Tag: nevin manimala

Front Public Health. 2026 Aug 14;14:1858500. doi: 10.3389/fpubh.2026.1858500. eCollection 2026.

ABSTRACT

BACKGROUND: Civil Registration and Vital Statistics (CRVS) systems are fundamental to evidence-based governance and public health. In India, a persistent gender disparity exists in death registration: approximately 73% of male deaths are officially recorded compared to only 64% of female deaths nationally (NFHS-5). Gujarat, despite its relatively advanced socio-economic standing and near 93.1% overall death registration rate (CRS 2023), continues to exhibit this troubling gap.

OBJECTIVE: This study analyses the structural, economic, and socio-cultural drivers of gender disparities in death registration in Gujarat and proposes policy interventions aimed at achieving universal and gender-equitable registration completeness.

METHODS: This study employs a mixed-method policy analysis framework, synthesizing secondary data from the National Family Health Survey (NFHS-5), the Civil Registration System (CRS) 2023 Annual Report, Sample Registration System (SRS) data, and peer-reviewed literature. Qualitative insights are drawn from administrative case studies, district-level reports from Gujarat, and comparative analysis of high-performing states (Kerala and Tamil Nadu).

RESULTS: The gender gap in death registration was widest among the poorest wealth quintile (13 percentage points) and narrowed substantially among the richest quintile (4 percentage points). Key barriers included: (i) an economic-utility logic, whereby male deaths are prioritized due to implications for asset succession (“Varsai”); (ii) higher prevalence of female home deaths linked to healthcare access inequities; (iii) administrative and bureaucratic barriers at the Panchayat level; and (iv) under-reporting of socially sensitive female deaths, including maternal mortality and suicides.

CONCLUSION: Closing gender gaps in death registration requires a rights-based approach that integrates administrative simplification, strengthened community-level reporting through ASHA and Anganwadi networks, expanded digital infrastructure, and targeted public awareness initiatives. If equitably implemented, Gujarat’s digital governance architecture has the potential to substantially reduce female invisibility in official mortality statistics.

PMID:42666286 | PMC:PMC13522170 | DOI:10.3389/fpubh.2026.1858500

Front Psychiatry. 2026 Aug 14;17:1908580. doi: 10.3389/fpsyt.2026.1908580. eCollection 2026.

ABSTRACT

BACKGROUND: Exercise intervention has been associated with cognitive development in children. However, current study methods have not clarified the potential nonlinear association between exercise dosage and cognitive ability, and interpretable machine learning approaches may provide a novel perspective for exploring these complex relationships. Therefore, this study aimed to construct and verify a machine learning model of the relationship between exercise dosage and cognitive development in children.

METHODS: A total of 8623 valid samples from the China Family Panel Studies (CFPS) database were analyzed in this study. SPSS 25.0 was used to perform descriptive statistical analysis. SHAP values and partial dependence plots were used to enhance model interpretability. Three predictive models-Exercise Dose-Cognitive Ability Score (ED-CAS) model, Daily Physical Activity Duration-Cognitive Ability Score (DPAD-CAS) model, and Weekly Frequency of Physical Activity-Cognitive Ability Score (WFPA-CAS) model-were developed using the random forest algorithm.

RESULTS: The ED-CAS, DPAD-CAS, and WFPA-CAS models demonstrated moderate predictive performance (R² = 0.21, 0.14, and 0.11, respectively). SHAP analysis revealed mean marginal contributions of 0.12, 0.07, and 0.11 for ED, DPAD, and WFPA, respectively. Partial dependence analyses further identified normalized parameter peaks at 1.35 (ED), 1.4 (DPAD), and 0.9 (WFPA), indicating that these exercise-related features contributed differently to model predictions across dose ranges. However, dose thresholds were observed (≤720 minutes/week, ≤6 days/week, ≤85 minutes/day), beyond which CAS declined significantly.

CONCLUSIONS: This study identified a potential inverted U-shaped association between exercise dosage and cognitive ability in children. The observed dose ranges may provide preliminary reference information for future exercise intervention. However, longitudinal and experimental studies are required to determine causal relationships and establish evidence-based exercise recommendations.

PMID:42666282 | PMC:PMC13522174 | DOI:10.3389/fpsyt.2026.1908580

Math Financ Econ. 2026;20(2):405-453. doi: 10.1007/s11579-026-00418-5. Epub 2026 Aug 1.

ABSTRACT

We provide a stochastic analysis of an overlapping-generations model under incomplete markets. By casting individual optimization with idiosyncratic income risk into a forward-backward stochastic differential-equation (FBSDE) system, we (i) establish existence and uniqueness of the dynamic general-equilibrium interest rate and (ii) derive analytical and semi-explicit formulas for both the equilibrium interest-rate path and the natural borrowing limit – defined as the discounted expected shortfall of future income. Our FBSDE-based approach yields tractable policy functions and equilibrium mappings without relying on high-dimensional PDE methods, offering clear insights into how income dynamics and demographic structure drive interest-rate fluctuations and credit constraints.

PMID:42666272 | PMC:PMC13521973 | DOI:10.1007/s11579-026-00418-5

Am J Health Promot. 2026 Aug 28:8901171261481766. doi: 10.1177/08901171261481766. Online ahead of print.

ABSTRACT

PurposeTo evaluate the effect of an educational intervention based on the Oral Health and Your Pregnancy booklet on the knowledge, attitudes, and behaviors of pregnant women in primary care in Cuiabá, Brazil.DesignQuantitative pre-post intervention study without a control group.SettingA primary healthcare unit in Cuiabá, Mato Grosso, Brazil.Sample374 pregnant women in the first to third trimester.InterventionA 30-minute lecture and practical demonstration of oral hygiene.MeasuresSociodemographic questionnaire, indicators of oral-health and dietary knowledge/practices, and OHIP-14.AnalysisDescriptive statistics, paired t-tests, Wilcoxon signed-rank tests, and chi-square tests.ResultsKnowledge about the relevance of oral health during pregnancy increased from 38% to 72% (χ² = 44.27; P < 0.001), awareness of disease transmission to newborns increased from 10% to 63% (χ² = 36.41; P < 0.001), and self-reported oral pain/discomfort decreased from 60% to 35% (χ² = 21.87; P < 0.001).ConclusionThe intervention improved short-term oral-health knowledge and self-perception. The absence of a control group and immediate post-intervention assessment limit causal and long-term inferences.

PMID:42665564 | DOI:10.1177/08901171261481766

Pharm Stat. 2026 Sep-Oct;25(5):e70115. doi: 10.1002/pst.70115.

ABSTRACT

In many studies, multiple longitudinal outcomes are collected, and interest lies in studying the association between these outcomes. Joint modeling is then required, but full likelihood estimation becomes infeasible as the number of outcomes increases. To address this, the pairwise-fitting approach was developed. However, the robustness of this pseudo-likelihood-based approach under missing at random (MAR) remains unclear. We investigate the impact of MAR dropout on the pairwise-fitting approach through a case and simulation study and compare the results to full likelihood estimation. In the simulation study, we simulate three continuous longitudinal outcomes so that full likelihood estimation remains computationally feasible, allowing a comparison with the pairwise fitting approach. Various settings are examined, including random intercept and random intercept-and-slope models, in which we vary the standard deviation of the error terms and the degree of correlation between random effects. Our results show that bias remains limited in random intercept models and in most random intercept-and-slope models. However, when the standard deviation of the error terms becomes large compared to that of the random effects, some bias appears in the covariances between the random effects of the outcomes not driving dropout. This bias is mitigated using multiple imputation. As a case study, we analyzed data from a schizophrenia study using both full likelihood and pseudo-likelihood approaches and compared the results.

PMID:42665560 | DOI:10.1002/pst.70115

Eur J Intern Med. 2026 Aug 29:107169. doi: 10.1016/j.ejim.2026.107169. Online ahead of print.

ABSTRACT

BACKGROUND: Systemic lupus erythematosus (SLE) is associated with increased cardiovascular morbidity, but the long-term prognostic value of subclinical atherosclerosis and circulating biomarkers remains uncertain. We aimed to assess 10-year vascular outcomes and identify clinical and biological predictors of thrombotic events in SLE.

METHODS: This prospective cohort study included 97 consecutive female patients with SLE who underwent baseline clinical, laboratory, and carotid ultrasound evaluation and were followed for a mean of 9.7 ± 2.8 years. Carotid intima-media thickness (IMT) and plaque were assessed according to standardized criteria. Traditional cardiovascular risk factors, lupus-related variables, and biomarkers including adipokines, inflammatory mediators, endothelial activation markers, and osteoprotegerin were analyzed. Cardiovascular events were confirmed by medical record review. Logistic and Cox regression models were used to identify predictors. Arterial events were compared with an age-matched population-based cohort.

RESULTS: Carotid plaques were present in 44% of patients at baseline. During follow-up, 11 patients (11.3%) experienced thrombotic cardiovascular events, including eight arterial events. Metabolic syndrome (29.4% vs. 6.5%, p = 0.006) and hypertension (22.2% vs. 7.1%, p = 0.036) were associated with increased risk. In Cox analysis, metabolic syndrome independently predicted events (HR 4.3, 95% CI 1.2-15.2, p = 0.012), while age was the strongest independent determinant of both overall and arterial events. Higher IMT, cumulative damage, and reduced renal function were associated with adverse outcomes. An independent prognostic association between most inflammatory and adipokine biomarkers could not be demonstrated within our cohort. Compared with controls, SLE patients showed numerically higher arterial event rates, although differences were not statistically significant.

CONCLUSIONS: Long-term cardiovascular risk in SLE appears to be driven mainly by age, metabolic abnormalities, and cumulative organ damage rather than by lupus-specific inflammatory biomarkers.

PMID:42665520 | DOI:10.1016/j.ejim.2026.107169

Eur Urol Oncol. 2026 Aug 28:S2588-9311(26)00228-2. doi: 10.1016/j.euo.2026.08.001. Online ahead of print.

ABSTRACT

DESIGN, SETTING, AND PARTICIPANTS: Exploratory post hoc analysis of the international, randomised, open-label phase 3 PEACE-3 trial including 446 patients with asymptomatic or mildly symptomatic mCRPC and bone metastases. Overall, 441 and 436 patients were evaluable for ALP and PSA, respectively.

INTERVENTION: Enzalutamide 160 mg daily alone or combined with six-monthly injections of radium-223 (55 kBq/kg).

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: ALP response was defined as a ≥30% decline from baseline (ALP-30), and PSA response as a≥50% decline (PSA-50) or ≥90% decline (PSA-90). Confirmed responses required consecutive measurements ≥21 d apart. Time-to-event endpoints were analysed using Kaplan-Meier and Cox models.

RESULTS AND LIMITATIONS: At 6 months, confirmed ALP-30 response was 56.5% with the combination versus 50.8% with enzalutamide alone. Median time to confirmed ALP-30 response was 2.4 versus 3.7 months (hazard ratio [HR] 1.41, 95% confidence interval [CI] 1.12-1.78; p = 0.003), and time to ALP normalisation was 2.0 versus 4.5 months (HR 2.05, 95% CI 1.46-2.88; p < 0.001). Confirmed PSA-90 response at 6 months was 50.5% versus 34.1% (p = 0.001), with median time to confirmed PSA-90 response of 5.6 versus 22.1 months (HR 1.48, 95% CI 1.13-1.93; p = 0.004). Limitations include the exploratory post hoc design, the absence of multiplicity adjustment, and the lack of an analysis linking biomarker responses to clinical outcomes.

CONCLUSIONS: Adding radium-223 to enzalutamide was associated with faster and more frequent ALP and deep PSA responses. These findings support additional antitumour activity of radium-223 when combined with enzalutamide.

PMID:42665513 | DOI:10.1016/j.euo.2026.08.001

Br J Anaesth. 2026 Aug 28:S0007-0912(26)00576-3. doi: 10.1016/j.bja.2026.07.026. Online ahead of print.

ABSTRACT

BACKGROUND: Pre-admission functional status might be associated with mortality in critically ill patients admitted to the ICU. With this systematic review, we aimed to investigate the association of pre-admission functional domains with mortality after ICU admission and which functional measures were used.

METHODS: We searched PubMed, Embase, and the Cochrane Register of Controlled Trials for studies of acutely admitted adult ICU patients reporting pre-admission functional status and mortality. Exploratory outcomes were mechanical ventilation, renal replacement therapy, delirium, ICU and hospital length of stay, discharge destination, and health-related quality of life. Screening, data extraction, and risk-of-bias evaluation were performed in duplicate. Certainty of evidence was assessed using Grading of Recommendations Assessment, Development, and Evaluation.

RESULTS: Of the 55 observational studies included, 21 contributed to the meta-analyses. Overall, 26.7% of the participants were deceased at variable follow-up (ICU to 1 yr). Frailty prevalence ranged from 3.6% to 76.8%, and functional dependency from 10.6% to 68.7%. Meta-analysis showed a risk ratio (RR) of 0.62 (95% confidence interval [CI] 0.58-0.67, P<0.01) for all-cause mortality between non-frail and frail participants and an RR of 0.47 (95% CI 0.40-0.54, P<0.01) between independent and dependent participants. No statistically significant association was found in the subgroup analysis of exploratory outcomes. Statistical and clinical heterogeneity were substantial, and overall certainty of evidence was very low.

CONCLUSIONS: Pre-admission frailty and functional dependency were associated with higher mortality after ICU admission. Overall, the evidence is very uncertain, and the true effect could differ substantially from our estimates.

PMID:42665487 | DOI:10.1016/j.bja.2026.07.026

Cardiovasc Revasc Med. 2026 Aug 24:S1553-8389(26)00373-8. doi: 10.1016/j.carrev.2026.08.014. Online ahead of print.

NO ABSTRACT

PMID:42665483 | DOI:10.1016/j.carrev.2026.08.014

Lancet Digit Health. 2026 Aug 28:101031. doi: 10.1016/j.landig.2026.101031. Online ahead of print.

ABSTRACT

BACKGROUND: RETFound, a self-supervised retina-specific foundation model, has shown potential in downstream tasks, but its performance in comparison with that of traditional deep-learning models remains unclear. We aimed to evaluate RETFound against three supervised deep-learning models (ResNet50, ViT-Base, and SwinV2) pretrained on images from ImageNet for the detection of several ocular (disease-related visual impairment, visually significant cataract, glaucoma, and diabetic retinopathy) and systemic (diabetes, hypertension, and chronic kidney disease) diseases.

METHODS: In this retrospective comparative study, all models were fine-tuned on different proportions of the training dataset (100%, 50%, and 20%) and on smaller datasets of fixed sizes (100, 200, and 400 images; 250 and 500 images for diabetic retinopathy) for all tasks. The fine-tuned models were tested on internal datasets from the Singapore Epidemiology of Eye Disease (SEED) study (1842-10 474 images) for all diseases except diabetic retinopathy, for which the Asia Pacific Tele-Ophthalmology Society 2019 dataset (1100 images) was used. Each model was also evaluated on external datasets, comprising population-based datasets (from the Beijing Eye Study, the Central India Eye and Medical Study, the Singapore Prospective Study, and the UK Biobank) and open-source datasets (Ocular Disease Recognition-5K [ODIR-5K], PAPILA, Glaucoma Grading from Multi-Modality Images [GAMMA], Indian Diabetic Retinopathy Image Dataset, and Methods to Evaluate Segmentation and Indexing Techniques in the Field of Retinal Ophthalmology-2). The performance of the models was assessed using 2000 pairwise bootstrap iterations of the area under the receiver operating characteristic curve (AUC) and compared using a two-tailed test with Bonferroni correction, with statistical significance defined as p<0·017 to account for the three pairwise comparisons between models.

FINDINGS: In internal testing, similar performance was observed for traditional models (AUC 0·914 [95% CI 0·899-0·928] to 0·965 [0·952-0·976]) and RETFound (0·938 [0·920-0·954] to 0·966 [0·951-0·978]) in the detection of ocular disease after fine-tuning on full datasets. With smaller datasets, the performance of all models was similar, except in the case of diabetic retinopathy (≤100 images per class) and glaucoma (≤400 images), for which ResNet50 was inferior to RETFound (all p≤0·0001), although the performance of SwinV2 remained similar to that of RETFound. Similar patterns were observed with external test sets. As an example for glaucoma detection, after fine-tuning on 400 images, RETFound had an AUC of 0·908 (95% CI 0·888-0·928) when tested on the internal SEED dataset and, for the external datasets, AUCs of 0·835 (0·816-0·855) when tested on ODIR-5K, 0·779 (0·731-0·826) on PAPILA, and 0·990 (0·974-1·000) on GAMMA, performing significantly better than ResNet50 (SEED p=0·0001; ODIR-5k p<0·0001; PAPILA p=0·0032; and GAMMA p=0·0010). For systemic diseases, RETFound consistently outperformed traditional deep-learning models in internal testing when fine-tuned on smaller datasets (≤400 images): for example, for the detection of hypertension when fine-tuned on 100 images, the AUC for RETFound in the SEED dataset was 0·705 (0·687-0·723), compared with 0·634 (0·615-0·654) for ResNet50 and 0·648 (0·628-0·667) for SwinV2 (both p<0·0001) and 0·657 (0·637-0·676) for ViT-Base (p=0·0003). When tested in the external UKBB dataset, RETFound achieved an AUC of 0·622 (95% CI 0·618-0·625) for the detection of hypertension when fine-tuned on 400 images, 0·599 (0·595-0·602) on 200 images, and 0·599 (0·595-0·603) on 100 images, significantly outperforming ResNet50 and SwinV2 when fine-tuned on 400, 200, and 100 images (all p≤0·0001) and ViT-Base when fine-tuned on 400 images (p<0·0001) and on 200 images (p=0·0002).

INTERPRETATION: Under this specific study design, the performance of traditional deep-learning models is similar to that of RETFound for ocular disease detection when fine-tuned on large datasets. By contrast, RETFound shows an advantage in the detection of systemic disease when fine-tuned on smaller datasets. These findings offer insights into the respective merits and limitations of traditional models and foundation models. Future benchmarking on broader datasets is warranted.

FUNDING: Agency for Science, Technology and Research (A∗STAR).

PMID:42665469 | DOI:10.1016/j.landig.2026.101031