on ALT and TG in patients with NAFLD and T2DM. While the treatment was associated with a higher burden of mostly manageable gastrointestinal adverse events, the findings of this study warrant further validation in prospective high-quality studies.

PMID:41321175 | DOI:10.1111/dom.70301

Glob Health Action. 2025 Dec;18(1):2585674. doi: 10.1080/16549716.2025.2585674. Epub 2025 Dec 1.

ABSTRACT

BACKGROUND: While the adverse effects of intimate partner violence (IPV) on sexual and reproductive health are globally recognized, research in low- and middle-income countries, particularly Uganda, remains limited.

OBJECTIVE: This study aims to assess the association between past-year IPV and HIV, contraceptive use, and unintended pregnancies among Ugandan women.

METHODS: Data from the Africa Medical and Behavioural Sciences Organization collected during the 2019 Population Health Surveillance in Hoima and Wakiso districts, Uganda were analysed including 1,819 women aged 15-49. Binary logistic regression was performed to estimate adjusted odds ratios (AOR) at 95% confidence interval. This study used a cross-sectional design; therefore, causal inference cannot be established.

RESULTS: Women with past-year sexual IPV had 3.2 times higher odds of having unintended pregnancy (adjusted odds ratio (AOR): 3.2, 95% CI: 1.72, 5.97). There was a borderline association between both HIV infection and physical (AOR: 1.67 95% CI: 1.00, 2.79) and psychological IPV (AOR: 1.42 95% CI: 1.00, 2.00). Contraceptive use was not found to be associated with IPV (AOR: 1.30 95% CI: 0.90, 1.89).

CONCLUSION: The results indicate that the link between IPV and unintended pregnancies is suggestive of a potential association. While the association between IPV and HIV was not statistically significant, it points to a possible relationship that requires further research. There was no significant association between IPV and contraceptive use. Given the design of the study, causal inference cannot be established; however, the results may inform future studies aimed at preventing IPV and improving SRHR outcomes in Uganda.

PMID:41321171 | DOI:10.1080/16549716.2025.2585674

J Chem Theory Comput. 2025 Dec 1. doi: 10.1021/acs.jctc.5c01143. Online ahead of print.

ABSTRACT

Markov state models (MSMs) are widely employed to analyze the kinetics of complex systems. But despite their effectiveness in many applications, MSMs are prone to systematic or statistical errors, often exacerbated by suboptimal hyperparameter choice. In this article, we attempt to understand how these choices affect the error of estimates of mean first-passage times and committors, key quantities in chemical rate theory. We first evaluate the performance of the recently introduced “stopped-process estimator” [Strahan, J. Long-time-scale predictions from short-trajectory data: A benchmark analysis of the trp-cage miniprotein. J. Chem. Theory Comput. 2021, 17, 2948-2963. 10.1021/acs.jctc.0c00933.] that attempts to reduce error caused by choosing a too-large lag time. We then study the effect of statistical errors on Markov state model construction using the condition number, which measures an MSM’s sensitivity to perturbation. This analysis helps give an insight into which factors cause an MSM to be more or less sensitive to statistical error. Our work highlights the importance of choosing a good sampling measure, the measure from which the initial points are drawn, and has implications for recent work applying a variational principle for evaluating the committor.

PMID:41321159 | DOI:10.1021/acs.jctc.5c01143