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PubMed2025

Improving Community-Based Care for Adolescents with ADHD: a Randomized Controlled Trial of Artificial Intelligence-Assisted Fidelity Supports.

Cognitive-behavioral treatments (CBTs) for adolescents with ADHD demonstrate promise of long-term effects on outcome. However, their implementation in routine care community clinics faces barriers that impact quantity, efficiency, and quality of delivery, as well as client outcomes. This study is a randomized controlled trial designed to evaluate the impact of an AI-assisted service delivery model on therapist implementation of Supporting Teens' Autonomy Daily (STAND), a CBT blended with Motivational Interviewing (MI) for adolescents with ADHD. Adolescents with ADHD (N = 51), who were clients at three community mental health agencies, received treatment from 23 therapists. There was randomization of adolescents and therapists to AI-assisted or standard implementation supports. In addition to standard supports (i.e., training, standard facilitation resources, technical assistance, case supervision), AI-assisted support package included digitized facilitation resources housed in a clinical dashboard (Care4), feedback on content fidelity, and AI-generated feedback on MI implementation quality. The AI-assisted group was associated with more efficient treatment delivery and lower number of appointments attended by the adolescent. There was also a significant decrement in MI quality over time in the AI-assisted group compared to the standard support group. Feedback in focus groups indicated that therapists perceived a task-oriented mindset to be associated with receipt of the AI-assisted support package, leading therapists to prioritize efficiency over relational aspects of therapy. Following the results of this trial, a future, larger RCT should examine the impact of the AI-assisted implementation model on mental health outcomes and cost savings to organizations, third party payers, and clients. Trial registration number: NCT05135065; https://www.clinicaltrials.gov ; Registered September 2021.

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PubMed2026

Effects of testosterone-augmented multimodal exercise intervention in spinal cord injury: a randomized controlled trial.

CONTEXT: Spinal cord injury (SCI) leads to profound muscle atrophy, aerobic deconditioning, and metabolic dysfunction. Exercise-based interventions alone produce modest benefits. Whether testosterone can augment physiologic responses to exercise in this population remains untested. OBJECTIVE: To evaluate efficacy and safety of home-based intervention combining functional electrical stimulation-assisted leg cycling (FES-LC), arm ergometry (AE), and testosterone compared with FES-LC, AE plus placebo in adults with SCI. METHODS: This randomized, placebo-controlled, double-blind trial enrolled 84 adults (76 males and 8 females) aged 19-70 years with SCI (neurologic levels C4-T12; AIS grades A-D). Participants were randomized to multimodality intervention (home-based FES-LC, AE and intramuscular testosterone undecanoate) (n = 38) or control intervention (FES-LC, AE plus placebo) (n = 46) for 16 weeks. The primary outcome was change in aerobic capacity (peak VO2) during AE cardiopulmonary exercise testing. Secondary outcomes included lean mass, hemoglobin, cardiometabolic markers, and safety. RESULTS: Mean (SD) age was 44 (13) years and time since injury was 13.9 (13) years). Between-group changes in peak VO2 were not statistically significant. Within-group improvements were larger in multimodality (∼19% increase; 0.10 L/min; 95% CI, 0.02-0.18 L/min) compared to controls (∼6% increase; 0.06 L/min; 95% CI, -0.01-0.13). The multimodality group gained significantly more lean mass (whole-body:1.84 kg, 95% CI: 0.52-3.16, P = .007; lower extremity 0.92 kg, 95% CI: 0.38-1.45, P = .001), and anemia was corrected in a greater proportion of participants. Adverse event rates were similar between groups. CONCLUSION: A home-based multimodality intervention combining FES-LC, AE, and testosterone was safe and associated with greater improvements in lean mass and hemoglobin. Although between-group differences in aerobic capacity were not statistically significant, greater within-group increases were observed in the multimodality group. These findings may inform future studies of testosterone-augmented exercise interventions for individuals living with SCI.

Humans↗

PubMed2026

Whole cell inactivated poly-bacterial preparation MV130 effect on nasal mucosal immunity and experimental human pneumococcal carriage: double-blind randomised controlled trial with controlled human infection model.

BACKGROUND: Bacterial mucosal immunotherapy has shown protection of children and adults from both viral and bacterial respiratory infections, offering the potential to reduce antimicrobial use, and hence also control antimicrobial resistance (AMR). Pneumococcal carriage of vaccine type Streptococcus pneumoniae remains high in Malawi despite infant conjugate vaccination and AMR is increasing. We compared nasal inflammation following sublingual bacterial immunotherapy including S. pneumoniae (MV130, Inmunotek, Spain) or placebo and determined the effect in an experimental human pneumococcal carriage model. METHODS: A double-blind, randomised, placebo-controlled trial in healthy adult volunteers was conducted at Queen Elizabeth Central Hospital in Blantyre, Malawi. Participants were randomly allocated to receive MV130 or placebo sublingually once daily for 42 days. Mucosal inflammation (neutrophil to T cell ratio, NTR) was measured in nasal micro-biopsies. Post-treatment, participants were challenged with 160,000 CFU/naris S. pneumoniae 6B (Spn6b). Experimental pneumococcal carriage rates post inoculation were compared between the two arms. All participants completing the study were included in the analysis. Prospective trial registration: PACTR202403820001276. FINDINGS: 107 participants were enrolled and randomised to MV130/placebo between May and December 2024. There were no serious adverse events, complete compliance was good (72%) and all adverse events were mild. 96 participants (53 male, 43 female) completed the study with 52 participants randomised to MV130 and 44 to placebo. There was no difference in mucosal inflammation (neutrophil to T cell ratio) at day 14 of the intervention MV130 NTR median = 0.737 (IQR 0.294, 2.059) and placebo NTR = 0.831 (IQR 0.450, 2.073), p = 0.64. Secondary analyses showed a rise in mucosal neutrophils after MV130 treatment and after experimental pneumococcal inoculation. There was no difference in nasal or serum anti-pneumococcal immunoglobulin or in experimental pneumococcal carriage proportion between MV130 (12/52, 23%) and placebo (10/44, 23%) groups (unadjusted risk ratio 1.02 (CI 0.49-2.12) p = 1.0). INTERPRETATION: MV130 induced non-specific mild neutrophil inflammation of the nasal mucosa but had no protective effect against experimental human pneumococcal carriage. FUNDING: Wellcome Trust.

Humans↗

PubMed2026

Diagnostic performance of machine learning models versus established risk stratification for intracranial aneurysm rupture: a systematic review and bivariate meta-analysis.

BACKGROUND: Machine learning (ML) models have been proposed to improve the discrimination of intracranial aneurysm rupture status beyond established clinical risk stratification tools. However, reported performance is heterogeneous and the relative contribution of model architecture and feature dominance remains unclear. METHODS: We performed a Preferred Reporting Items for Systematic Reviews and Meta-Analyses-diagnostic test accuracy systematic review and diagnostic meta-analysis of studies evaluating ML models for intracranial aneurysm rupture discrimination. PubMed, Embase and CENTRAL were searched to February 2026. Sensitivity and specificity were pooled using a bivariate random-effects model, with summary receiver operating characteristic curves generated across training, internal testing and external validation datasets. Models were compared with regression-based approaches and Population, Hypertension, Age, Size of aneurysm, Earlier subarachnoid haemorrhage, Site of aneurysm (PHASES) scores. Subgroup and meta-regression analyses explored associations between algorithm family and feature domain. RESULTS: Sixty-two retrospective cohorts (29 709 patients 209 models) met the inclusion criteria. In training datasets, pooled sensitivity and specificity for ML were 0.81 (95% CI 0.75 to 0.85) and 0.83 (0.80-0.86), with an area under the curve (AUC) of 0.878, exceeding PHASES (AUC 0.667). In testing datasets, ML retained higher discrimination (AUC 0.837) than regression models (0.806) and PHASES (0.646). In external validation, sensitivity was preserved (0.82), but specificity declined (0.66). Deep learning demonstrated the highest AUCs (training and testing). Incorporation of haemodynamic or radiomic features improved pooled discrimination relative to morphology alone. Evidence of small-study effects and mostly unclear Prediction Model Risk Of Bias Assessment Tool ratings were observed. CONCLUSIONS: ML approaches demonstrate higher pooled discrimination for aneurysm rupture status than conventional risk scores in retrospective datasets, but reduced external validation specificity and heterogeneity limit confidence for clinical translation. Prospective, externally validated, calibrated models are required before integration into routine cerebrovascular risk stratification.

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PubMed2026

Could the preoperative urethral curve be used to predict immediate urinary continence following Retzius-sparing robot-assisted radical prostatectomy? A retrospective multi-center study.

PURPOSE: Immediate urinary continence (UC) recovery following Retzius-sparing robot-assisted radical prostatectomy (RS-RARP) remains highly variable, highlighting the need for reliable preoperative prediction. We aimed to develop and validate models to identify patients likely to achieve immediate UC recovery following RS-RARP. MATERIALS AND METHODS: A total of 580 prostate cancer patients who underwent RS-RARP from four medical centers were assigned to a training set (n=348), an internal validation set (n=103) and an external validation set (n=129). Independent predictors were identified through univariate analysis and LASSO regression. A nomogram was constructed using multivariate logistic regression. Its performance was evaluated with receiver operating characteristic (ROC) curve, calibration curves, and decision curve analysis. RESULTS: Immediate UC recovery was observed in 84.5% (294/348) of patients in the training cohort, 80.6% (83/103) in the internal validation cohort, and 81.4% (105/129) in the external validation cohort, respectively. Multivariate analysis identified membranous urethral length (MUL) (OR=1.23, P=0.029) and urethral curvature (OR=2.84, P<0.001) as independent predictors, while prostate volume (PV) (OR=0.84, P <0.001) as a protective factor. The nomogram integrating MUL, PV, and urethral curvature demonstrated superior predictive accuracy, with an AUC of 0.87 (95% CI, 0.83-0.91) in the training cohort. The bootstrap-corrected calibration slope was 0.96, and the Brier score was 0.08. Calibration curves and decision curve analysis confirmed the predictive accuracy and clinical utility of the nomogram. CONCLUSIONS: Our study introduces a novel quantitative method for assessing urethral curvature. The mpMRI-based model, integrating urethral curvature and prostate spatial configuration, offers enhanced predictive accuracy for postoperative immediate UC recovery.

Humans↗

PubMed2026

A systematic review of sleep hygiene interventions in physically and operationally demanding occupations.

Workers in physically and operationally demanding (POD) occupations (e.g. military personnel, emergency responders, law enforcement) experience disrupted sleep due to irregular schedules and high-stress work environments. Given the importance of sleep for physical and cognitive performance, interventions to improve sleep in POD occupations are crucial yet remain under-researched. To investigate the effectiveness of sleep hygiene interventions in improving sleep quality and quantity outcomes for POD occupations, a systematic review was conducted across five databases (PubMed, CINAHL, SPORTDiscus, PsycINFO, Web of Science) in September 2024. Eligible studies involved workers in POD occupations where a sleep hygiene intervention was compared against a waitlist or passive control. Ten studies were included, eight randomised controlled trials (RCTs) and two non-randomised controlled trials (NRCTs). Narrative synthesis identified Structured Training Programs (n = 7), Phone Assistance Programs (n = 2), and Single Lecture Interventions (n = 1). Evidence certainty ranged from Very Low to Moderate, converging towards Low quality due to imprecision, risk of bias, and indirectness. Structured Training Programs showed moderate improvements in sleep quality and small-to-moderate effects on sleep duration. Phone Assistance Programs had minimal effects, and Single Lecture Interventions had negligible impact. Higher-quality research is urgently needed to assess sleep hygiene interventions in POD occupations.

Humans↗

PubMed2026

Development and Validation of a Predictive Model for Identification of Cognitive Impairment Risk in Older Adults with Subjective Cognitive Decline：A Longitudinal Study.

BACKGROUND: Subjective cognitive decline (SCD) is a transitional state between objective cognitive impairment and cognitively intact mental status, providing a critical window for implementing preventive interventions to delay objective cognitive decline. AIMS: We aimed to develop a predictive model for SCD progression in older adults with mild cognitive impairment (MCI). This model will facilitate the identification of risk factors and establishment of targeted interventions for community-based SCD management. METHODS: Data from the China Health and Retirement Longitudinal Study (CHARLS) was utilized in this study, extracting 18 indicators. Potential predictors selected through univariate Cox regression and LASSO regression analyses were sequentially incorporated into a multivariable Cox regression model. A nomogram was constructed to establish a predictive model. Model validation encompassed Area Under Curve (AUC) metrics for discriminative capacity, complemented by quantitative assessments using calibration curve analysis for precision verification and decision curve analysis (DCA) for clinical utility evaluation. RESULTS: A total of 1099 older adults with SCD were included in the final analysis, of whom 114 (10.3%) developed MCI. Multivariable Cox regression identified residence, marital status, educational level, social participation, gait speed, and baseline cognitive function. The model demonstrated time-dependent AUC values of 0.885, 0.830, 0.839, and 0.836 in the training set when evaluating discriminative capacity at 2-, 4-, 7-, and 9-year, respectively. The predictive model showed excellent predictive ability according to AUC, calibration curve, and DCA. CONCLUSIONS: A predictive model was created to estimate the risk of developing MCI in older individuals with SCD, offering clinician-actionable intervention benchmarks for preventive care.

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PubMed2026

Infra-low-frequency neurofeedback alters EEG network efficiency: exploratory evidence from healthy volunteers.

Infra-Low-Frequency Neurofeedback (ILF-NFB) combines classic frequency-band (FB) and infra-low-frequency (ILF) EEG components in implicit training protocols and is increasingly applied in clinical contexts. Yet, the neurophysiological mechanisms underlying ILF-NFB remain to be further elucidated. In this randomized, sham-controlled and double-blind study, we explored the online impact of a one-session ILF-NFB application on EEG correlates in healthy participants (39 analyzed datasets). Continuous 31-channel EEG was recorded during verum and sham feedback in a double-blind, randomized crossover design. In this exploratory analysis approach, functional connectivity was estimated using the debiased weighted phase-lag index (dwPLI) and analyzed with graph-theoretical measures. The results revealed higher global efficiency during verum compared to sham in the Beta1 band (12-15 Hz), reaching significance in the primary comparison but not surviving Bonferroni correction across the five tested bands; block-wise follow-ups showed a significant verum-sham difference in the first half of the neurofeedback session and a directionally consistent pattern in the second half. The Condition × Block interaction was not significant. No consistent differences were observed in other frequency bands, nor for betweenness centrality. While preliminary, these exploratory results point to possible network-level effects during ILF-NFB and motivate further confirmatory work in extended training protocols and clinical populations.

Humans↗

PubMed2026

Improving Sleep and PTSD Outcomes in Service Members: A Randomized Controlled Trial Examining the Long-Term Effects of an Integrated Treatment.

Trauma-induced sleep disturbances often persist after successful posttraumatic stress disorder (PTSD) treatment. While integrated protocols combining sleep and exposure-based treatments may maximize outcomes, prior studies are limited and have largely relied on subjective sleep measures or failed to include long-term follow up assessments. Active-duty service members with PTSD (n = 82) were randomly assigned to Compressed Prolonged Exposure (CPE) treatment or Trauma Management Therapy (TMT), which integrates exposure therapy with sleep hygiene training and other skills-based interventions. PTSD symptoms and actigraphy-based sleep were measured at baseline, posttreatment, 3- and 6-month follow-up and data were compared between groups and across time. Posttreatment, both groups showed negligible to small changes in sleep compared to baseline. However, the TMT group evidenced improvements in most sleep parameters by the 3- and 6-month follow-ups, while sleep health generally worsened in the CPE group over time. Between groups, those randomized to TMT exhibited better sleep efficiency (g = 0.24) and onset latency (g = -0.34) at 3-month follow-up, and better sleep quality (g = 0.70), efficiency (g = 0.51), and wake after sleep onset (g = -0.52) at 6-month follow-up. Within both treatment groups, poorer sleep at the 6-month follow-up was correlated with greater PTSD symptom severity measured at the same time point. Integrated treatment for sleep and PTSD produced superior objective sleep outcomes compared to exposure alone, with the most meaningful improvements in sleep observed 6 months after treatment completion. Several critical directions for future studies are discussed.

Humans↗

PubMed2026

"Clinical efficacy and expression of antimicrobial resistance genes after using a novel herbal mouthwash compared to chlorhexidine: A Randomised controlled trial in generalised gingivitis patients".

OBJECTIVES: Chlorhexidine, the gold-standard mouthwash, has several disadvantages, like promotion of antimicrobial resistance. Herbal mouthwashes are emerging as alternatives to chlorhexidine. However, its impact on antimicrobial resistance remains unclear. The aim of the study was to compare the clinical efficacy and the expression of antimicrobial resistance genes of chlorhexidine with a novel herbal mouthwash. DESIGN: Sixty patients with generalised gingivitis were randomly assigned to two groups using block randomisation. After professional mechanical plaque removal patients were instructed to use either chlorhexidine or a novel herbal mouthwash (patented composition) for two weeks. Tetracycline resistance (tetM) and macrolide efflux (mefI) gene expression in subgingival plaque were analysed using real-time polymerase chain reaction. Intragroup comparisons were performed with a paired t-test and Wilcoxon signed-rank test for parametric and nonparametric data. Intergroup comparisons employed unpaired t-test, chi-square test, and Mann-Whitney test. RESULTS: A significant reduction in bleeding, plaque, pocket depth and and patient reported outcomes were noticed in both groups. But reduction in plaque was more significant in chlorhexidine group. tetM and mefI genes significantly upregulated in the chlorhexidine group, while it was downregulated with herbal mouthwash (fold change 1.79 ± 0.74 and 0.60 ± 0.43 for tetM, and 1.83 ± 0.87 and 0.51 ± 0.44 for mefI). However, patients' perception of taste, freshness, and overall satisfaction was better in the chlorhexidine group. CONCLUSIONS: The increased expression of antimicrobial resistance genes following chlorhexidine use warrants careful consideration. Herbal mouthwash is an effective, safer alternative with comparable clinical benefits and less impact on antimicrobial resistance.

Humans↗

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

Applications of artificial intelligence in robot-assisted surgery: a systematic review.

To characterize applications of artificial intelligence (AI) in robot-assisted surgery, summarize technical and clinical performance, and assess the quality of the available evidence. PubMed, Web of Science Core Collection, and Scopus were searched for English-language journal articles published from 1 January 2020 through 31 October 2025. Randomized, observational, model-development, validation, and feasibility studies evaluating AI in robot-assisted surgery or closely related image-guided minimally invasive workflows were eligible. Two reviewers independently performed study selection, data extraction, and risk-of-bias assessment. Owing to heterogeneity in surgical procedures, AI tasks, analytical units, validation strategies, and outcomes, findings were synthesized descriptively without statistical pooling. The review was registered in the International Prospective Register of Systematic Reviews (CRD420251175699). Seventeen studies were included: seven clinical prediction or decision-support studies, eight intraoperative recognition, segmentation, or image-guided studies, and two training or workflow studies. Five prediction studies reported area-under-the-curve values of 0.74-0.95. Technical studies reported F1 or Dice scores of 0.525-0.995 and task-specific accuracies of 0.840-0.998. Two randomized studies suggested benefits for personalized suturing feedback and automated camera control, but neither established improved patient outcomes. Only one study had low overall risk of bias; the remaining studies were at high or unclear risk or raised some concerns. AI applications in robot-assisted surgery show promise for prediction, intraoperative perception, training, and workflow support. Evidence primarily demonstrates technical feasibility rather than established clinical effectiveness. Independent multicenter validation and prospective evaluation of patient, educational, and workflow outcomes are required before widespread implementation.

Robotic Surgical Procedures↗

PubMed2026

Written vs. verbal sleep hygiene strategies administration in track and field athletes: a randomized controlled trial study.

BACKGROUND: Sleep hygiene strategies (SHS) are practical, evidence-informed recommendations to enhance both the quantity and quality of sleep in athletes. However, little is known about how these strategies could be communicated and implemented in practice. The primary objective of this study is to investigate how different methods of delivering SHS (written vs. verbal) affect sleep hygiene and sleep parameters in athletes. METHODS: The study was a three-arms randomized controlled trial (ClinicalTrials.gov Identifier: NCT07083544) involving track and field athletes competing at the regional or national level (N.=66). Athletes were randomized to either a control group (CON=22), a written SHS group (W-SHS=22), or a verbal SHS group (V-SHS=22). Sleep characteristics were assessed by actigraphy and sleep diary during a ten-day baseline period (T0) and a ten-day intervention period (T1). Six objective sleep parameters and the Sleep Regularity Index were assessed. Participants also completed a training diary and the Sleep Hygiene Index (SHI). RESULTS: No statistical differences were found between and within groups in training and sleep parameters, but SHI scores improved significantly in the intervention groups between T0 and T1, with differences compared to the control group. A non-significant improvement in total sleep time was observed in the intervention groups, primarily due to earlier bedtimes. CONCLUSIONS: While significant differences in objective sleep measures were not observed, the trends suggest that both written and verbal SHS interventions can modestly improve sleep-related behaviors, particularly by encouraging earlier bedtimes and slightly extending total sleep duration.

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PubMed2026

Effectiveness of exercise-based prehabilitation on pre and postoperative outcomes of patients undergoing cardiac surgery-An umbrella review of systematic reviews.

AIMS: Individuals undergoing cardiac surgery are becoming older, frailer, and less mobile. Prehabilitation has shown to improve postoperative outcomes by optimizing preoperative physical function. This umbrella review aims to pool the systematic reviews assessing the effectiveness of exercise-based prehabilitation in cardiac surgery. METHODS AND RESULTS: The review followed the PRIOR checklist. PubMed, Embase, CINAHL, Cochrane library, Scopus, Web of science, ProQuest NAHD, ProQuest HMC, Open Grey and MedNar were searched using relevant keywords from inception to 16th December, 2024. Two reviewers screened and extracted data from the included reviews and assessed primary study overlap with the corrected covered area. Methodological quality of the reviews was evaluated with the A MeaSurement Tool to Assess systematic Reviews-2 scale. Certainty of evidence was assessed using a previously developed criteria for overview of reviews. Six systematic reviews with 30 unique trials and 6705 participants were included. The interventions assessed included breathing exercises, inspiratory muscle training, and exercise training. Prehabilitation reduced length of hospital stay, postoperative pulmonary complications, and clinically improved functional capacity with a very low to moderate certainty of evidence. However, there was uncertainty regarding the effects pertaining to adverse events and quality of life. The methodological quality of all reviews was critically low. The primary trials scored poorly in the domains of selection and detection bias. CONCLUSION: Exercise-based prehabilitation might reduce length of hospital stay and postoperative complications, and improve functional capacity. However, the quality of evidence is poor, and individual discretion is required before implementing them into practice. REGISTRATION: PROSPERO: CRD42023480100.

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PubMed2026

Advancing nursing education through social and emotional learning: A systematic review guided by the Collaborative for Academic, Social, and Emotional Learning framework.

BACKGROUND: With Generation Z entering the nursing workforce in growing numbers, strengthening social and emotional learning is critical for academic success, professional adaptation, and safe practice. However, the existing evidence remains fragmented because of varied interventions and inconsistent approaches. OBJECTIVES: This systematic review examined (1) the social and emotional learning essential for nursing students and nurses within the Collaborative for Academic, Social, and Emotional Learning framework, (2) their impact on educational and clinical outcomes, and (3) implications for advancing nursing education and practice. METHODS: Following Joanna Briggs Institute methodology and Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, five international (PubMed, EMBASE, CINAHL, PsycINFO, Cochrane) and three Korean (RISS, KoreaMed, KMBASE) databases were searched up to June 2025. Eighteen studies involving 2,952 participants met the inclusion criteria, including quasi-experimental quantitative studies, descriptive quantitative studies, qualitative studies, and mixed-methods studies. The methodological quality of the included studies was appraised using the Mixed Methods Appraisal Tool. RESULTS: Within the Collaborative for Academic, Social, and Emotional Learning framework, relationship skills and self-management were the most frequently studied competencies, emphasizing teamwork, communication, and stress regulation. Self-awareness and social awareness were underexplored, despite their importance in empathy, resilience, and reflective practice. Responsible decision-making was the least studied competency, despite its importance in ethical reasoning. Social and emotional learning was consistently associated with enhanced adaptation, communication, leadership, relationships, and clinical performance. Effective strategies included blended learning, simulation, reflective activities, and mentorship, which are aligned with Generation Z's learning preferences. CONCLUSION: Although social and emotional learning integration is associated with improvements in educational and clinical outcomes in nursing, current research has largely centered on relational and stress-related competencies while underrepresenting responsible decision-making. To cultivate reflective, empathetic, and ethically grounded nurses, curricula should integrate social and emotional learning through a balanced and structured approach. REGISTRATION: This study was registered on PROSPERO (ID: CRD420251005683).

Humans↗

PubMed2026

Low Carbohydrate Availability in Energy Balance Alters Bone Turnover and Muscle Proteomic Response With Limited Endocrine Disruption.

Training with low carbohydrate availability (LCA) has been proposed as an independent determinant of physiological perturbations commonly attributed to low energy availability (LEA) and to increase skeletal muscle oxidative machinery, yet the effects of LCA in isolation from LEA remain unclear. We examined whether short-term carbohydrate restriction under energy balance alters endocrine and metabolic markers associated with LEA and skeletal muscle proteomic response. In a randomized crossover design, eight trained males completed 4 days of either a low-carbohydrate high-fat diet (LOW; 12% carbohydrate, 69% fat, 19% protein) or a normal-carbohydrate diet (NORM; 62% carbohydrate, 19% fat, 19% protein), while undertaking daily cycloergometer exercise (15 kcal kg FFM-1 day-1) and maintaining energy availability at 45 kcal kg FFM-1 day-1. LOW induced a clear metabolic shift consistent with LCA, evidenced by elevated circulating free fatty acids, glycerol and β-hydroxybutyrate, in fasting conditions and fat oxidation at rest and during exercise, alongside reduced exercise glucose concentrations. Despite these responses, LOW did not alter insulin, testosterone, triiodothyronine, leptin, hepcidin, or P1NP. In contrast, β-CTX increased and IGF-1 decreased relative to NORM. Muscle glycogen concentration decreased only in LOW (40% ± 14%). Proteomic analysis identified 671 proteins; 57 differentially expressed in LOW relative to NORM were limited to fatty acid metabolism pathways and suppression of ribosomal, sarcomeric, and extracellular matrix proteins. These findings indicate that isolated LCA exerts limited endocrine disruption but may selectively compromise bone turnover and muscle anabolic response, suggesting that without acute LEA, LCA has limited influence on muscle oxidative phenotype.

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PubMed2026

Five-year outcomes in a randomised controlled trial of prolonged exposure therapy and supportive counselling for post-traumatic stress disorder in adolescents: a task-shifted intervention.

BACKGROUND: Cognitive-behavioural therapies with a trauma focus are effective in reducing posttraumatic stress disorder and other psychological distress in adolescents. Long-term follow-up data on adolescents treated for PTSD remain scarce, with few studies extending beyond 12 months after treatment completion. OBJECTIVE: To evaluate the maintenance of treatment gains in a comparative study of effectiveness of PE-A and SC up to 60 months post-treatment. METHOD: Sixty-three adolescents diagnosed with PTSD were randomly assigned to either treatment, provided by newly trained and supervised non-specialist health workers. The primary outcome measure was PTSD symptom severity, as independently assessed on the Child PTSD Symptom Scale (CPSS). We report on the 60-month post-treatment follow-up, building on post-treatment, 3-month, 6-month, 12-month and 24-month post-treatment data that have been published previously. RESULTS: Participants in both treatment groups maintained a significant reduction in PTSD symptoms up to 60-months post-treatment (F (7, 343) = 2.86, p < .01). Participants receiving prolonged exposure experienced greater improvement on the CPSS at all follow-up assessment timepoints, except for the 60-month FU (p = .28; g = 0.33). CONCLUSION: Adolescents with PTSD continued to maintain treatment gains up to 60-months post-treatment. These data, along with findings from the original RCT, indicate that a brief treatment protocol (averaging 9 sessions of PE-A or SC) in a LMIC, task-shifted to be delivered by nurses without prior psychotherapy experience, led to lasting improvements in PTSD and comorbid symptoms for up to five years. The sustained benefits and improved functioning over the first few years post-treatment support expanding both treatments, especially PE-A, in community settings.

Humans↗

PubMed2026

Development and Crossover Evaluation of an Artificial Intelligence-Assisted System for Solid Pancreatic Lesion Detection and Pancreatic Parenchyma Recognition in Endoscopic Ultrasonography (With Video).

BACKGROUND AND STUDY AIMS: Pancreatobiliary endoscopic ultrasonography (EUS) is technically demanding, and supervised training opportunities are limited. We developed an artificial intelligence (AI) overlay system for detecting solid pancreatic lesions (SPL) and recognizing pancreatic parenchyma (PP) and evaluated its effect on reader performance. PATIENTS AND METHODS: Across six centers, two deep learning-based models were trained using expert-annotated EUS frames. We then conducted a randomized, two-sequence, two-period crossover reader study in which eight endosonographers (five novices and three experts) interpreted image sets with and without AI assistance. The primary endpoint was superiority of sensitivity for SPL detection among novices; key secondary endpoints included specificity and PP recognition. RESULTS: From 118 patients, 120 SPL-positive/negative image sets and 160 PP-positive/negative image sets were constructed. Among novices, AI assistance improved SPL detection sensitivity (88.7% vs. 76.8%, p < 0.001) and accuracy (86.4% vs. 78.7%), while specificity met the predefined noninferiority criterion (84.2% vs. 80.5%, p < 0.001). For PP recognition, sensitivity increased numerically (86.3% vs. 83.3%) but did not meet the predefined superiority criterion (p = 0.095); specificity met the noninferiority criterion (87.8% vs. 81.0%), and accuracy increased from 82.1% to 87.0%. Among experts, sensitivity was maintained for both tasks, whereas specificity increased with AI assistance. CONCLUSIONS: AI assistance improved SPL detection among novice endosonographers. For PP recognition, sensitivity increased without reaching statistical superiority, whereas specificity met the predefined noninferiority criterion. These findings support a potential adjunctive role for AI in EUS interpretation.

Humans↗