Nevin Manimala

Am J Hum Biol. 2025 Nov;37(11):e70169. doi: 10.1002/ajhb.70169.

ABSTRACT

INTRODUCTION: This study aimed to evaluate potential relationships between the frequency of physical, and psychological or behavioral symptoms of premenstrual syndrome (PMS) in relation to body mass index (BMI) and body shapes in young women.

METHODS: In total, 22 of the most common PMS symptoms were assessed using a questionnaire, as well as self-reported height, weight, and body shape (using five silhouette types). A total of 6697 women aged 18-30 was included in the final statistical analysis. Symptom frequencies were measured using a 5-point Likert scale, and the mean frequency of occurrence (MFO) was calculated for all symptoms. Statistical analyses included analysis of variance (ANOVA), univariate logistic regression, and stepwise regression.

RESULTS: PMS symptom prevalence ranged from 61.0% to 97.2%. Overall, MFO of all physical PMS symptoms (M ± SD = 3.12 ± 0.75) was lower than the MFO of all psychological and behavioral symptoms (M ± SD = 3.29 ± 0.96; p < 0.001). Women with overweight or obesity, also those with an apple-shaped body, reported the highest symptom frequencies (MFO = 3.20-3.35), while underweight and rectangular-shaped women had the lowest MFO (2.98-3.25; p < 0.001). Stepwise analysis showed BMI and body shape were more strongly associated with physical symptoms than psychological or behavioral ones.

CONCLUSIONS: These results highlight the importance of body size and shape in understanding individual differences in PMS symptoms, suggesting that higher BMI and an apple-shaped body are more associated with PMS symptoms. Therefore, special attention should be paid to women with this body type, and they should be examined more thoroughly in order to take preventive measures in a timely manner.

PMID:41243766 | DOI:10.1002/ajhb.70169

Pharm Stat. 2025 Nov-Dec;24(6):e70052. doi: 10.1002/pst.70052.

ABSTRACT

In many acute myeloid leukemia (AML) studies, event-free survival (EFS) has been accepted as a primary efficacy endpoint. In those studies, the patients who do not achieve complete remission (CR) in the induction period are regarded as induction treatment failure (ITF). The recent FDA guidance on AML (2022) has clearly specified ITF as the event at Day 1 of randomization, considering the variability of length of individual induction treatment periods among studies. Xu et al. (2021) suggested decomposing the log-rank test statistic into the ITF portion, and the Non-ITF portion that is defined as the patients who achieved CR, and assumed proportional hazards for the Non-ITF portion. However, especially in the newly diagnosed AML study, there is some indication of the cured patients who achieve CR during the induction period. As a result, Non-zero ITF rates and cured patients invalidate the proportional hazards assumption and therefore, the conventional power calculation based on the number of events may be problematic in this setting. Our research follows the same decomposition of the log-rank test statistic as Xu et al. (2021) and suggests a new sample size calculation method accounting for the presence of both ITF and cured patients. The result shows that the analytically calculated power of log-rank test based on our proposal was very similar to the empirical power based on simulations in various finite sample settings and was also useful to protect from overestimation and underestimation of the required sample size in the presence of cure fraction.

PMID:41243764 | DOI:10.1002/pst.70052

Clin Transl Sci. 2025 Nov;18(11):e70403. doi: 10.1111/cts.70403.

ABSTRACT

This study aimed to identify predictors of critical outcomes, including mortality, in hospitalized COVID-19 patients treated with remdesivir, using statistical, machine learning, and Bayesian methods. A retrospective multicenter cohort of 1628 patients hospitalized between January 2021 and August 2022 was analyzed. Clinical data were collected from electronic medical records. Multivariable logistic regression, machine learning models (LightGBM, Elastic Net) with SHapley Additive exPlanations (SHAP), and Bayesian logistic regression were applied. Among the cohort, 14.5% experienced critical outcomes or death. Advanced age (≥ 65 years; aOR 3.950), atrial fibrillation (aOR 4.087), and kidney disease (aOR 1.939) were identified as significant predictors. Machine learning models achieved moderate predictive performance (AUROC: LightGBM 0.705, Elastic Net 0.698), with SHAP highlighting atrial fibrillation and age as key contributors. Bayesian analysis confirmed a strong association between atrial fibrillation and adverse outcomes (adjusted OR 5.121). Atrial fibrillation emerged as a consistent and strong predictor, underscoring its relevance in clinical risk assessment.

PMID:41243757 | DOI:10.1111/cts.70403

Artif Organs. 2025 Nov 17. doi: 10.1111/aor.70046. Online ahead of print.

ABSTRACT

BACKGROUND: We sought to estimate left ventricular assist device use (LVAD) with waitlist and post-transplant survival trends in patients supported on durable LVAD in relation to the UNOS donor heart allocation policy revision.

METHODS: Adult patients implanted with HeartMate II LVAD, HeartWare HVAD, or HeartMate 3 LVAD, and listed for isolated heart transplantation between October 18, 2013, and June 16, 2023, were identified in the UNOS database and were stratified into pre- and post-policy revision groups. Patients on temporary circulatory support, right, or biventricular assist devices, total artificial hearts, recipients of donation after circulatory death (DCD) hearts, and those undergoing simultaneous multiorgan transplants were excluded. Waitlist and post-transplant survival were compared between the groups.

RESULTS: Policy revision was associated with a decrease in LVAD use both at the time of listing (pre: 28% vs. post: 24.5%, p < 0.01) and at the time of transplant (pre: 45.8% vs. post: 31.7%, p < 0.01). For those listed with an LVAD, more patients eventually underwent transplantation (pre: 89.6% vs. post: 94.3%, p < 0.01) following the policy change. Overall waitlist and post-transplant survival among patients supported on LVAD worsened following the policy change, both showing statistical significance (p < 0.01).

CONCLUSION: In the post-policy era, a decline in durable LVAD utilization was observed, along with worse waitlist and post-transplant outcomes among LVAD-supported patients.

PMID:41243743 | DOI:10.1111/aor.70046

Glob Health Action. 2025 Dec;18(1):2586278. doi: 10.1080/16549716.2025.2586278. Epub 2025 Nov 17.

ABSTRACT

BACKGROUND: Adolescents in low- and middle-income countries often struggle to access sexual and reproductive health services (SRHS). To address this, the Ministry of Health, with support from Partners In Health, implemented Youth Corners in selected health facilities in Neno District to improve the utilisation of Youth-Friendly Health Services (YFHS).

OBJECTIVE: This study examines the role of Youth Corners in enhancing YFHS usage in Neno District, Malawi.

METHODS: A descriptive cross-sectional study was conducted by extracting data from Youth Corner registers and DHIS2 from health facilities between October 2022 and September 2023. Population estimates were obtained from the National Statistical Office projections. Descriptive statistics and chi-square tests were used to describe service utilization patterns, and binary logistic regression was used to assess the association between distance and service attendance.

RESULTS: During the study period, 1,877 young people aged 10-24 accessed YFHS, with 45% (n = 852) aged 15-19 and 57% (n = 1,063) female. They completed 2,869 visits, all receiving information and counselling. The utilisation rate was 829 visits per 1,000 young people aged 10-24. An association was found between distance, age, and attendance (p < 0.05). Adolescents aged 15-19 were less likely to attend youth corners (OR = 0.57, p = 0.003), and those living more than 10 km from facilities participated less frequently (OR = 0.59, p = 0.011).

CONCLUSION: While Youth Corners are highly suggested as a way for improving YFHS uptake among young people, their impact in Neno District was found to be suboptimal.

PMID:41243736 | DOI:10.1080/16549716.2025.2586278

J Forensic Sci. 2025 Nov 17. doi: 10.1111/1556-4029.70227. Online ahead of print.

ABSTRACT

Elevated beta-hydroxybutyrate (BHB) is a marker for ketoacidosis. Post-mortem values for the diagnosis of fatal ketoacidosis and the associated clinical and histologic findings are limited in the pediatric population. A retrospective case series of pediatric autopsy records and histology slides was conducted. Deaths occurring between 2010 and 2022 of children (ages<18 years) with an elevated BHB level (vitreous BHB >2 mmol/L or blood >200 mg/L) were analyzed. Histology of the heart, lung, liver, and kidneys was reviewed and scored. Five hundred twelve pediatric autopsies were conducted during the study period, of which 20 cases (3.9%) met the inclusion criteria. The age ranged from stillborn to 17 years, with a mean age of 6.3 years and a median age of 3.5 years. The mean concentration of vitreous BHB was 3.9 mmol/L (median 2.69; range 2.0-11.86 mmol/L; n = 17 cases) and the blood BHB had a mean of 416 mg/L (median 291; range from <50 mg/L to 1188 mg/L; n = 9 cases). Death was attributed to diabetic ketoacidosis, infection, malignancy, trauma, congenital heart disease, and drug toxicity. Histological changes were seen in all tissues examined in this pediatric population including hepatic steatosis (n = 17), glycogenated hepatocyte nuclei (n = 5), renal tubular vacuoles (n = 7) and heart vacuoles (n = 9). The only statistically significant correlation was found between vitreous BHB and renal tubular vacuoles (p = 0.014). Overall, elevated BHB levels were identified in blood and/or vitreous in fatal diabetic and non-diabetic cases, including infection. Diabetic ketoacidosis had the highest level of BHB at 11.86 mmol/L.

PMID:41243723 | DOI:10.1111/1556-4029.70227

Int J Psychol. 2025 Dec;60(6):e70123. doi: 10.1002/ijop.70123.

ABSTRACT

Successfully managing one’s unpleasant emotions despite adversities is important to help people maintain their well-being. Using daily diary assessment, we explored the role of Self-efficacy in Regulating Negative Affect (SRN) on Hedonic well-being (HWB), measured once a day over 21 days in a sample of 63 Italian young adults (mean age = 25.43, SD = 3.47; 67.7% women). Dynamic Structural Equation Modelling showed that there is a significant positive correlation between the spill-over effect from daily SRN_t-1 to HWB_t, with the carry-over effect of SRN (r = 0.625; 95% CI: [0.179, 0.850]). To explore this result more in depth, we performed a simple slope analysis that revealed that for those young adults with high carry-over of SRN over time, the spill-over effect from daily SRN_t-1 to HWB_t was positive and statistically significant (b = 0.247, 95% CI [0.032, 0.447]) compared to those young adults with low carry-over of SRN, which was nonsignificant (b = -0.092, 95% CI [-0.299, 0.137]). We discuss these findings in light of the potential role that SRN could play in people’s well-being during their everyday lives, which is in line with Bandura’s social cognitive theory. At the practical level, our results suggest that enhancing SRN might be beneficial to young adults’ HWB.

PMID:41243707 | DOI:10.1002/ijop.70123

Eur J Clin Invest. 2025 Nov 17:e70150. doi: 10.1111/eci.70150. Online ahead of print.

ABSTRACT

The C statistic, also known as the concordance index (C-index), is widely used in clinical research to assess the discriminative ability of risk prediction models. Its appeal lies in its intuitive interpretation and broad applicability, particularly in fields such as cardiovascular medicine and oncology, where accurate risk stratification is essential. However, despite its popularity, the C statistic has notable limitations that can undermine its utility in both research and clinical practice. Chief among these is its inherent conservativeness: the C statistic is often insensitive to meaningful improvements in model performance when new biomarkers or risk factors are added to an already robust model. This insensitivity stems from its rank-based nature, which focuses solely on the correct ordering of risk predictions rather than the magnitude of improvement. As a result, significant advances in risk estimation may be overlooked, potentially discouraging the adoption of clinically valuable innovations. Furthermore, the C statistic does not account for calibration-the agreement between predicted and observed outcomes-or the clinical consequences of misclassification. Alternative metrics, such as the Mean Absolute Difference (MAD), Brier score and Net Reclassification Improvement (NRI), offer complementary perspectives by capturing aspects of predictive accuracy and clinical relevance that the C statistic may miss. A comprehensive evaluation of risk models should therefore integrate these alternative measures to ensure that predictive tools are both statistically robust and clinically meaningful, ultimately advancing patient care and the practice of precision medicine.

PMID:41243705 | DOI:10.1111/eci.70150

Glob Health Action. 2025 Dec;18(1):2572010. doi: 10.1080/16549716.2025.2572010. Epub 2025 Nov 17.

ABSTRACT

BACKGROUND: Data are limited on the impact of chronic underlying conditions on COVID-19 treatment outcomes in sub-Saharan Africa.

OBJECTIVES: Determine the effect of underlying conditions on COVID-19 severity and treatment outcomes in Kenya.

METHODS: We conducted a retrospective cohort study using routine medical records from Kenya’s three large COVID-19 treatment centers. We examined two outcomes: mortality and clinical severity. Patients with lower respiratory tract illness without tachypnoea or difficulty in breathing were considered to have mild COVID-19. Underlying conditions were based on documentation in medical records. Logistic regression models assessed associations between underlying conditions and COVID-19 severity and mortality.

RESULTS: Among the 1,123 hospitalized COVID-19 patients included in the analysis, 59% (n = 664) had at least one underlying condition, 24.9% (n = 261) had severe disease, and 32.5% (n = 365) died. Hypertension (61.1%; n = 409), diabetes (38.9%; n = 258), and HIV (14.2%; n = 94) were the most common underlying conditions. Deaths were significantly higher among hospitalized COVID-19 patients with underlying conditions (35.4%) than those without (28.3%) (p = 0.01). The adjusted odds of severe COVID-19 were 50% higher among patients with hypertension (adjusted odds ratio [aOR] 1.50; 95% confidence interval [CI] 1.11-2.02). Mortality during COVID-19 hospitalization was nearly threefold higher among patients with heart disease (aOR 2.82; 95% CI 1.18-6.74) and 37% higher among patients with diabetes (aOR 1.37; 95% CI 1.00-1.88).

CONCLUSION: Patients with underlying conditions hospitalized for COVID-19 were more likely to die than those without. Hypertension was independently associated with disease severity, while heart disease and diabetes were independently associated with death during COVID-19 treatment.

PMID:41243672 | DOI:10.1080/16549716.2025.2572010

ACS Appl Mater Interfaces. 2025 Nov 17. doi: 10.1021/acsami.5c14008. Online ahead of print.

ABSTRACT

Domain-wall dynamics in ferroelectric materials are strongly position-dependent, since each polar interface is locked into a unique local microstructure. This necessitates spatially resolved studies of wall pinning using scanning-probe microscopy techniques. The pinning centers and pre-existing domain walls are usually sparse within the image plane, precluding the use of dense hyperspectral imaging modes and requiring time-consuming human experimentation. Here, a large-area epitaxial PbTiO₃ film on cubic KTaO₃ was investigated to quantify the electric-field-driven dynamics of the polar-strain domain structures using ML-controlled automated piezoresponse force microscopy. Analysis of 1500 switching events reveals that domain-wall displacement depends not only on field parameters but also on the local ferroelectric-ferroelastic configuration. For example, twin boundaries in polydomains regions, like a₁^–/c⁺∥a₂^–/c^–, stay pinned up to a certain level of bias magnitude and change only marginally as the bias increases from 20 to 30 V, whereas single-variant boundaries, like the a₂⁺/c⁺∥a₂^–/c^– stack, are already activated at 20 V. These statistics on the possible ferroelectric and ferroelastic wall orientations, together with the automated high-throughput AFM workflow, can be distilled into a predictive map that links domain configurations to pulse parameters. This microstructure-specific rule set forms the foundation for the design of ferroelectric memories.

PMID:41243655 | DOI:10.1021/acsami.5c14008