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PubMed2025

Artificial Intelligence in Diagnosing Depression Through Behavioural Cues: A Diagnostic Accuracy Systematic Review and Meta-Analysis.

AIM: To synthesise existing evidence concerning the application of AI methods in detecting depression through behavioural cues among adults in healthcare and community settings. DESIGN: This is a diagnostic accuracy systematic review. METHODS: This review included studies examining different AI methods in detecting depression among adults. Two independent reviewers screened, appraised and extracted data. Data were analysed by meta-analysis, narrative synthesis and subgroup analysis. DATA SOURCES: Published studies and grey literature were sought in 11 electronic databases. Hand search was conducted on reference lists and two journals. RESULTS: In total, 30 studies were included in this review. Twenty of which demonstrated that AI models had the potential to detect depression. Speech and facial expression showed better sensitivity, reflecting the ability to detect people with depression. Text and movement had better specificity, indicating the ability to rule out non-depressed individuals. Heterogeneity was initially high. Less heterogeneity was observed within each modality subgroup. CONCLUSIONS: This is the first systematic review examining AI models in detecting depression using all four behavioural cues: speech, texts, movement and facial expressions. IMPLICATIONS: A collaborative effort among healthcare professionals can be initiated to develop an AI-assisted depression detection system in general healthcare or community settings. IMPACT: It is challenging for general healthcare professionals to detect depressive symptoms among people in non-psychiatric settings. Our findings suggested the need for objective screening tools, such as an AI-assisted system, for screening depression. Therefore, people could receive accurate diagnosis and proper treatments for depression. REPORTING METHOD: This review followed the PRISMA checklist. PATIENTS OR PUBLIC CONTRIBUTION: No patients or public contribution.

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PubMed2026

The application of artificial intelligence in healthcare practice: A mapping review of systematic reviews.

Artificial intelligence (AI) is rapidly transforming healthcare practice, with growing evidence supporting its use in diagnosis, prognosis, treatment planning, and operational decision-making. The proliferation of systematic reviews in recent years underscores the need for an updated synthesis of the literature to inform research, policy, and practice. We searched PubMed, Web of Science, Scopus, IEEE Xplore, and CINAHL for systematic reviews and meta-analyses published between 2019 and February 2026. Eligible reviews focused on AI applications in healthcare practice, were peer-reviewed, and written in English. A total of 368 reviews met the inclusion criteria. Publication volume increased steadily, peaking in 2025. AI research was concentrated in high-density domains, such as radiology, oncology, and critical care. Across reviews, diagnostic imaging, electronic health record (EHR) data, and biomarkers/laboratory results accounted for 68% of training data sources, though newer data types, such as wearable device and sensor data, emerged from 2022 onward. Diagnosis, prognosis, and treatment comprised over 80% of AI applications, with novel uses emerging in recent years, such as AI-assisted clinical documentation (e.g., ambient documentation tools) and patient education. Ethical concerns were reported in 78.5% of reviews, with privacy, model accuracy, data and algorithmic bias, and explainability as recurrent themes. The proportion of reviews reporting ethical concerns increased from 2021 to 2025. AI applications in healthcare are expanding in scope, diversifying in data sources, and evolving toward novel clinical and operational uses. The human-centered AI or augmented intelligence paradigm, integrating computational precision with clinical expertise, holds significant promise but will require parallel advances in governance, regulatory frameworks, and ethical oversight to ensure safe adoption.

Artificial Intelligence↗

PubMed2026

The future of pediatric vesicoureteral reflux management.

BACKGROUND AND OBJECTIVE: Vesicoureteral reflux (VUR) is a common condition in pediatric urology, yet important uncertainties persist regarding risk stratification, imaging strategies, and prevention of long-term renal damage. Emerging technologies may help address these challenges. This review provides a forward-looking overview of recent advances in artificial intelligence (AI) and immunomodulation that may influence future management of pediatric VUR. METHODS: A forward-looking literature review was performed using the PubMed database (January 2000-March 2025), focusing on studies addressing AI, immunomodulation, or vaccination in the context of VUR and urinary tract infections. Criteria of inclusion were the relevance to pediatric VUR, the novelty of the proposed concept, the potential clinical implications and, for the AI literature, the existence of a clinical evaluation of the algorithm on a dataset from patients. KEY FINDINGS AND LIMITATIONS: AI-based models show promising performance in supporting clinical decision-making, including prediction of the need for voiding cystourethrography, automated grading of VUR, estimation of recurrent urinary tract infection risk and prediction of chemoprophylaxis. These tools may facilitate more individualized diagnostic and therapeutic strategies, although current evidence is largely retrospective and requires prospective validation. Immunization and immunomodulatory approaches aim to reduce infection burden and modulate inflammatory pathways associated with renal scarring. While early experimental and adult clinical data are encouraging, pediatric-specific evidence remains limited, and clinical applicability in children with VUR is not yet established. CONCLUSION: Artificial intelligence and immunologically targeted strategies represent complementary, emerging approaches that may contribute to more personalized management of pediatric VUR. At present, both should be regarded as exploratory tools whose clinical impact will depend on further validation and appropriately designed pediatric studies.

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PubMed2026

Cardiorespiratory training for people with stroke.

RATIONALE: Low levels of cardiorespiratory fitness are common after stroke and are associated with post-stroke disability and increased risk of secondary stroke. Cardiorespiratory training interventions aim to increase cardiorespiratory fitness, improve physical function, reduce disability, and help prevent future strokes. Clinical guidelines recommend exercise as part of lifestyle modification for secondary prevention, and strongly recommend exercise for rehabilitation. This review is one of three reviews that were originally a single review on physical fitness training for stroke. OBJECTIVES: The primary objective of this review was to determine whether cardiorespiratory training after stroke has an effect on death, disability, adverse events, risk factors, fitness, walking, and indices of physical function when compared to a non-exercise control. SEARCH METHODS: In April 2025, we searched nine bibliographic databases and two trials registers to identify studies for inclusion in the review. We checked reference lists, tracked citations, and contacted experts. ELIGIBILITY CRITERIA: We included randomised controlled trials comparing cardiorespiratory training interventions with usual care, no intervention, or a non-exercise intervention in people with stroke. OUTCOMES: Our critical outcomes were death, disability, adverse events, risk factors, fitness, walking, and indices of physical function, assessed at the end of the intervention and the end of the longest follow-up. RISK OF BIAS: We used the Cochrane RoB 1 tool to assess the risk of bias in the included studies. SYNTHESIS METHODS: The studies evaluated different comparisons (e.g. cardiorespiratory training versus no intervention/waiting list control or versus attention control or versus usual care), which we synthesised into a single comparison: cardiorespiratory training versus control. We used random-effects meta-analysis on arm-level data (risk difference (RD) for dichotomous data, and mean difference (MD) or standardised mean difference (SMD) for continuous data, with 95% confidence intervals (CIs)). For outcome data that we did not meta-analyse, we followed Synthesis Without Meta-analysis (SWiM) guidance. We used GRADE to assess the certainty of the evidence for critical outcomes. INCLUDED STUDIES: We included 53 studies (2672 participants, with an average age of 61.9 years). Most studies recruited ambulatory participants in the early subacute (7 days to 3 months) or chronic (> 6 months) phases of recovery. Exercise duration recommendations were met in 49 studies, and frequency recommendations in 48. Twenty-eight studies lacked balanced exposure between groups. Programme duration was 12 weeks or more in 16 studies (maximum: 24 weeks). Sixteen studies had a post-intervention follow-up period (12 weeks to 12 months from baseline). One study planned a six-month follow-up but did not report it. SYNTHESIS OF RESULTS: Cardiorespiratory training does not increase or decrease deaths at the end of intervention (RD 0.00, 95% CI -0.01 to 0.01; 36 studies, 1563 participants; high-certainty evidence) or the end of follow-up (RD -0.00, 95% CI -0.02 to 0.02; 10 studies, 713 participants; high-certainty evidence). Cardiorespiratory training may improve indices of disability slightly at the end of intervention (SMD 0.35, 95% CI 0.12 to 0.57; 17 studies, 1073 participants; very low-certainty evidence), but the evidence is very uncertain. Re-expressed using the Barthel Index (0 to 20), the equivalent effect is MD 1.68, 95% CI 0.59 to 2.74. It is unclear if the effect is clinically meaningful (the minimal clinically important difference (MCID) is +1.85). The effect is unclear at the end of follow-up (SMD -0.14, 95% CI -0.36 to 0.08; 5 studies, 347 participants; low-certainty evidence). Cardiorespiratory training does not increase or decrease the incidence of secondary cardiovascular or cerebrovascular events at the end of intervention (RD -0.00, 95% CI -0.03 to 0.02; 8 studies, 544 participants; high-certainty evidence) and probably does not affect them at the end of follow-up (RD -0.02, 95% CI -0.08 to 0.04; 4 studies, 412 participants; moderate-certainty evidence). It is very uncertain whether cardiorespiratory training affects systolic blood pressure (mmHg) at the end of intervention (MD -2.12, 95% CI -5.81 to 1.57; 9 studies, 535 participants; very low-certainty evidence) (MCID -2 mmHg) or follow-up (MD 0.93, 95% CI -4.30 to 6.16; 3 studies, 155 participants; very low-certainty evidence); the 95% CIs include the MCID. Cardiorespiratory training probably results in a slight improvement in cardiorespiratory fitness (VO2 ml/kg/min) at the end of intervention (MD 2.37, 95% CI 1.39 to 3.36; 13 studies, 608 participants; moderate-certainty evidence); it is unclear if the effect is clinically meaningful (MCID +3.5 ml/kg/min). The effect may be similar at the end of follow-up (MD 2.76, 95% CI 1.36 to 4.16; 5 studies, 237 participants; low-certainty evidence). Subgroup analysis favoured longer interventions. Cardiorespiratory training probably results in a slight increase in comfortable walking speed (metres per second) at the end of intervention (MD 0.08, 95% CI 0.04 to 0.12; 16 studies, 647 participants; moderate-certainty evidence), but the effect is not clinically meaningful (MCID +0.13). The effect is unclear at the end of follow-up (MD 0.02, 95% CI -0.05 to 0.10; 3 studies, 182 participants; low-certainty evidence). Cardiorespiratory training may improve indices of balance at the end of intervention (SMD 0.31, 95% CI 0.15 to 0.47; 18 studies, 772 participants; very low-certainty evidence), but the evidence is very uncertain. Re-expressing using the Berg Balance Scale, the equivalent effect is MD 2.09, 95% CI 1.10 to 3.07; and it is unclear if it is clinically meaningful (MCID of +2). The effect is unclear at the end of follow-up (MD 0.90, 95% CI -1.32 to 3.12; 6 studies, 253 participants; low-certainty evidence). Overall, our certainty about the evidence is limited for most outcomes by imprecision (small number of studies and participants) or risks of bias (e.g. imbalanced exposure doses) or both. AUTHORS' CONCLUSIONS: Cardiorespiratory training after stroke does not affect mortality or the incidence of secondary events at the end of the aerobic exercise training programme or end of follow-up. It may increase fitness, reduce disability, increase walking speed, and improve balance at the end of intervention, but it is unclear if these improvements are clinically meaningful. Further well-designed randomised trials are needed to fully understand the potential benefits and long-term effects of cardiorespiratory training and the optimal exercise prescription. FUNDING: No dedicated funding REGISTRATION: Protocol (and previous versions) available via DOI 10.1002/14651858.CD003316.

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PubMed2026

Artificial intelligence (AI) uses in stereotactic radiosurgery (SRS): diagnosis with brain metastasis (BM) - A systematic review.

BACKGROUND: Brain metastases (BM) are the most common intracranial tumors in adults, and stereotactic radiosurgery (SRS) has become a mainstay of management. However, several diagnostic challenges persist in the SRS pathway, particularly the differentiation of radiation necrosis (RN) from true tumor progression, which conventional MRI and even advanced imaging techniques often cannot reliably resolve. Recent advances in artificial intelligence (AI) offer the potential to address these diagnostic limitations. This systematic review synthesizes current literature on AI applications for MRI-based diagnostic decision support in BM patients undergoing SRS, with a focus on radiomics and deep learning tools for distinguishing RN from progression, classifying molecular and histologic subtypes, and predicting treatment response. METHODS: A systematic review was performed in accordance with PRISMA guidelines. PubMed, Web of Science, and Scopus were searched using a targeted query combining terms related to AI, brain metastasis, diagnosis or imaging, and SRS. After screening 483 records and applying strict inclusion and exclusion criteria, 18 studies published between 2015 and 2025 were included. Data were extracted on study design, cohort characteristics, imaging modality, AI methodology, validation strategy, and reported diagnostic performance. RESULTS: Among the 18 included studies, AI models demonstrated strong performance across diagnostic tasks in the BM-SRS pathway. The differentiation of RN from true tumor progression was the most extensively studied application, addressed by 14 of 18 studies, with reported AUCs ranging from 0.71 to 0.94. Support vector machines, random-forest ensembles, convolutional neural networks, and transformer-based multimodal architectures were widely used. The literature evolved from single-sequence radiomic classifiers in 2018 to multimodal deep learning frameworks fusing imaging with clinical and genomic data in 2025. Contrast-enhanced T1-weighted MRI was the dominant imaging input, and texture-based radiomic features (GLCM, GLSZM, GLDM, and wavelet-derived features) were the most consistently predictive. The highest-performing models reached AUCs of 0.85-0.91 through multimodal integration of imaging with clinical and genomic features, and consistently outperformed expert neuroradiologist read on matched cases. Remaining studies addressed longitudinal segmentation-based detection of local failure and adverse radiation effects, BRAF mutation status in melanoma BM, early Gamma Knife treatment response, and primary tumor histology classification, with more variable performance. CONCLUSION: AI models, particularly those integrating MRI-derived radiomic features with clinical and genomic data, show high accuracy in supporting diagnostic decisions for BM patients treated with SRS. The post-SRS differentiation of radiation necrosis from true tumor progression has reached the greatest level of maturity and is closest to clinical translation, with potential to reduce unnecessary biopsies, personalize surveillance intervals, and rationalize treatment-pathway decisions. Other diagnostic applications, including molecular subtyping and primary tumor histology classification, remain exploratory and require further multicenter validation. Integration of AI tools into multidisciplinary tumor-board workflows, combined with prospective validation and standardized reporting, will be essential to realize the full clinical benefits of AI in SRS for brain metastases.

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PubMed2026

Comparison of summative assessments between simulated electronic health records versus traditional paper-based patient cases: A non-inferiority randomized controlled trial.

INTRODUCTION: Electronic health records are fundamental to contemporary pharmacy practice, yet evidence supporting their use in pharmacy education is lacking. This single-center, non-inferiority randomized controlled trial with blinded outcome assessment evaluated whether delivering patient cases via a simulated academic EHR (aEHR) was non-inferior to a traditional paper-based format in student exam performance. METHODS: 53 third-year PharmD students at the University of British Columbia were randomized 1:1 to complete a mock summative examination using either the aEHR or paper-based case delivery, stratified by self-reported EHR comfort level. The primary outcome was mean written exam score (%). Non-inferiority was pre-specified at a margin of 14%. Adjusted linear regression was used for the primary analysis, with a multiple imputation sensitivity analysis. Student perceptions were explored through post-exam focus groups analyzed using inductive thematic analysis. RESULTS: 42 students (21 per group) completed the exam and were included in the primary analysis. Mean scores were 66% (SD 11) in the aEHR group and 68% (SD 10) in the paper group. The adjusted mean difference (paper minus aEHR) was -2.2% (95% CI -9.2% to +4.8%), satisfying non-inferiority but not superiority. Sensitivity analysis (n = 53) yielded consistent results (-2.3%; 95% CI -7.1% to +4.1%). Focus groups revealed initial student anxiety with the aEHR but recognized its alignment with clinical practice. DISCUSSION: These findings support the feasibility of integrating simulated EHRs into summative pharmacy assessments without compromising performance. CONCLUSION: Simulated EHRs are a non-inferior assessment medium compared with paper-based formats and represent a viable step toward technology-driven pharmacy practice environments.

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PubMed2026

The potential of clustering methods for pre-test triage in sleep medicine: A systematic review.

Sleep disorders exhibit substantial heterogeneity, and traditional classifications may not fully capture clinically relevant subtypes. Clustering techniques can identify patient subgroups that improve phenotypic characterization and may support personalized management. This systematic review evaluated the application of clustering in sleep medicine, with particular focus on its potential use as a pre-test triage tool prior to formal sleep testing. PubMed/MEDLINE, Embase, Web of Science, and Scopus were searched to February 2025. Eligible studies applied clustering to classify sleep disorders in adults. Two reviewers independently conducted screening, data extraction, and risk-of-bias assessment using QUADAS-2. The protocol was registered on PROSPERO. Fifty-one studies (1983-2025) were included, predominantly focused on obstructive sleep apnea (OSA) (n = 38, 74%). Hierarchical clustering (n = 20) and K-means clustering (n = 14) were the most frequently used techniques. Internal validation was reported in only 18% of studies, and external validation was reported in only 1 study. Seven studies relied exclusively on baseline clinical, demographic, or questionnaire data, representing pre-test scenarios, whereas most incorporated polysomnography-derived variables, limiting their applicability to early clinical stratification. Hierarchical clustering was the most commonly applied method; however, the overall lack of validation limits confidence in the robustness and clinical applicability of identified phenotypes. The potential role of clustering as a pre-test triage strategy remains largely unexplored, as most studies focused on post-diagnostic phenotyping and were affected by incorporation bias. Future research should prioritize pre-test clinical variables, rigorously validate internally and externally, and adopt standardized methodological and reporting practices to facilitate clinical translation.

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PubMed2026

A systematic approach to standardizing the visual appearance of endometriotic lesions for artificial intelligence recognition.

INTRODUCTION: Numerous studies have shown that the diagnostic performance and reproducibility of visual recognition of endometriosis during laparoscopy are poor. The use of artificial intelligence (AI) seems relevant for exhaustive lesion recognition. Standardization of the visual classification of lesions, in the form of an ontology, is an essential prerequisite to enable medical experts to annotate surgical data consistently and subsequently allow engineers to train and build an artificial intelligence tool for endometriosis recognition. MATERIAL AND METHODS: A systematic search was conducted in the MEDLINE (via PubMed), EMBASE, and the Cochrane Library databases up to May 2022, aiming to identify studies describing the laparoscopic visual appearance of superficial endometriosis, endometriomas, and deep infiltrating endometriosis. The accumulated data in the literature concerning the visual appearance of the different forms of endometriosis were used to create an ontology that could be used for artificial intelligence applications. RESULTS: Out of 932 articles screened, 35 studies were selected based on the inclusion criteria of human subjects with histologically confirmed endometriosis lesions visualized via laparoscopy. The selected studies were reviewed to develop a visual ontology of endometriosis lesions observed via laparoscopy. The lesions were categorized into 4 classes and further subdivided into 11 subclasses: superficial (black, red, white, or subtle), adhesions (dense or filmy), deep (obliteration, retraction, or deformation), and ovarian (endometrioma or chocolate fluid). The positive predictive value (PPV) varied across lesion types: black lesions (PPV 47%-97%), red lesions (PPV 33%-100%), white lesions (PPV 20%-81%), and ovarian endometriosis (PPV 42%-98%). Nonspecific lesions such as adhesions (PPV 16%-50%) and subtle superficial lesions (PPV 0%-67%) presented lower PPVs. Deep endometriosis lesions, often buried within organs, required indirect signs (obliteration, retraction, deformation) for identification. CONCLUSIONS: The visual ontology proposed in this systematic search could facilitate the detection and classification of endometriosis lesions using artificial intelligence. This study highlights the challenges of reaching a consensus on lesion recognition and classification in AI projects due to the diverse visual presentations of endometriosis.

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PubMed2026

Pedagogical Efficacy of LLM-Generated Synthetic Data Versus Real-World Clinical Records: A Randomized Controlled Non-Inferiority Trial.

BACKGROUND: Expert-reviewed clinical cases generated by large language models (LLMs) may supplement case resources in medical education, but their short-term educational performance relative to real-case-derived teaching materials remains uncertain. We compared immediate post-training test performance after teaching with the two types of case materials and assessed non-inferiority against a prespecified margin. METHODS: We conducted a prospective, parallel-group, randomized non-inferiority trial. Through the Wenjuanxing online platform, participants were randomized 1:1 to learn with either real-case-derived teaching cases compiled by clinicians and reviewed by experts or AI-generated clinical cases produced by Gemini 3.0 Pro from fully de-identified matched real cases and reviewed by three senior general surgery specialists with full-professor rank. The primary outcome was the total score on an independent 10-item immediate post-training test (0-10 points), with a prespecified non-inferiority margin of -0.5 points. Secondary outcomes included the training-phase performance score, learning efficiency index, single-item mental effort rating, case realism, and case-source judgment. RESULTS: A total of 403 participants were randomized, of whom 386 were included in the modified intention-to-treat analysis: 192 in the real-case group and 194 in the AI-generated case group. The mean post-training test score was 4.95 (SD, 3.35) in the real-case group and 4.61 (SD, 3.35) in the AI-generated case group. The mean difference (AI-generated minus real-case group) was -0.335 points (95% CI, -1.006 to 0.337). Because the lower bound of the confidence interval was below the prespecified non-inferiority margin of -0.5 points, non-inferiority was not demonstrated (one-sided P = 0.314). No significant between-group differences were observed in the training-phase performance score, learning efficiency index, or single-item mental effort rating. AI-generated cases received lower realism ratings for Level 3 cases. The proportion of participants with at least one high-confidence completely incorrect response was 1.6% in the real-case group and 2.1% in the AI-generated case group. CONCLUSIONS: In this short-term, text-based online case-learning setting, no statistically significant between-group difference was observed in immediate post-training test performance; however, non-inferiority of AI-generated clinical cases relative to real-case-derived teaching materials was not demonstrated.

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PubMed2026

A comparative systematic review of pharmacist education systems and pharmacy service quality in ASEAN-5: Indonesia, Malaysia, Thailand, the Philippines, and Singapore.

BACKGROUND: The global transition toward patient-centered pharmaceutical care has exposed structural disparities in ASEAN pharmacy workforce training and deployment. This review examines four research questions: how pharmacy education systems and accreditation standards differ across Indonesia, Malaysia, Thailand, the Philippines, and Singapore (collectively, the ASEAN-5); the extent to which pre-registration education influences clinical service scope and professional confidence; how education reform and regulatory change have shaped pharmacist clinical roles; and what barriers and enablers exist for regional qualification harmonization. METHODS: A systematic literature review following PRISMA 2020 was conducted. Searches of PubMed/MEDLINE and Scopus, supplemented by grey literature, were completed in May 2026. Of 78 unique records screened, 46 studies published between 2005 and 2026 met inclusion criteria. Quality appraisal used an adapted Mixed Methods Appraisal Tool; synthesis employed narrative thematic analysis. RESULTS: The five countries represent four structurally distinct pharmacy education architectures: Thailand's standardized six-year Doctor of Pharmacy with dual specialization tracks; four-year Bachelor of Pharmacy programmes in Malaysia and the Philippines with institutional variation; Indonesia's clinically underdeveloped system despite rapid expansion; and Singapore's four-year Bachelor of Pharmacy followed by a nationally mandated one-year pre-registration pathway. Evidence links deeper clinical training to broader practice scope, higher confidence, and improved patient outcomes. Reform produced uneven results: Thailand's PharmD transition improved clinical recognition but exposed deployment paradoxes; Singapore achieved the strongest training-to-practice alignment; Indonesia's health insurance reforms were not absorbed by an underprepared workforce; the Philippines lacks a national competency framework. No binding mutual recognition arrangement was identified; divergent qualification structures, incompatible accreditation systems, and an asymmetric evidence base remain the primary barriers. DISCUSSION: These findings indicate that clinical service scope is bounded less by national policy ambition than by the depth and clinical orientation of the pre-registration education that precedes it, and that credentialing reforms which outpace a health system's capacity to absorb new clinical roles, or the reverse, do not by themselves translate into expanded practice. CONCLUSIONS: Pharmacy education across the ASEAN-5 remains nationally distinct and clinically uneven. Clinical service scope is directly bounded by pre-registration education quality. No country has fully closed the education-practice gap. Regional harmonization requires national-level educational reform as a prerequisite.

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PubMed2026

User Engagement and Feature Preferences in an AI-Powered mHealth Intervention for Diabetes Prevention: Secondary Analysis of a Randomized Controlled Trial.

BACKGROUND: Prediabetes is highly prevalent and increasing globally, yet lifestyle interventions remain underused. AI-driven mobile health (mHealth) tools can help scale diabetes prevention efforts, but the key factors driving their success are not well understood. OBJECTIVE: This post hoc secondary analysis of a randomized controlled trial (RCT) aimed to characterize the most valued features and the role of user engagement in outcomes of a fully automated mHealth intervention for diabetes prevention. METHODS: Data from 151 participants with prediabetes and overweight or obesity who were assigned to an AI-based diabetes prevention program (Sweetch) in a parent RCT (NCT05056376) were analyzed. Engagement (defined as the total number of days the app was used) was categorized into tertiles (low, medium, and high). Baseline characteristics were compared across engagement groups using ANOVA, Kruskal-Wallis, and chi-square tests, and regression models assessed the association between engagement and achievement of diabetes risk reduction outcomes (≥5% weight loss, ≥4% weight loss with ≥150 min/week of physical activity, or ≥0.2 percentage point reduction in hemoglobin A1c [HbA1c] at 12 months). Perceived usefulness of intervention features was surveyed at 12 months. RESULTS: Median engagement was 98 (IQR 34-232) days. Older age (P<.001) and lower baseline BMI (P=.04) were significantly associated with higher engagement. Compared with low engagement, high engagement was associated with greater odds of achieving the composite diabetes risk reduction outcome (odds ratio [OR] 2.59, 95% CI 1.11-6.01; P=.03), ≥5% weight loss (OR 3.31, 95% CI 1.16-9.42; P=.03), and ≥0.2 percentage point reduction in HbA1c (OR 3.57, 95% CI 1.19-10.75; P=.02). Participants most frequently rated weight tracking, physical activity tracking, and the digital body weight scale as the features that were most helpful for achieving their health goals. CONCLUSIONS: Higher engagement with an AI-driven intervention requiring no human intervention was associated with improved diabetes risk reduction. Contrary to concerns about lower digital literacy, older adults engaged with the intervention more than younger adults. Features related to weight and physical activity tracking were most valued by patients in the program. TRIAL REGISTRATION: ClinicalTrials.gov NCT05056376; https://clinicaltrials.gov/study/NCT05056376.

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PubMed2026

Short-term psychodynamic psychotherapy for functional neurological disorder: A pilot randomized controlled trial.

BACKGROUND: Evidence-based psychotherapeutic treatments for Functional Neurological Disorder (FND) remain limited. This pilot trial evaluated the preliminary efficacy of Short-term Psychodynamic Psychotherapy (STPP) plus Standard Medical Care (SMC) compared with SMC alone in reducing FND symptom frequency. METHODS: Adults with FND were randomized (1:1) to receive either SMC alone or 12 weekly sessions of STPP plus SMC. The primary outcome was symptom frequency (days with symptoms in the last 4 weeks) assessed at the end of treatment (3 months) and at 6-month follow-up. Secondary outcomes included treatment response (≥50% reduction in symptom frequency) and scores on the Hamilton Depression Rating Scale (HAM-D), Hamilton Anxiety Rating Scale (HAM-A), and World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0). RESULTS: Of 91 randomized patients (mean age 38.2 years, 75.8% female), 81.3% completed follow-up. Intention-to-treat analysis using Linear Mixed Models showed that STPP plus SMC significantly reduced symptom frequency compared with SMC alone (estimated mean difference -5.72 [95% CI -8.68 to -2.77]; Cohen's d = 0.77; p < 0.001).Treatment response was achieved by 65.8% in the intervention group versus 16.7% in controls (OR 8.21 [95% CI 2.79-24.19]; p < 0.001; NNT 2.0).Significant improvements were also observed for depression (HAM-D: estimated mean difference -10.80; d = 1.45), anxiety (HAM-A: -7.94; d = 1.06), and disability (WHODAS 2.0: -5.77; d = 0.74), all p < 0.001. CONCLUSIONS: STPP was associated with clinically meaningful improvements in FND symptom frequency and all secondary outcomes, with large effect sizes and high treatment response rates. These findings support the preliminary efficacy of STPP for FND and justify larger, multicenter confirmatory trials.

Humans↗

PubMed2026

Multilevel Revision Percutaneous Vertebroplasty in Elderly Patients With Osteoporotic Thoracolumbar Fractures: A Retrospective Cohort Study.

PURPOSE: Vertebral compression fractures (VCFs) are common complications of osteoporosis in elderly patients. Percutaneous vertebroplasty (PVP) provides pain relief and functional improvement, but some patients require revision due to refracture, cement failure, or new symptomatic levels. While outcomes of primary and multilevel augmentation have been described, systematic data on multilevel revision PVP remain rare. The aim of this study was to evaluate pain relief, functional improvement, and perioperative safety after three- and four-level revision PVP in elderly patients with osteoporotic thoracolumbar fractures. METHODS: This retrospective, single-center cohort included patients aged 75-85 years who underwent revision PVP between August 2019 and November 2023. Eligible cases had a history of prior PVP and required repeat augmentation of three or four vertebral levels in a single session. Visual Analogue Scale (VAS) scores for pain and Oswestry Disability Index (ODI) for functional disability were recorded preoperatively and at 1-, 3-, 6-, and 12-month follow-up. RESULTS: Nine patients were analyzed. Revision involved three levels in five patients and four levels in four patients, with a mean interval of 14.1 months after the index procedure. Mean VAS improved from 8.3 ± 0.7 preoperatively to 3.2 ± 0.6 at 12 months (61% reduction, p < 0.01). ODI improved from 75.2% ± 3.4% to 26.9% ± 2.7% (64% reduction, p < 0.01). All patients exceeded the minimal clinically important difference thresholds. No perioperative complications such as cement leakage, neurological deficits, or pulmonary events were observed. CONCLUSION: Three- and four-level revision PVP provided significant pain relief and functional improvement in elderly patients with osteoporotic fractures, without increased complication rates. To our knowledge, this represents one of the first reports addressing this topic, suggesting it is an effective option in carefully selected patients.

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PubMed2026

Adverse Experiences in Brief Meditation Practices: Randomized Controlled Trial.

BACKGROUND: Meditation has become increasingly popular in recent decades. However, relatively little remains known about the prevalence of and risk factors for adverse experiences related to a single meditation practice. OBJECTIVE: The objective of our study was to examine adverse experiences associated with 3 brief, digitally delivered meditation practices (mindfulness, self-compassion, and gratitude) relative to using the internet as usual, as well as to investigate whether preintervention characteristics could predict such outcomes. METHODS: In a secondary analysis of a randomized controlled trial using samples that were representative of the US and UK adult populations with regard to ethnicity, sex, and age, we examined adverse experiences associated with 3 brief (ie, 5 or 10 minutes) meditation practices (ie, mindfulness, self-compassion, and gratitude) relative to using the internet as usual. We also investigated the potential of using preintervention characteristics to predict such outcomes. RESULTS: A total of 5049 participants completed all preintervention measures and were randomly assigned to meditation or control conditions. Across the sample, 4.1% (204/4925) of participants reported having a distressing experience during the intervention, and 7.1% (348/4908) of participants experienced an increase in negative affect from before to after the intervention. The results showed that participants who were randomized to a brief meditation intervention were no more likely to report a distressing experience than those who were randomized to use the internet as usual (odds ratio [OR] 1.05, 95% CI 0.76-1.47; P=.76). The results also showed that participants who were randomized to a brief meditation intervention were less likely to report clinically relevant increases in negative affect relative to using the internet as usual (OR 0.63, 95% CI 0.50-0.80; P<.001). Notably, participants in the 10-minute condition had a significantly higher likelihood of reporting a distressing experience than those in the 5-minute condition (OR 1.42, 95% CI 1.07-1.89; P=.02). Preintervention characteristics showed acceptable discrimination ability to predict a distressing experience (area under the curve=0.73) and slightly lower ability to predict increased negative affect (area under the curve=0.67). CONCLUSIONS: Taken together, we found that the brief, digitally delivered meditation practices tested in this study carry risks of adverse experiences that are comparable to or lower than those of typical activities on the internet; 10-minute condition was more likely to result in distressing experiences than 5-minute condition; and adverse responses to a brief meditation practice can, at least to a certain degree, be predicted using preintervention characteristics. TRIAL REGISTRATION: Open Science Framework 94HKS; https://osf.io/94hks/overview.

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PubMed2026

Development and validation of a comprehensive prognostic model for 28-day ICU mortality in non-traumatic subarachnoid hemorrhage: an analysis based on the MIMIC-IV database.

BACKGROUND: Due to the complex pathophysiology of non-traumatic subarachnoid hemorrhage (SAH), accurate risk prediction remains a challenge. Our aim is to develop and validate a comprehensive prognostic model that integrates demographic characteristics, vital signs, laboratory parameters, and more, to provide clinical decision-making support in real-world practice. METHODS: We conducted a retrospective cohort study of 785 Non-traumatic subarachnoid hemorrhage patients. The cohort was randomly divided into a training set (n = 549) and a validation set (n = 236). Feature selection was performed using LASSO regression, followed by backward stepwise Cox regression for optimization. A nomogram was constructed based on independent predictive factors, and model performance was assessed using discrimination, calibration, and decision curve analysis. To prevent immortal-time bias, all predictors were anchored to a fixed early (first-24-hour) measurement window, treatment variables were modelled as binary indicators rather than cumulative exposures, and a five-model sensitivity analysis with baseline-severity adjustment was performed. RESULTS: The development of our model followed a systematic approach: first, 15 potential predictive factors were selected via LASSO regression, which were then refined to 12 independent predictors using backward stepwise Cox regression. The final predictive factors included: Ventilation, AHT, Nimodipine 60 mg, Age, SAPS.II, Input amount, Calcium total, Platelet count, White blood cells, Anion gap, pH, and Chloride. The integrated model demonstrated excellent predictive ability for 7-day, 14-day, and 21-day mortality in both the training set (AUC: 0.972, 0.934, 0.898) and the validation set (AUC: 0.968, 0.948, 0.911). Calibration curves and decision curve analysis confirmed the model's reliability and clinical utility across different time points. We constructed a nomogram for individualized risk prediction. Univariate Kaplan-Meier survival analysis demonstrated significant stratification of survival outcomes by each predictor, while restricted cubic spline analysis revealed non-linear relationships between continuous variables and mortality risk. Random survival forest analysis identified the top three predictive factors (Nimodipine 60 mg, Ventilation, AHT) and compared them with our full 12-variable model, confirming superior performance of the integrated model at all time points. At the 28-day primary endpoint, the model achieved a time-dependent AUC of 0.898 (training) and 0.904 (validation); after restricting predictors to the early baseline window, the leakage-controlled model retained good discrimination (validation C-index 0.803). CONCLUSIONS: Our ICU 28-day mortality prognosis model demonstrated robust performance in predicting ICU 28-day mortality in non-traumatic subarachnoid hemorrhage. The model, through the nomogram, provides individualized risk assessment, aiding clinical decision-making and patient stratification.

Humans↗

PubMed2026

Safety and efficacy of recombinant botulinum toxin type A (Eveotox®) in patients with post-stroke upper limb spasticity: Results from a Phase Ib/II clinical trial.

Upper limb spasticity is a common and disabling complication of stroke. Botulinum toxin type A (BoNT-A) is widely used for focal spasticity treatment, but naturally derived products may present limitations related to immunogenicity and manufacturing variability. Recombinant botulinum toxin type A, produced by genetic engineering without complexing proteins, may provide improved product consistency. This Ib/II study evaluated the safety, tolerability, and preliminary efficacy of recombinant botulinum toxin type A in adults with post-stroke upper limb spasticity. This multicenter, seamless Ib/II clinical study included an open-label dose-escalation Ib phase and a randomized, double-blind, placebo-controlled II phase. Adult patients with post-stroke upper limb spasticity received a single intramuscular injection of recombinant botulinum toxin type A or placebo. The primary endpoint in Phase II was the change from baseline in the Modified Ashworth Scale (MAS) score of the primary target muscle group at Week 4. Secondary endpoints included MAS and Tardieu scale changes in individual muscle groups, Disability Assessment Scale (DAS), Physician's Global Assessment (PGA), and immunogenicity. The Ib phase showed improvements in MAS, DAS, and PGA, indicating an early efficacy signal. In Phase II, recombinant botulinum toxin type A produced a significant reduction in MAS score of the primary target muscle group at Week 4 compared with placebo, with effects sustained through Week 12. At Week 4, the PGA score in the Eveotox® group showed a statistically significant improvement compared with the placebo group. While MAS and PGA scores showed significant improvement, DAS functional scores did not differ statistically from the placebo group at week 4. The treatment was generally well tolerated, and low incidence of antibodies were observed. Recombinant botulinum toxin type A was safe and effective in reducing post-stroke upper limb spasticity after a single administration. These results support further Phase III clinical evaluation.

Humans↗

PubMed2026

Final-year nursing students' clinical practice experiences: a reflection study.

OBJECTIVES: This study aimed to explore the most impactful clinical practice experiences of final-year nursing students and the future-oriented actions developed in response to these experiences. METHODS: A retrospective descriptive qualitative design was used. Following reflection training in the internship practice course, 134 final-year nursing students were asked to describe the experience that affected them most during clinical practice. A total of 123 written reflections were analyzed using content analysis. RESULTS: Three themes emerged: near-miss events, incivility behaviors, and positive preceptoring roles. Negative experiences were mainly related to patients, relatives, and nurses and often led students to feel fear and inadequacy. Students reported action plans focused on effective communication, safe patient care, and becoming positive role models. CONCLUSIONS: These findings highlight the importance of supportive clinical learning environments and positive professional socialization during the transition from student to nurse. IMPLICATIONS FOR INTERNATIONAL AUDIENCE: Nursing students worldwide may encounter incivility and near-miss events during clinical practice, potentially adversely affecting their learning experiences and professional development.

Humans↗

PubMed2026

Swab Testing to Optimize Pneumonia Treatment With Empiric Vancomycin: A Randomized Controlled Trial.

BACKGROUND: Fear of methicillin-resistant Staphylococcus aureus (MRSA) as a cause of community-acquired pneumonia (CAP) frequently leads to empiric vancomycin coverage. Data evaluating the use of MRSA polymerase chain reaction (PCR) nasal swab testing to guide vancomycin de-escalation is limited for patients in the intensive care unit (ICU). METHODS: Swab Testing to Optimize Pneumonia Treatment With Empiric Vancomycin (STOP-Vanc) is a pragmatic, prospective, single-center, non-blinded randomized trial in which adult ICU patients with suspicion of CAP were randomized 1:1 to receive usual care either with (intervention) or without (control) the addition of MRSA nares PCR testing following ICU admission. The primary outcome was vancomycin-free hours alive, defined as the expected number of hours alive and free of vancomycin use within the first 7 days of trial enrollment as estimated using a longitudinal proportional odds state transition model adjusted for baseline covariates. RESULTS: A total of 277 adult ICU patients were randomized. Methicillin-resistant Staphylococcus aureus PCR nasal swab testing had a negative predictive value (NPV) of 98.9% in the intervention arm. The primary endpoint, vancomycin-free hours alive, was 105.7 in the control arm and 109.7 in the intervention arm (adjusted difference, 4 hours; 95% CI, -9.5-18.2; P = .458). CONCLUSIONS: Despite MRSA PCR nasal swab testing demonstrating a high NPV in this critically ill population, MRSA PCR nasal swab testing did not decrease the duration of vancomycin use or 30-day mortality among ICU patients with suspected CAP. Additional clinician education and antimicrobial stewardship interventions might be needed to reduce vancomycin use in this patient population. CLINICAL TRIALS REGISTRATION: ClinicalTrials.gov NCT06272994 (STOP-Vanc).

Humans↗