Category: Statistics

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

Genome Res. 2026 Aug 28:gr.282203.126. doi: 10.1101/gr.282203.126. Online ahead of print.

ABSTRACT

Hybridization between species is an important force in evolution, commonly modeled by the network multispecies coalescent. Reconstructing evolutionary histories under this model is computationally challenging, even for level-1 networks where hybridization events are isolated. Divide-and-conquer is a promising path forward, but current methods with statistical guarantees rely on an estimated tree of blobs (TOB) for the network, which compresses each nontree-like part into a single vertex. TOB reconstruction is itself challenging, with the only available method TINNiK having time complexity O(n ⁵ + n ⁴ k) for k genes and n species. Here, we present a new framework for scalable TOB reconstruction with statistical guarantees. Our approach operates by (1) seeking a refinement of the TOB and then (2) contracting edges in it. For step (1), we show that any optimal solution to Weighted Quartet Consensus is a TOB refinement almost surely, as the number of genes goes to infinity, motivating the use of methods, such as ASTRAL or TREE-QMC. For step (2), we show that applying the same hypothesis tests as TINNiK to just O(n) four-taxon subsets around each edge is sufficient for statistically consistent TOB reconstruction when the underlying network is level-1. Leveraging TREE-QMC for the first step gives our method time complexity O(n ³ k) and its name: TOB-QMC. On simulated data, TOB-QMC typically matches or exceeds TINNiK in accuracy while being more scalable. TOB-QMC also enables fast exploration of nontreelike evolution, as demonstrated through reanalysis of three phylogenomic data sets. Lastly, our study clarifies the theoretical utility of quartet-based species tree methods in the context of hybridization, which is critical given the recent result that ASTRAL can be misleading.

PMID:42665444 | DOI:10.1101/gr.282203.126

J Med Genet. 2026 Aug 28:jmg-2025-110787. doi: 10.1136/jmg-2025-110787. Online ahead of print.

ABSTRACT

BACKGROUND: Pathogenic missense variants in the MORC2 gene are associated with two distinct disorders: Charcot-Marie-Tooth disease type 2Z (CMT2Z) and the recently described DIGFAN (developmental delay, impaired growth, dysmorphic facies and axonal neuropathy) phenotype, which encompasses a broad range of clinical manifestations that vary significantly between individuals.

METHODS: Clinical and imaging data from 16 patients were collected. Western blot analysis was performed on 10 identified variants in affected patients as well as on two novel variants without clinical data. Those missense variants were introduced into the wild-type vector transfected into HEK293T cells, and western blot analysis was performed to assess protein expression level.

RESULTS: A total of 11 different missense variants in the MORC2 gene were identified in our cohort, including four novel variants. We demonstrate that early-onset MORC2-associated disorders segregate into two principal neurological phenotypes: a predominantly neuromuscular form and a central nervous system-predominant form. The p.Ser87Leu variant, which defines the neuromuscular cluster, was uniquely characterised by a significant reduction in MORC2 protein levels, distinguishing it mechanistically from other variants. Overall, western blot analysis revealed no statistically significant difference in protein expression levels between variants related to CMT2Z and DIGFAN cases.

CONCLUSION: A comparison of our patients with previously reported cases revealed an intriguing trend suggesting a probable dependence of the leading clinical features on specific variants in the MORC2 gene. Further accumulation of patient data is required to determine whether this observation correlates with other specific variants.

PMID:42665440 | DOI:10.1136/jmg-2025-110787

BMJ Lead. 2026 Aug 28:leader-2026-001625. doi: 10.1136/leader-2026-001625. Online ahead of print.

ABSTRACT

INTRODUCTION: Attitudes and clinical norms are shaped during medical training. Evidence from high-value care education suggests early exposure influences long-term practice patterns, making it an ideal target for curricula interventions. STARS (Students and Trainees Advocating for Resource Stewardship) is a learner-driven programme developed by Choosing Wisely Canada in 2015 and subsequently adopted in the USA. It exposes medical students to high-value care principles and activates them as change agents. We evaluated perceived sustained influence of the US STARS programme on attitudes, behaviours and professional development among medical students.

METHODS: We conducted a mixed-methods programme evaluation of approximately 20% of participants from the first six U.S. cohorts (n=579; 2018-2023). Participants completed an anonymous retrospective pre-post survey assessing familiarity with healthcare value concepts and STARS’ perceived influence. They also submitted annotated CVs reviewed for scholarly activities attributed to programme participation. Survey data were analysed using descriptive statistics.

RESULTS: Ninety-four of 118 invited participants (80% response rate) completed both components. Participants reported that STARS influenced how they consider healthcare costs in clinical decision-making, discuss medical overuse with peers and appreciate the impact of costs on patients. Many attributed subsequent leadership activities and scholarly output to their participation, including quality improvement projects, peer-reviewed publications and locally implemented educational initiatives.

CONCLUSION: This evaluation highlights the potential of learner-driven, longitudinal models such as STARS to foster durable engagement with high-value care education and catalyse professional development among medical trainees.

PMID:42665435 | DOI:10.1136/leader-2026-001625