Tag: pubmed

Popul Stud (Camb). 2025 Nov 12:1-23. doi: 10.1080/00324728.2025.2573925. Online ahead of print.

ABSTRACT

In the absence of complete civil registration and vital statistics, Health and Demographic Surveillance Systems (HDSSs) are important sources of population-based data throughout sub-Saharan Africa. However, HDSS data on the vital status of newborns are often unreliable due to omission of those who were born and died between two rounds of data collection and are therefore never enumerated. This study investigates whether pregnancy registration improves estimation of under-five mortality (U5M) in three HDSSs in The Gambia, Kenya, and South Africa. We find that mortality is higher for children whose mother’s pregnancy was observed than for children who were first registered after birth. Cox proportional hazards models with inverse probability weights further suggest that this difference is probably due to improved ascertainment of deaths in pregnancy cohorts and unlikely to be driven by a selection effect. These results highlight the importance of pregnancy registration in HDSSs for the estimation of U5M.

PMID:41221637 | DOI:10.1080/00324728.2025.2573925

Int J Gynaecol Obstet. 2025 Nov 12. doi: 10.1002/ijgo.70620. Online ahead of print.

ABSTRACT

OBJECTIVE: To investigate the association between the first-trimester aggregate index of systemic inflammation (AISI) and the risk of gestational diabetes mellitus (GDM) in women with twin pregnancies, and to evaluate the predictive value of this novel index.

METHODS: A prospective cohort study was conducted in Maternal and Child Health Hospital of Hunan Province from January 2019 to December 2024, enrolling 335 women with twin pregnancies during their first trimester of pregnancy (7-14 weeks) after exclusions. Multivariable logistic regression, restricted cubic spline (RCS) models, receiver operating characteristic (ROC) curves, subgroup analyses, and sensitivity analyses were used to evaluate associations, diagnostic effects, and consistency of the study.

RESULTS: AISI was significantly and positively associated with the risk of GDM. After fully adjusted, the risk of GDM was significantly higher in the highest quartile compared with the lowest of AISI (odds ratio [OR]: 2.11, 95% confidence interval [CI]: 2.11 [1.07-4.19]; P = 0.032). A non-linear dose-response relationship was identified (P for nonlinear = 0.020). ROC analysis demonstrated a diagnostic accuracy with an area under the curve (AUC) of 0.61 (95% CI: 0.54-0.69, cutoff point = 610.65). The associations remained consistent in sensitivity analyses and most of the subgroup analyses (P for interaction >0.05).

CONCLUSION: Elevated first-trimester AISI levels are independently associated with an increased risk of GDM in twin pregnancies. AISI may serve as a potential indicator for early prediction of GDM in this unique population.

PMID:41221622 | DOI:10.1002/ijgo.70620

Analyst. 2025 Nov 12. doi: 10.1039/d5an00937e. Online ahead of print.

ABSTRACT

Global metabolic profiles of dried blood microsamples (BμS) were studied in comparison to conventional plasma and blood samples using Gas Chromatography-Mass Spectrometry (GC-MS). Venous blood from 10 healthy, overnight-fasted individuals was collected and used to produce dried microsamples on Whatman cards, Capitainer and Mitra devices. In parallel paired plasma samples were collected. The metabolite extraction protocol was optimized and methanol was selected as the extraction solvent. Twenty µL of the venous BμS and plasma were analyzed using the Fiehn GC-MS protocol which includes methoximation and trimethylsilylation derivatization steps. In an additional study, three paired finger capillary BµS (Mitra), liquid venous blood, and plasma metabolic profiles were evaluated. BµS devices, mainly the Mitra, provided equivalent or greater information than plasma, considering it had the highest mean abundance of features and most annotated metabolites (37) with highest abundance. Additionally, in the last study, 14 metabolites had statistically higher abundance in the capillary blood Mitra BμS compared to liquid venous blood and plasma. Overall, the results suggest that BμS is a viable alternative for untargeted blood metabolomics, providing comparable information. Since the different BμS devices capture different metabolic profiles, the choice of device for a research study should be carefully considered depending on one’s goals.

PMID:41221588 | DOI:10.1039/d5an00937e

Med Decis Making. 2025 Nov 12:272989X251388633. doi: 10.1177/0272989X251388633. Online ahead of print.

ABSTRACT

ObjectivesBayesian multiparameter evidence synthesis (B-MPES) can improve the reliability of long-term survival extrapolations by leveraging registry data. We extended the B-MPES framework to also incorporate historical trial data and examined the impact of alternative external information sources on predictions from early data cuts for a trial in metastatic non-small-cell lung cancer (mNSCLC).MethodsB-MPES models were fitted to survival data from the phase III CheckMate 9LA study of nivolumab plus ipilimumab plus 2 cycles of chemotherapy (NIVO+IPI+CHEMO, v. 4 cycles of CHEMO) in first-line mNSCLC, with 1 y of minimum follow-up. Trial observations were supplemented by registry data from the Surveillance, Epidemiology, and End Results program, general population data, and, optionally, historical trial data with extended follow-up for first-line NIVO+IPI (v. CHEMO) and/or second-line NIVO monotherapy in advanced NSCLC, via estimated 1-y conditional survival. Predictions from the 3 alternative B-MPES models were compared with those from standard parametric models (SPMs).ResultsB-MPES models better anticipated the emergent survival plateau with NIVO+IPI+CHEMO that was apparent in the 4-y data cut compared with SPMs, for which short-term extrapolations in both treatment arms were overly conservative. However, the B-MPES model incorporating NIVO+IPI data slightly overestimated 4-y NIVO+IPI+CHEMO survival owing to a confounding effect on estimated hazards that could not be accounted for a priori until later data cuts of CheckMate 9LA. Extrapolations were relatively robust to the choice of external data sources provided that the prior data had been adjusted to attenuate confounding.ConclusionsIncorporating historical trial data into survival models can improve the plausibility and interpretability of lifetime extrapolations for studies of novel therapies in metastatic cancers when data are immature, and B-MPES provides an appealing method for this purpose.HighlightsLeveraging historical trial data with extended follow-up to extrapolate survival from early study data cuts in a Bayesian evidence synthesis framework can realize anticipated longer-term effects that are characteristic of a novel therapy or class thereof.Using moderately confounded external data sources can improve the reliability of survival extrapolations from B-MPES models provided that the prior information is adjusted and rescaled appropriately, but it is essential to rationalize the implicit assumptions surrounding longer-term treatment effects in the current study.B-MPES models are an attractive option to conduct informed lifetime survival extrapolations based on transparent clinical assumptions via leveraging multiple external data sources, but model flexibility and a priori confidence in external data must be specified carefully to avoid overfitting.

PMID:41221583 | DOI:10.1177/0272989X251388633

Int J Gynaecol Obstet. 2025 Nov 12. doi: 10.1002/ijgo.70652. Online ahead of print.

ABSTRACT

OBJECTIVE: Selective reporting of research results based on statistical significance compromises research validity, potentially misleading clinical decision-making and future research. In obstetrics, the extent of this issue remains unclear. This study aimed to characterize the frequency, patterns, and temporal trends in the reporting of P-values, effect sizes, and statistically significant results in abstracts of obstetric studies from 2013 to 2023.

METHODS: We retrieved abstracts in the field of obstetrics between January 1, 2013, and December 31, 2023, from Medline, Embase and Cochrane CENTRAL. Automated text-mining was performed to detect and extract reporting of statistical inference, including P-values, effect sizes, Bayesian-related statistics, confidence intervals, and textual descriptions. The extracted statistical inferences were analyzed to assess trends over time and overall distribution, as well as specific patterns across different study designs.

RESULTS: A total of 23 167 eligible obstetric studies were identified from 46 788 abstracts. The proportion of abstracts reporting only P-values remained relatively stable over time, from 28.5% (95% confidence interval [CI]: 26.5%-30.5%) in 2013 to 27.6% (95% CI: 25.7%-29.5%) in 2023. There was a consistent rise in the proportion of abstracts reporting effect sizes, whether alone or alongside P-values, increasing from 22.1% (95% CI: 20.3%-24.0%) in 2013 to 39.5% (95% CI: 37.4%-41.7%) in 2023. Abstracts that reported neither P-values nor effect sizes decreased from 49.4% (95% CI: 47.2%-51.6%) in 2013 to 32.9% (95% CI: 30.8%-34.9%) in 2023. Most reported P-values clustered around common cut-offs, with 30.7% at 0.001 and 31.5% at 0.05. Among abstracts that reported statistical significance, 89.0% (95% CI: 87.4%-90.5%) reported a statistically significant difference, and the trend has remained stable over the past decade. Randomized controlled trials reported a lower proportion of statistically significant statements (82.4%, 95% CI: 75.9%-88.8%) than other study types.

CONCLUSION: Although the reporting of effect sizes has gradually increased over time, the use of standalone P-values remains common. The consistently high proportion of abstracts presenting at least one statistically significant result might reflect entrenched reporting practices in the field.

PMID:41221575 | DOI:10.1002/ijgo.70652

Indian J Pharmacol. 2025 Nov 1;57(6):409-413. doi: 10.4103/ijp.ijp_754_24. Epub 2025 Oct 12.

ABSTRACT

OBJECTIVE: To assess the knowledge, attitude, and practice (KAP) regarding reporting adverse events due to medical devices among healthcare workers in our hospital.

MATERIALS AND METHODS: A cross-sectional, observational, and questionnaire (KAP) study was conducted among healthcare professionals working in the various departments of our hospital. Healthcare professionals from different specialties who volunteered to participate in the study were enrolled. A total of 15 questions were included: 8 based on knowledge (7 scored), 2 on attitude, and 5 on practice. Statistical analysis was performed using Microsoft Excel® worksheet, Chi-square, and unpaired t-test. P < 0.05 was considered statistically significant.

RESULTS: A total of 370 responses were received. The knowledge of healthcare workers was found to be 73.57%. The mean score (out of 7) for doctors and paramedical staff was 5.78 ± 1.21 and 3.76 ± 1.50, respectively, indicating a wide knowledge gap between them (P < 0.05). Most healthcare workers (63%) reported witnessing fewer than 5 MDAEs. The majority (37.30%) mentioned that the cause of underreporting was a lack of knowledge. Out of all healthcare workers, 85.13% responded positively and are willing to report MDAEs in future, and most of them considered it important to report MDAEs.

CONCLUSION: Despite healthcare professionals having adequate knowledge and a positive attitude toward reporting, very poor reporting of MDAEs is observed. Lack of knowledge is a significant barrier leading to underreporting, and a substantial knowledge gap among healthcare professionals is evident.

PMID:41221570 | DOI:10.4103/ijp.ijp_754_24

J Psychopharmacol. 2025 Nov 12:2698811251389541. doi: 10.1177/02698811251389541. Online ahead of print.

ABSTRACT

BACKGROUND: Whether starting antidepressants (ADs) precipitates treatment-emergent mania (TEM) in young people with major depressive disorder (MDD) is still debated. A recent nationwide cohort study found no short-term risk, but its transferability to more diverse settings is unknown.

METHODS: Using the TriNetX global electronic-health-record network, we emulated a target trial in children and adolescents aged 6-17 years with a first MDD diagnosis (2016-2024). Patients who initiated an AD within 3 months formed the exposed cohort, and those who did not served as controls. After 1:1 propensity-score matching, 105,728 participants (52,864 per group) were followed for 3 months. The primary outcome was a composite of new mania/bipolar diagnosis or lithium initiation.

RESULTS: The exposed group had a significantly higher risk of the primary composite outcome compared to the unexposed group (45 vs. 27 events; Hazard ratio = 1.64, 95% confidence interval, 1.01-2.63, p = 0.041). However, it lost statistical significance when disaggregating the composite outcome, in landmark time-split analyses, and when restricting the cohort to patients with a prior history of healthcare encounters.

CONCLUSION: In a large, multinational real-world cohort, AD initiation was associated with a non-robust increase in short-term TEM risk. The observed association appeared susceptible to unmeasured confounding factors. These results underscore the importance of careful assessment and monitoring rather than indiscriminate AD use or avoidance in this population.

PMID:41221544 | DOI:10.1177/02698811251389541

Biomed Rep. 2025 Oct 22;23(6):195. doi: 10.3892/br.2025.2073. eCollection 2025 Dec.

ABSTRACT

Retinopathy of prematurity (ROP) is a proliferative vascular disease affecting preterm infants with incompletely developed retinal vasculature, characterized by abnormal vascular proliferation that can lead to retinal detachment and blindness. Given its impact on neonatal visual health, developing reliable risk prediction models for ROP has become crucial for optimizing clinical screening and intervention strategies. However, existing models exhibit substantial heterogeneity in methodology, validation, and performance, limiting their generalizability across diverse clinical settings. The present study aimed to evaluate and summarize the effectiveness of existing ROP risk prediction models in preterm infants through a systematic review and meta-analysis, with the goal of providing reliable clinical screening tools based on effectiveness metrics. A systematic search was conducted across PubMed, Cochrane Library, Web of Science and Embase databases using a strategy that combined MeSH terms and free-text words to identify literature associated with risk prediction models for ROP in preterm infants. The risk of bias was assessed using the PROBAST tool. Statistical analysis involved data synthesis, heterogeneity testing, subgroup and sensitivity analyses, and publication bias assessment. A total of 492 relevant articles were retrieved; following deduplication and screening, 28 articles involving ROP risk prediction models were included. The included studies were published between 2009 and 2025, with sample sizes ranging from 90 to 22,569 participants, and a total sample size of 72,991. A total of 16 studies did not specify the validation method, five conducted external validation, two performed both internal and external validation, and five performed only internal validation. PROBAST assessment revealed that all included models had a moderate risk of bias, primarily attributed to the retrospective nature of the study design, inconsistent variable measurement and inadequate control of confounding factors. Meta-analysis showed that the pooled area under the receiver operating characteristic curve (AUC) was 0.87 (95% CI: 0.34; 0.99), indicating good discriminative ability of the models. However, significant heterogeneity was observed (I²=99.2%, P<0.05). Subgroup analysis by model type demonstrated significant heterogeneity in both traditional statistical (I²=92.2%) and machine learning models (I²=97.3%). Subgroup analysis by study region showed no significant heterogeneity in studies from South America (I²=0%), while high heterogeneity was found in studies from Asia and North America + Europe (I²=96.6 and 93.6%, respectively). This may be associated with cross-regional differences in population characteristics (such as ethnicity and disease spectra) and variations in medical standards. Funnel plot and Peters’ bias test indicated high reliability of the overall study conclusions, and the results of the sensitivity analysis were stable. However, some studies had small sample sizes and single-center designs, leading to selection bias. Additionally, multiple studies lacked model validation, and samples were limited to specific regions, failing to cover diverse healthcare settings and ethnic groups. In conclusion, current ROP risk prediction models for preterm infants exhibit good clinical application potential, with certain discriminative and predictive abilities, which can provide references for clinical screening. However, the risk of bias and insufficient validation limit their generalization ability. Future studies should expand sample sizes through prospective designs, strengthen external validation and optimize model development to improve prediction accuracy and universality, addressing the identified risks of bias and limited generalizability.

PMID:41221538 | PMC:PMC12598925 | DOI:10.3892/br.2025.2073

Front Med (Lausanne). 2025 Oct 27;12:1677818. doi: 10.3389/fmed.2025.1677818. eCollection 2025.

ABSTRACT

BACKGROUND: The triglyceride-glucose (TyG) index, a surrogate marker of insulin resistance, has been linked to various diabetic complications. However, its association with diabetic retinopathy (DR) remains inconsistent. We conducted a systematic review and meta-analysis to evaluate the relationship between TyG index levels and the risk of DR.

METHODS: We searched PubMed, Scopus, and Web of Science from inception to July 2025 for observational studies reporting the association between TyG index and DR in adults with type 1 or type 2 diabetes. Two reviewers independently screened studies, extracted data, and assessed risk of bias using the Agency for Healthcare Research and Quality (AHRQ) checklist and Newcastle-Ottawa Scale. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) were calculated using a random-effects model. Heterogeneity was evaluated with the I² statistic. Publication bias was assessed via funnel plots and Egger’s test. Subgroup and meta-regression analyses were conducted to explore heterogeneity.

RESULTS: Sixteen studies with a total of 33,436 participants were included. The pooled OR for the association between higher TyG index and DR was 1.89 (95% CI: 1.27-2.82) when TyG was treated as a categorical variable, and 1.57 (95% CI: 1.25-1.98) when treated as continuous. Significant heterogeneity was observed (I ² > 87%). Subgroup analyses revealed stronger associations in studies with smaller sample sizes and higher male proportions. Meta-regression showed that male proportion accounted for 48.71% of the heterogeneity. In categorical analyses, funnel-plot asymmetry and Egger’s test indicated small-study effects; after trim-and-fill adjustment the pooled effect attenuated and was no longer significant, suggesting sensitivity to publication bias.

CONCLUSIONS: While higher TyG levels correlate with DR-particularly when modeled continuously-the signal is heterogeneity- and bias-sensitive in categorical analyses. Our moderator analyses newly indicate a sex-composition effect, and the current lack of harmonized clinical TyG thresholds limits immediate translation.

PMID:41221513 | PMC:PMC12597932 | DOI:10.3389/fmed.2025.1677818

Med Pharm Rep. 2025 Oct;98(4):475-485. doi: 10.15386/mpr-2933. Epub 2024 Oct 30.

ABSTRACT

BACKGROUND AND AIM: Aneuploidies are rare diseases with great impact on an individual’s life, as well as on their families, the reason why prenatal screening is performed, allowing families to take an informed decision. Initial prenatal screening includes the double test, triple test, non-invasive prenatal testing and ultrasonography. Among these, ultrasonography plays an important role giving information regarding an elevated risk for aneuploidies.

METHODS: Eighty-four pregnant women who underwent prenatal screening were included in this study, of whom 9 cases were diagnosed with an aneuploidy. A statistical analysis was performed to identify possible associations between morpho-fetal characteristics, estimated fetal growth, and other parameters, such as maternal characteristics or gestational age.

RESULTS: As expected, based on the data available in the literature, an advanced maternal age was observed in the high-risk group, compared to the low-risk one (the risk was evaluated after the initial screening and influenced the decision of a further amniocentesis). A good correlation was observed in this study between the fetal biometric parameters and gestational age, as well as between fetal biometric parameters and maternal weight gain in healthy pregnancies, while low or no correlations were found in the aneuploid pregnancies.

CONCLUSIONS: The results of our study highlight the importance of ultrasonography evaluation and reveal possible correlations of fetal parameters with maternal characteristics. These findings, together with already well-established parameters, might suggest stronger clusters of soft markers and bring supplementary information regarding the risk level of pregnancy, in order to perform a better assessment of cases where invasive diagnosis is required.

PMID:41221453 | PMC:PMC12600065 | DOI:10.15386/mpr-2933