Category: Statistics

J Bras Nefrol. 2026 Oct-Dec;48(4):e20260025. doi: 10.1590/2175-8239-JBN-2026-0025en.

ABSTRACT

INTRODUCTION: Pediatric rapidly progressive glomerulonephritis (RPGN) encompasses heterogeneous serology-based subtypes, including anti-glomerular basement membrane (anti-GBM), immune-complex-associated, and ANCA-associated (pauci-immune) RPGN. Although these subtypes differ in their underlying immune mechanisms, their ability to predict early renal recovery in children remains uncertain. This study aimed to evaluate the association between serology-based RPGN subtypes and early changes in renal function and tubular injury markers.

METHODS: This prospective cohort study included 30 children with newly diagnosed RPGN treated at Dr. Soetomo General Hospital. Patients were classified into anti-GBM, immune-complex-associated, or ANCA-associated RPGN based exclusively on serologic criteria. Estimated glomerular filtration rate (eGFR) and serum kidney injury molecule-1 (KIM-1) were measured at baseline and at 3 months after induction therapy. Primary outcomes were changes in eGFR (ΔeGFR) and serum KIM-1 (ΔKIM-1). Differences among subtypes were assessed using multivariate analysis of variance.

RESULTS: Of the 30 patients, 67% had immune-complex-associated RPGN, 20% had ANCA-associated RPGN, and 13% exhibited anti-GBM disease. The median age was 15 years. No statistically significant differences in ΔeGFR or ΔKIM-1 were observed among subtypes (MANOVA, p = 0.506), although numerical improvements varied across groups.

CONCLUSION: Serology-based RPGN subtype was not associated with early improvement in glomerular filtration or reduction in tubular injury markers in pediatric RPGN. Early renal recovery may be influenced more by baseline disease severity and therapeutic responsiveness than by serologic subtype classification alone.

PMID:42475735 | DOI:10.1590/2175-8239-JBN-2026-0025en

Genet Mol Biol. 2026 Jul 20;49Suppl 1(Suppl 1):e20250248. doi: 10.1590/1678-4685-GMB-2025-0248. eCollection 2026.

ABSTRACT

Ancient DNA research has expanded dramatically in recent years, transforming reconstructions of how and when humans settled the American continent. In this review, we synthesize evidence for genetic temporal continuity and discontinuity in Native American population history using mitochondrial DNA (mtDNA) from ancient and contemporary individuals. We systematically surveyed studies indexed in PubMed, ResearchGate, and Google Scholar, extending earlier compilations with publications through October 2025. For each population, we compiled sample sizes, mtDNA haplogroup frequencies, geographic coordinates, and associated archaeological and chronological information. These data were used to map the spatial distribution of founding mtDNA lineages, examine regional trajectories of haplogroup frequencies, and characterize patterns of mitochondrial population structure. Geographic distance showed a statistically detectable but limited association with mtDNA differentiation. Time-ordered haplogroup frequency series revealed region-specific dynamics, including long-term persistence of maternal lineages as well as marked episodes of turnover, some coincident with major cultural transitions. Genetic data were obtained from 315 studies. The dataset for contemporary populations included 23,315 individuals from 322 populations, while ancient DNA data included 4,192 individuals associated with 211 archaeological populations. Together, these data provide a comprehensive synthesis of mtDNA-based temporal and spatial patterns relevant to the peopling of the American continent.

PMID:42475729 | DOI:10.1590/1678-4685-GMB-2025-0248

Commun Dis Intell (2018). 2026 Jul 21;50. doi: 10.33321/cdi.2026.50.049.

ABSTRACT

BACKGROUND: In October 2024, Pilbara treatment guidance for uncomplicated urogenital gonorrhoea shifted from routine ZAP pack (amoxicillin 3 g and probenecid 1 g and azithromycin 1 g oral as a single treatment) to ceftriaxone-based LAC pack (ceftriaxone 500 mg in 2 mL 1% lignocaine intramuscularly and azithromycin 1 g oral, as a single treatment) in response to rising penicillinase-producing N. gonorrhoeae (PPNG) and the threat of imported ciprofloxacin resistance.

DESIGN: A retrospective clinical audit to describe demographics, compare treatment and resistance data collected for N. gonorrhoeae notifications for Pilbara health region residents meeting the surveillance case definitions in the Western Australian Notifiable Infectious Diseases Database (WANIDD) against clinical guidelines.

SETTING: All Pilbara health region resident N. gonorrhoeae notifications in the Western Australian Notifiable Infectious Diseases Database (WANIDD) from 1 July 2023 to 30 June 2024.

MAIN OUTCOME MEASURES: The proportion of notifications that reported treatment with a ZAP pack or LAC pack as per Western Australian and national clinical guidelines. Secondary outcomes included the proportion of notifications undertaken by the WA Country Health Service that reported test of cure at 1-2 weeks; the proportion that reported rescreening at 3 months post notification; and the proportion of notifications that reported PPNG and ciprofloxacin resistance.

RESULTS: A total of 188 N. gonorrhoeae notifications were received over the audit time frame. One hundred and twenty-seven notifications of a total of 156 N. gonorrhoeae notifications (81%) reported receiving treatment consistent with WA and National STI treatment guidelines, i.e. ZAP or LAC pack. Fifteen notifications of a total of 188 notifications (8%) reported detection of PPNG and 20 notifications of a total of 188 notifications (11%) reported ciprofloxacin resistance. For WA Country Health service notifications, 9 of 27 (33%) reported re-testing at 1-2 weeks or 3 months.

CONCLUSIONS: The majority of notifications (81%) reported N. gonorrhoeae treatment consistent with guidelines. A significant proportion of notifications (8%) indicated likely penicillin resistance due to the detection of PPNG. Reinforcing treatment consistent with the updated treatment guidelines of October 2024 for the Pilbara region will reduce the risk of ineffective treatment. Improving the rate of test of cure and test for reinfection (33%) would improve the likelihood of detecting treatment failure and detecting resistance.

PMID:42475726 | DOI:10.33321/cdi.2026.50.049

Commun Dis Intell (2018). 2026 Jul 21;50. doi: 10.33321/cdi.2026.50.045.

ABSTRACT

In 2020, the National Notifiable Diseases Surveillance System received 1,618 tuberculosis (TB) notifications, representing a notification rate of 6.3 per 100,0000 population. In 2019, there were 1,505 TB notifications, with a rate of 5.9 per 100,000 population. Australia has achieved and maintained good TB control since the mid-1980s, sustaining a low annual TB incidence rate of approximately five to six cases per 100,000 population. The number of multi-drug-resistant TB (MDR-TB) cases notified in Australia is lower than global rates, with approximately 2% of TB notifications per year classified as MDR-TB. In Australia, overseas-born people represent the majority of TB cases, accounting for 92% and 90% of TB notifications in 2020 and 2019, respectively. In 2020 and 2019, Aboriginal and Torres Strait Islander people recorded TB rates approximately four times higher than the Australian-born non-Indigenous population. Whilst Australia has achieved and maintained excellent control of TB, sustained effort is required to reduce local rates further, especially among Aboriginal and Torres Strait Islander populations, and to contribute to the World Health Organization’s goal to end the global TB epidemic by 2035.

PMID:42475724 | DOI:10.33321/cdi.2026.50.045

J Ultrasound Med. 2026 Jul 20. doi: 10.1002/jum.70372. Online ahead of print.

ABSTRACT

OBJECTIVES: To determine the incidence of complete and partial levator ani muscle (LAM) lesions using 3-dimensional endovaginal ultrasound (3D-EVUS) at 3-months postpartum in low-risk primiparous women and evaluate associations with perineal outcomes and early urogynecological parameters.

METHODS: Prospective interventional study of primiparous women with spontaneous vaginal delivery (March 2021-May 2023) at a tertiary urogynecology center in Rome, Italy (LATA protocol, IRB: 4202).

INCLUSION CRITERIA: >37 weeks, age 18-45 years, body mass index (BMI) ≥20, physiologic pregnancy.

EXCLUSION CRITERIA: age >45, BMI <20, fetal macrosomia >4500 g, forceps delivery. Perineal outcomes were recorded at delivery. Participants underwent 3D-EVUS and urogynecological assessment evaluating pelvic floor muscle function, command inversion, recruitment of auxiliary muscles, and hypertonicity at 3-months postpartum. LAM lesions were classified as partial (asymmetry, irregularity, ballooning) or complete/avulsion (detachment from pubic bone). Statistical analysis included logistic regression.

RESULTS: Of 350 eligible patients, 202 completed follow-up. At 3D-EVUS, 52% had no LAM lesions, 45% had partial lesions, 3% had avulsions. Intact perineum was observed in 16.2% without LAM lesions, 4.4% with partial lesions, 0% with avulsion (p = .018). Lacerations were more frequent with partial LAM lesions (73.6%) versus no lesion (59.0%) and avulsion (33.3%) (p = .027). Command inversion was associated with LAM lesions (p = .004). Urogenital hiatal area under Valsalva independently predicted LAM lesions (p < .001), with area >20.8 cm² demonstrating 82% specificity and 45% sensitivity.

CONCLUSIONS: 3D-EVUS enables the detection of subtle lesions frequently missed by conventional approaches. Partial LAM lesions are common in primiparous women after low-risk delivery, while avulsions remain rare. Command inversion and enlarged urogenital area provide valuable markers for early detection and intervention.

PMID:42475720 | DOI:10.1002/jum.70372

Omega (Westport). 2026 Jul 20:302228261470280. doi: 10.1177/00302228261470280. Online ahead of print.

ABSTRACT

Patient death may constitute an emotionally significant but often unrecognized source of occupational grief among healthcare professionals. This study examined disenfranchised grief after patient death and tested whether maladaptive coping strategies mediated its association with psychological well-being. In this cross-sectional pilot survey, 56 healthcare professionals with direct patient contact and professional experience with patient death completed an anonymous online questionnaire assessing disenfranchised grief after patient death, maladaptive coping strategies, and psychological well-being. Disenfranchised grief was negatively associated with psychological well-being and positively associated with maladaptive coping, while maladaptive coping was negatively associated with well-being. Mediation analysis indicated a statistically significant indirect association between disenfranchised grief and well-being through maladaptive coping. These findings suggest that the psychological consequences of patient death may be related not only to exposure to death itself, but also to whether grief is recognized and how professionals cope with it. The results point to the need for organizational support that acknowledges occupational grief and promotes adaptive coping after patient death.

PMID:42475713 | DOI:10.1177/00302228261470280

J Med Internet Res. 2026 Jul 20;28:e90023. doi: 10.2196/90023.

ABSTRACT

BACKGROUND: AI is rapidly transforming medical practice, with emerging applications in perioperative care and anesthesiology. However, the clinical implementation of AI-assisted decision-making systems in anesthetic management remains challenging and requires comprehensive evaluation.

OBJECTIVE: This study aimed to assess the performance and clinical applicability of an AI-assisted decision support system (ZW-AA-001) for general anesthesia management by comparing its decisions with those of experienced anesthesiologists across 6 medical centers.

METHODS: A multicenter retrospective study was conducted using perioperative data from 1008 patients who underwent elective noncardiac surgeries under total intravenous anesthesia. The AI system’s recommendations for anesthetic and hemodynamic medication adjustments were compared with anesthesiologists’ decisions. Key outcomes included decision concordance rates, temporal performance, and consistency across centers. Advanced statistical methods, including prevalence-adjusted and bias-adjusted κ (PABAK) and Gwet’s first-order agreement coefficient (AC1), were used to evaluate agreement metrics.

RESULTS: The study included 1008 patients, with a median age of 50 (IQR 37-59) years and female predominance (619/1008, 61.4%). During anesthesia maintenance, the AI system demonstrated moderate overall decision agreement with anesthesiologists (73.3%, 95% CI 72.4%-74.3%). Analysis of center-specific data revealed generally consistent performance across all 6 centers. For propofol management, high concordance was observed in dosage adjustment decisions (91.1%, 95% CI 90.4%-91.8%), though fair agreement was found in adjustment direction (68.6%, 95% CI 67.3%-69.8%). The AI system showed significantly faster decision-making time compared to anesthesiologists for the adjustment of propofol (pseudomedian difference -77.5, 95% CI -79.5 to -75.5 seconds; P<.001). Although esmolol-related decisions showed a numerically higher concordance of 71.4%, this was not statistically significant (PABAK=0.429; P=.21; AC1=0.622; P=.09). Decisions for atropine, ephedrine, and urapidil demonstrated substantially lower agreement (17.4%-29.8%). The AI system recommended hemodynamic interventions more frequently than anesthesiologists across all medications.

CONCLUSIONS: The AI-assisted decision support system demonstrated varying levels of concordance with anesthesiologists in managing surgery, with the highest agreement observed in propofol administration. However, the system’s lower agreement in hemodynamic medication management highlights the need for further optimization and validation. These findings underscore the potential of AI systems to enhance anesthetic decision-making, improve efficiency, and address workforce challenges in anesthesiology. Future research should focus on expanding the system’s capabilities, validating its performance in prospective clinical trials, and ensuring its integration into diverse clinical settings.

PMID:42475676 | DOI:10.2196/90023

J Med Internet Res. 2026 Jul 20;28:e85403. doi: 10.2196/85403.

ABSTRACT

BACKGROUND: Health literacy is crucial for pregnancy outcomes; yet, 15%-44% of pregnant women have low health literacy, negatively affecting maternal and fetal health. While pregnancy apps are increasingly used to support it, the psychological mechanisms through which they influence behavior remain unclear. Understanding these mechanisms is essential for designing effective interventions. Cognitive load theory (CLT) and the integrated model of cognitive-affective learning with media (ICALM) provide theoretical frameworks for understanding these digital interventions in pregnancy’s emotionally intense context.

OBJECTIVE: This study aimed to understand the psychological and social-cognitive pathways through which engagement with pregnancy apps may enhance health literacy and behaviors.

METHODS: This cross-sectional survey study included 998 pregnant and early postpartum women aged 18-45 years from the United States and analyzed the data using Bayesian Network (BN) modeling informed by CLT and ICALM. Participants were stratified into Pregnancy+ (Royal Philips) users (n=362), other pregnancy app users (n=507), and nonapp users (n=129). We measured digital engagement, emotions, health literacy levels, support levels and sources, and health behaviors, including physical activity, nutrition, and stress management. The BN model underwent systematic refinement through bootstrap resampling (n=1000) to evaluate arc strength, followed by k-fold cross-validation (k=5) to assess model generalizability and predictive performance.

RESULTS: In our study, pregnancy apps improve health literacy or behaviors, but not through direct pathways. Instead, they work through two indirect psychological pathways: (1) digital engagement related to positive emotions, which in turn is related to health literacy and stress management, and (2) digital engagement strengthened support networks, which in turn are related to health literacy. No direct pathways from digital engagement to health literacy or behaviors were retained. Pregnancy+ users demonstrated stronger adherence to these pathways compared with other app users and nonusers, by demonstrating more joyfulness (5.1 vs 4.7; P=.046), elevated support levels (4.1 vs 3.9; P=.03), and higher critical health literacy scores (8.4 vs 8.2 vs 7.7; P<.001). Pregnancy+ users also showed higher engagement frequencies (P<.001) and more frequently cited pregnancy apps as valuable information sources (78% vs 68%, P=.01) compared with users of other pregnancy apps.

CONCLUSIONS: This study reveals that pregnancy apps may enhance health literacy by fostering positive emotions and strengthening support networks. This finding challenges assumptions about digital health interventions and demonstrates that apps function as psychological support systems rather than mere information sources. The findings validate CLT and ICALM within pregnancy contexts, showing that emotionally supportive apps reduce irrelevant emotional processing that consumes cognitive capacity, thereby enhancing information retention. For practice, app developers should prioritize emotional support and social connection over content volume, while health care providers should recommend apps that enhance emotional well-being. This study demonstrates BN’s value for revealing complex psychological relationships in digital health contexts.

PMID:42475675 | DOI:10.2196/85403

JMIR Med Educ. 2026 Jul 20;12:e91345. doi: 10.2196/91345.

ABSTRACT

BACKGROUND: AI is transforming medicine by enhancing care, reducing administrative tasks, and facilitating research. AI also raises many concerns, including a lack of clinical context awareness, data dependence, and the absence of ethical judgment. As future practitioners, medical students must be prepared for these changes. Most studies assessing students’ attitudes and knowledge were conducted before AI became accessible and tailored to the needs of the population. Therefore, how medical students actually use AI remains largely unexplored.

OBJECTIVE: This study aimed to explore French medical students’ perceptions, attitudes, and use of AI.

METHODS: A mixed methods study was conducted in 2025 among French medical students in their clerkship year. An online survey included open-ended questions about the definition of AI and feelings toward AI, a Likert scale item to assess specific attitudes, and multiple-choice questions about student characteristics. Quantitative analysis was performed using Kruskal-Wallis tests, chi-square tests, and exploratory multivariable linear regression to examine associations between AI knowledge, attitudes, and student characteristics. Qualitative thematic analysis was conducted inductively on open-text responses regarding perceptions of AI, feelings, training expectations, and use.

RESULTS: Of the 1377 responses received, 1342 were included. Students had a median age of 23 (IQR 22-24) years and were predominantly in their fifth year. Only 5% (67/1342) provided a correct definition of AI, while 57.4% (770/1342) gave incorrect responses. Attitudes toward AI were generally positive, with a median score of 7 (IQR 5-8). Students with unknown AI definitions had significantly lower attitude scores (P=.02), although the magnitude of the difference was small (ε²=0.005). In multivariable analysis, belonging to the unknown AI definition category remained associated with a lower general attitude toward AI score compared with the incorrect category (regression coefficient β=-0.72, 95% CI -1.17 to -0.28; P=.001). Regarding education, 48.5% (651/1342) of students preferred AI training outside the formal curriculum. Qualitative analysis revealed 5 themes: representation, nuanced optimism, critical consideration, replacement, and AI use. Students describe AI as a robot, an improved search engine, or an unlimited data source. Their nuanced optimism blends enthusiasm for efficient patient care and the opportunity to focus more on the patient relationship, with concerns about dehumanization, energy costs, and skill regression. Critical consideration underscores distrust from ethical dilemmas and data security risks. Replacement concerns arise from shifting professional roles, though many believe human empathy remains irreplaceable. Regarding AI use, students highlight its potential for administrative aid, personalized training, and clinical support.

CONCLUSIONS: Medical students report generally positive but varied attitudes toward AI, despite having a limited understanding of its foundations. Ecological concerns, fears of skill loss, and ethical issues coexist with widespread self-directed use of AI for learning. These findings provide a descriptive baseline for future evaluations of AI-related training, particularly regarding critical appraisal, ethical issues, and self-directed AI use.

PMID:42475670 | DOI:10.2196/91345

Neurology. 2026 Aug 11;107(3):e218297. doi: 10.1212/WNL.0000000000218297. Epub 2026 Jul 20.

ABSTRACT

BACKGROUND AND OBJECTIVES: Mild cognitive impairment (MCI) is a high-risk stage for progression to dementia. The SUPERBRAIN-MEET trial previously demonstrated cognitive benefits of a multidomain lifestyle intervention (MLI) delivered through face-to-face sessions and digital platforms. The aim of this study was to examine whether the cognitive effects of the MLI varied according to sociodemographic characteristics, digital readiness, baseline cognitive status, and vascular risk profiles, in a prespecified subgroup analysis of the SUPERBRAIN-MEET randomized controlled trial.

METHODS: SUPERBRAIN-MEET was a 24-week, multicenter, outcome assessor-blinded, parallel-group randomized controlled trial conducted across 17 hospitals in South Korea. Adults aged 60-85 years with MCI were randomly assigned (1:1) to the MLI or control group. Subgroups were defined based on sociodemographic factors (sex, age, education, and living status), digital readiness (internet access, frequency of digital device use), cognitive status (MMSE score), and vascular risk profiles (body mass index [BMI], obesity status, smoking status, systolic and diastolic blood pressure, serum total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, fasting plasma glucose, and cardiovascular comorbidity). The primary outcome was the change in the repeatable battery for the assessment of neuropsychological status (RBANS) total index score from baseline to 24 weeks. Effect modification was assessed using linear mixed-effects models with interaction terms and false discovery rate correction.

RESULTS: Of 300 randomized participants, 277 participants (mean age, 72.9 years; 69.3% female) were included in the modified intention-to-treat analysis (142 in the MLI group and 135 in the control group). MLI significantly improved RBANS total index scores compared with control at 24 weeks (between-group difference, 4.17 points; 95% CI 1.92-6.43). No subgroup interactions remained significant after false discovery rate correction, indicating consistent effects across subgroups.

DISCUSSION: In this subgroup analysis of the SUPERBRAIN-MEET trial, the cognitive benefits of MLI were not significantly modified by sociodemographic factors, digital readiness, baseline cognitive status, or vascular risk profiles. These findings should be interpreted with caution, given the exploratory nature of subgroup analyses and limited statistical power. The results support the generalizability and scalability of technology-assisted multidomain lifestyle interventions for dementia prevention in older adults with MCI.

TRIAL REGISTRATION INFORMATION: The trial was registered at ClinicalTrials.gov (NCT05023057; submitted August 20, 2021; first patient enrolled September 3, 2021; URL: clinicaltrials.gov/study/NCT05023057).

PMID:42475653 | DOI:10.1212/WNL.0000000000218297