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Predicting ACL injury risk in athletes: A systematic review of machine learning-based models.

BACKGROUND: Early ACL injury risk identification in athletes is essential. This systematic review examines machine learning (ML) models for predicting ACL injuries, evaluating their methodological quality, performance, and reliability. METHOD: A comprehensive electronic search was conducted across PubMed, Scopus, Web of Science, and IEEE Xplore databases, supplemented by Google Scholar for grey literature, covering articles published between January 1, 2015, and August 30, 2025. Eligible studies were appraised using the Prediction Model Study Risk of Bias Assessment Tool (PROBAST) for methodological quality and risk of bias, and the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) guidelines for quality of evidence. RESULTS: Ten studies were included. PROBAST showed eight studies had moderate risk of bias and two low risk. TRIPOD found only two studies met quality criteria. ML models included logistic regression (n = 5), support vector machines (n = 4), k-nearest neighbor (n = 3), decision trees (n = 3), random forests (n = 5), neural networks (n = 2), linear discriminant analysis (n = 1), and pre-trained CNNs (n = 1). AUC ranged from 0.63 to 0.98. Accuracy (reported in six studies) ranged from 26% to 95%; however, these values should be interpreted with caution due to the absence of confidence intervals, lack of class imbalance handling, and limited external validation across studies. Tree-based ensemble methods such as random forest achieved competitive accuracy (74-86%), while SVM, a non-ensemble classifier, reported accuracy ranging from 71% to 95%; however, the highest values were obtained in studies with notably small sample sizes (n = 12 to n = 39), raising concerns about overfitting and generalizability. CONCLUSION: Current ML algorithms show promise for identifying athletes at high ACL injury risk and detecting relevant risk factors. Although study quality was generally satisfactory, future research should prioritize external validation and model interpretability to support clinical translation.

Humans

The Role of Artificial Intelligence for Intimate Partner Violence Prevention: A Systematic Review.

INTRODUCTION: Intimate partner violence (IPV), encompassing physical, sexual, emotional and economic abuse, remains a pervasive global health concern. Traditional prevention efforts face obstacles such as underreporting, delayed detection and limited personalised support. Emerging artificial intelligence (AI) approaches offer new opportunities to enhance IPV prevention. AIM: This systematic review maps and synthesises evidence on AI-driven tools in IPV prevention based on studies published between 2004 and 2024. METHODS: Following PRISMA 2020 guidelines and PROSPERO registration, we searched PubMed, Embase, CINAHL, PsycINFO, IEEE Xplore and Web of Science. Eligible studies explicitly evaluated AI technologies targeting IPV prediction, screening, intervention or support delivery. Study quality was appraised using the Mixed Methods Appraisal Tool (MMAT). RESULTS: Of 1304 records initially identified, 41 studies met eligibility criteria. AI applications ranged from machine learning (ML) for risk prediction and natural language processing (NLP) for IPV detection in clinical and social media data, to image analysis for forensic evaluation and chatbot-based support. Predictive modelling demonstrated strong discriminative performance, while NLP-based screening detected IPV with notable sensitivity. Chatbots showed feasibility and user acceptability, but evidence of their direct impact on reducing IPV incidence was limited, with one randomised controlled trial showing a modest reduction. Key challenges identified included algorithmic bias, data privacy risks and barriers to integration across health and social care systems. DISCUSSION: AI-informed interventions show promise for improving IPV detection, risk assessment, and scalable support, but questions remain about long-term effectiveness, ethical fairness, transparency and equitable implementation. Future interdisciplinary research should address these concerns to responsibly deploy AI in IPV prevention. RELEVANCE TO CLINICAL PRACTICE: The findings highlight the importance of trauma-informed, culturally responsive care and provider training in AI applications. Nurse-led innovation and policy advocacy will be crucial for safe, equitable integration of AI in IPV prevention.

Artificial Intelligence

Machine learning-based prediction of unplanned readmission and construction of an online calculator for elderly patients with mild ischemic stroke.

OBJECTIVE: To screen for independent risk factors for unplanned readmission in elderly patients with mild ischemic stroke, and to construct and validate an online risk prediction calculator based on an interpretable machine learning model, thereby providing a promising practical tool for accurate clinical assessment of 30&#x2011;day all&#x2011;cause unplanned readmission risk in this population. METHODS: A prospective cohort study was conducted, including 1050 patients aged&#xa0;&#x2265;&#xa0;60&#xa0;years with mild ischemic stroke admitted between August 2023 and September 2024. Participants were randomly divided into a training set (840 cases) and a test set (210 cases) at a ratio of 8:2. Risk factors were screened by univariate analysis and multivariable Logistic regression. Four machine learning models, namely LightGBM, XGBoost, Random Forest, and K&#x2011;Nearest Neighbors (KNN), were developed and their performance was evaluated using AUC, accuracy, sensitivity, and specificity as metrics. The SHAP framework was used for interpretability analysis, and an online calculator was subsequently developed based on the optimal model. RESULTS: Univariate analysis showed significant differences (P&#xa0;<&#xa0;0.05) in 13 factors including age, smoking, AIP, TyG index, HALP score, etc. Multivariable Logistic regression identified age (OR&#xa0;=&#xa0;9.752), smoking (OR&#xa0;=&#xa0;5.171), AIP (OR&#xa0;=&#xa0;6.691), TyG index (OR&#xa0;=&#xa0;4.393), HALP score (OR&#xa0;=&#xa0;2.831), and&#xa0;&#x2265;&#xa0;2 comorbidities (OR&#xa0;=&#xa0;3.664) as independent risk factors. All four machine learning models demonstrated good predictive performance. Based on a comprehensive evaluation of multiple metrics and computational efficiency, the LightGBM model exhibited the best predictive performance (AUC&#xa0;=&#xa0;0.884, accuracy&#xa0;=&#xa0;0.829, sensitivity&#xa0;=&#xa0;0.812, specificity&#xa0;=&#xa0;0.875). SHAP analysis showed that age, AIP, TyG index, smoking, and HALP score were key predictors. An online calculator developed based on this model enables individualized risk predictions. CONCLUSION: Key risk factors associated with 30&#x2011;day unplanned readmission in elderly patients with mild ischemic stroke were identified. The LightGBM model demonstrated high predictive accuracy, and together with the interpretability analysis and online calculator, offers a practical tool to support clinical risk assessment. However, this tool requires future external validation.

Humans

Leading with Innovation: Maternal Health Transformation in New York City Health + Hospitals.

New York City's (NYC) maternal health crisis drew close attention in the late 2010s, driven by alarming data: Approximately 30 women died annually during childbirth in NYC, Black non-Hispanic women were 12 times more likely to die than white women, and more than 3,000 women experienced life-threatening birth complications each year. In response, NYC committed $12.8 million in July 2018 to reduce maternal mortality and eliminate racial disparities.NYC Health + Hospitals (H+H)-the nation's largest public health system, serving 1.1 million patients annually with roughly 15,000 births per year-became the primary vehicle for this initiative. With 80 percent of the system's deliveries covered by Medicaid and a patient population that is 51.2 percent Hispanic and 27.1 percent Black, H+H is uniquely positioned to lead the fight against maternal health inequity.Three flagship programs anchor H+H's response to the city's maternal mortality rate. The OB Simulation Program, launched in 2012 and expanded in 2018, was the first in the nation to use mannequins of color to train thousands of providers in obstetric emergencies. The Maternal Home Program, piloted at H+H's Kings County Hospital in 2019 and scaled system-wide by 2021, has served more than 10,341 patients, generating more than 33,000 referrals for social, behavioral health, and community resources. The Cardio-Obstetrics Program located at Kings County Hospital targets cardiovascular disease-the leading cause of maternal death among Black women-through screening, education, and community outreach. These programs are a health equity imperative, made more urgent by impending federal Medicaid cuts resulting from the H.R.1 One Big Beautiful Bill Act (passed on July 4, 2025).

Humans

Exploring Primary Care Clinicians' Sexual and Reproductive Health Care Delivery to Male Adolescents and Young Adults.

INTRODUCTION: Despite existing guidance for adolescent sexual and reproductive health (SRH) care, male adolescent SRH care receipt is inadequate. Limited research has explored factors affecting clinicians' provision of SRH care to male adolescents, specifically. METHODS: This mixed-method study with 12 primary care clinicians included a brief survey assessing care delivery practices and confidence, followed by an in-depth interview to explore factors affecting SRH care delivery. RESULTS: Clinicians reported high confidence delivering male adolescent SRH care (mean &#xb1; SD: 8.31 &#xb1; 1.71 out of 10), but delivered only about half the recommended services (20 items out of 38). Factors influencing care delivery included gaps in education/training, assumptions about male SRH care, and behavioral constraints at various levels. DISCUSSION: Findings underscore the need to strengthen male adolescent SRH care by enhancing provider training, increasing clinic-level supports, and addressing structural barriers. CONCLUSIONS: Findings can inform strategies to improve the quality and comprehensiveness of SRH services for male adolescents in primary care settings.

Humans

Workplace Safety Champions: Strengthening safety culture through nurse engagement.

Workplace violence is a growing concern in health care, disproportionately affecting frontline nurses and nursing assistants. Despite high prevalence, underreporting remains a barrier to effective prevention and response. This article describes the development, implementation, and outcomes of a Workplace Safety Champion program designed to increase reporting of violent incidents and strengthen a culture of safety. A multidisciplinary task force developed an evidence-based Workplace Safety Champion course that emphasizes de-escalation strategies, reporting processes, and staff support. Champions were appointed across inpatient and emergency units and integrated into a hospital-wide Workplace Safety Champion Council. Program evaluation used course completion data and posttraining surveys. The organizational goal of having at least one trained champion in 90% of inpatient and emergency units was exceeded, with 98% of units represented (N = 93 champions). More than 85% of learners reported intent to change their response to workplace violence, and 90% endorsed improved knowledge of resources and de-escalation strategies. The Workplace Safety Champion program successfully improved staff awareness, reporting, and engagement in workplace violence prevention. Embedding champions across units can serve as a sustainable strategy to strengthen safety culture and support frontline health care workers.

Humans

An exploratory analysis of decision-making in population affinity estimation among forensic anthropology practitioners in the United States.

Population affinity estimation in forensic anthropology often involves the integration of multiple pieces of information, including visual (nonmetric) and metric data. This study examines how practitioners interpret and synthesize visual and metric information and their decision-making processes. A Qualtrics survey was developed using two cases: Case 1 presented clear nonmetric signal but ambiguous metric signal, while Case 2 showed more ambiguous nonmetric signal but clear metric signal. Practitioners were asked to estimate population affinity based on visual assessment, Fordisc data, and provide a final, integrated assessment. A total of 22 valid survey responses were received, with the majority of survey respondents reporting more than 10&#xa0;years of forensic anthropology experience and holding a PhD degree. Results showed that there is substantial variability in Fordisc use and interpretation. Across both cases, participants synthesized conflicting visual and metric information, converged toward the stronger signal, and came to more consistent final estimates relative to the more ambiguous input. These findings highlight variability in practitioner decision-making but suggest that integration of nonmetric and metric information in population affinity estimation can moderate decision-making uncertainty. The results have implications for forensic anthropology education, training, and proficiency testing.

Humans

Psychological interventions for children with chronic physical conditions: a systematic review assessing the role of coping, emotional and cognitive processes.

OBJECTIVES: Coping, emotional and cognitive processes are crucial in child development, particularly in children with pediatric chronic physical conditions (CPC). No systematic review in pediatric psychology has investigated the effectiveness of interventions on these processes concurrently. This review addresses this gap by focusing on the effectiveness of psychological interventions on coping, emotional and cognitive processes in children with CPCs. METHODS: Five electronic databases were searched for studies assessing at least one of these processes. Only randomized-controlled trials with children (8-12&#x2009;years) with a CPC (e.g. diabetes, asthma), which implemented a psychological intervention were included. This study is registered in (CRD42021233505). RESULTS: Ten intervention studies were identified. While cognitive interventions (Cogmed) showed some improvements in working memory, the effects varied across studies despite similar methodologies. Coping interventions (e.g. Coping Skills Training) showed little effect on coping strategies or psychological health variables and were no more beneficial than control groups. No study trained coping, emotional processes and cognitive processes together. CONCLUSION: This review shows current limitations in evaluating psychological interventions targeting coping, cognitive or emotional processes in children with CPCs, limiting a comprehensive understanding of the interventions' action mechanisms. Systematically including underlying processes in intervention studies could help to better adjust those interventions.

Humans

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&#x202f;=&#x202f;7), Phone Assistance Programs (n&#x202f;=&#x202f;2), and Single Lecture Interventions (n&#x202f;=&#x202f;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

Assessing AI literacy and attitudes among medical students: implications for integration into&#xa0;healthcare practice.

PURPOSE: This study aims to assess AI literacy and attitudes among medical students and explore their implications for integrating AI into healthcare practice. DESIGN/METHODOLOGY/APPROACH: A quantitative research design was employed to comprehensively evaluate AI literacy and attitudes among 374 Lusaka Apex Medical University medical students. Data were collected from April 3, 2024, to April 30, 2024, using a closed-ended questionnaire. The questionnaire covered various aspects of AI literacy, perceived benefits of AI in healthcare, strategies for staying informed about AI, relevant AI applications for future practice, concerns related to AI algorithm training and AI-based chatbots in healthcare. FINDINGS: The study revealed varying levels of AI literacy among medical students with a basic understanding of AI principles. Perceptions regarding AI's role in healthcare varied, with recognition of key benefits such as improved diagnosis accuracy and enhanced treatment planning. Students relied predominantly on online resources to stay informed about AI. Concerns included bias reinforcement, data privacy and over-reliance on technology. ORIGINALITY/VALUE: This study contributes original insights into medical students' AI literacy and attitudes, highlighting the need for targeted educational interventions and ethical considerations in AI integration within medical education and practice.

Students, Medical

Use of wearable technologies for physical activity promotion in older adults: A systematic review.

This systematic review, conducted according to PRISMA guidelines and registered in PROSPERO (CRD420251055299), examined the use of wearable technologies for promoting physical activity (PA) in adults aged 60 years and older. Searches across five databases (PubMed, Scopus, Web of Science, CINAHL, Cochrane) identified 2438 records, of which only six randomized controlled trials published between 2021 and 2025 met inclusion criteria, with sample sizes ranging from 36 to 551 participants and mean ages between 65 and 79 years. Given the small number of included studies, findings should be interpreted as preliminary. The studies ranged from the standalone use of commercial trackers (Fitbit, Polar, ActiGraph) to multicomponent interventions combining wearables with physiotherapist feedback, telephone counseling, web-based platforms, or interactive cognitive-motor training. Wearables used alone, as in the REACT trial, produced small or non-significant PA effects. In contrast, interventions integrating devices with personalized feedback, professional support, or digital platforms, such as PROMOTE and TASMANIA, were associated with more consistent improvements in PA, physical function, and cognitive outcomes. Multicomponent programs, such as PEER and ICMT, reported broader benefits, including cognition, balance, and reductions in sedentary behavior, though these findings derive from individual trials and require replication. Risk of bias, assessed with the Cochrane Risk of Bias tool version 2 (RoB 2.0), was rated as "some concerns" for five studies and low for only one, mainly due to gaps in randomization reporting, missing data, and lack of preregistration. Tentatively, and based on a very limited evidence base, wearables may have greater impact when embedded within broader behavioral systems, incorporating feedback, coaching, or interactive components, rather than when used in isolation as passive monitoring tools. Adherence and psychosocial outcomes appeared related to comfort and perceived usefulness among older adults, though larger and more robust trials are needed to confirm these patterns.

Humans

Webcam-Based Real-Time Visual Feedback During Baduanjin Practice in Older Adults: 6-Week Pilot Randomized Study.

BACKGROUND: Baduanjin qigong is a traditional mind-body exercise used to support balance and physical health in older adults. Age-related changes in proprioception may make accurate self-directed performance difficult without external guidance. OBJECTIVE: The aim of this study is to explore whether webcam-based real-time visual feedback delivered during supervised laboratory sessions was associated with differences in webcam-derived 2D pose discrepancy and movement consistency during Baduanjin practice in older adults. METHODS: A total of 31 older adults were enrolled, and 28 participants with complete analyzable records were included in this complete-case dataset (feedback group, n=14; nonfeedback group, n=14). All sessions were conducted face-to-face in a supervised motion-analysis laboratory. Weekly 2D pose-discrepancy values were analyzed using a linear mixed-effects model with fixed effects for group, categorical week, and the group-by-week interaction and a participant-specific random intercept. Joint- and movement-specific participant-level 6-week means were analyzed exploratorily using Welch independent-samples t tests. Holm correction was applied across 24 exploratory contrasts (6 week-specific, 8 joint-specific, and 10 movement-specific comparisons), and Hedges g and 95% CIs were reported. Participant-specific weekly slopes and within-participant variability were additionally examined to directly assess longitudinal error drift. RESULTS: The linear mixed-effects model showed no significant group-by-week interaction (Wald &#x3c7;25=1.09; P=.96) and no significant overall week effect (Wald &#x3c7;25=6.40; P=.27). Averaged across 6 weeks, the feedback group had an estimated mean 2D pose discrepancy 1.20&#xb0; lower than the nonfeedback group (95% CI -2.38&#xb0; to -0.02&#xb0;; P=.046), although this marginal pilot finding was sensitive to an analytic approach. No week-specific contrast remained significant after Holm adjustment. Nominal right elbow, right shoulder, and right knee differences did not survive global Holm correction. Form 3 showed a lower mean discrepancy in the feedback group (mean difference -3.70&#xb0;, 95% CI -5.86&#xb0; to -1.54&#xb0;; Hedges g=-1.30; unadjusted P=.002; Holm-adjusted P=.04). Direct analyses of participant-specific slopes and within-participant SDs did not support a significant between-group difference in longitudinal error drift. CONCLUSIONS: In this small exploratory pilot study conducted under supervised laboratory conditions, the 6-week trajectories did not differ significantly between groups. A marginally lower average 2D pose discrepancy was observed in the feedback group across the 6 weeks, but no individual week- or joint-specific comparison remained significant after multiplicity adjustment. Form 3 was the only exploratory contrast that remained significant after global Holm correction. Direct longitudinal analyses did not demonstrate prevention of error drift. Larger studies using validated reference measurements, prespecified outcomes, and adequately powered longitudinal designs are required.

Humans

Adolescents' Growing Sensitivity to Psychosocial Stressors: Evidence From Two Decades of Health Behaviour in School-aged Children (HBSC) Data in the Nordic Countries.

PURPOSE: We tested a perception-based explanation for rising psychosomatic complaints among adolescents in the Nordic countries. Specifically, we examined whether adolescents have become more sensitive to psychosocial stressors, reflected in stronger associations between stressors and psychosomatic complaints in 2022 than in 2002. METHODS: Data were drawn from the 2002 to 2022 waves of the Health Behaviour in School-aged Children survey among 15-year-olds in five Nordic countries (N = 7,263 in 2002 and 6,739 in 2022). Psychosomatic complaints were examined in relation to stressors in the following three domains: interpersonal relationships, school-related strain, and body- and activity-related factors. Moderated regression analyses tested whether associations between stressors and complaints differed between survey years. Sex and perceived family finances were included as covariates. RESULTS: Four of five psychosocial stressors showed stronger associations with psychosomatic complaints in 2022 than in 2002. Perceived poor family finances, although less prevalent in 2022, were more strongly related to complaints. Girls consistently reported higher levels of psychosomatic complaints, and the association between school pressure and complaints was stronger among girls. DISCUSSION: Although several psychosocial stressors declined in prevalence, their associations with psychosomatic complaints strengthened over time. These findings suggest that rising complaints may reflect changes in how psychosocial stressors are linked to adolescents' psychosomatic symptoms, rather than increases in exposure to those stressors. This shift highlights the importance of considering how adolescents interpret and respond to everyday stress when addressing population trends in mental health.

Humans

Uce-based phylogeny and classification of Megachilini.

The generic-level classification of the bee tribe Megachilini (Megachilidae) has remained controversial due to poor phylogenetic resolution at the base of the group, particularly among the brood parasitic genera and the numerous dauber ("Chalicodoma s. l.") lineages. We present a phylogenomic analysis of Megachilini based on ultraconserved elements (UCEs), sampling 52 ingroup taxa with emphasis on the dauber lineages. We also present a combined UCE&#xa0;+&#xa0;six-gene analysis to improve taxon coverage, resulting in a dataset with 127 ingroup taxa. Maximum likelihood, coalescent, and Bayesian analyses of multiple UCE matrices recover largely congruent topologies with substantially improved support relative to previous studies. Our results strongly support the monophyly of Megachilini, the early divergence of Noteriades and Gronoceras, and a single origin of brood parasitism. All remaining non-parasitic Megachilini form a moderately supported clade sister to the brood parasitic lineage. The leafcutter bees are monophyletic and nested within dauber lineages. Several major dauber clades are consistently recovered, including an exclusively Australian clade corresponding to the Hackeriapis group of subgenera, while several recognized subgenera are paraphyletic. The lineage known as Morphella, previously placed in synonymy with the subgenus Callomegachile, was not closely related to that subgenus and is here treated as a valid subgenus. Divergence-time analyses place the crown age of Megachilini in the late Eocene to early Oligocene, with major extant lineages diversifying during the Miocene. Limited morphological diagnosability of several clades indicates that splitting non-parasitic lineages into numerous genera would result in an impractical classification that would widen the gap between taxonomists and non-specialists and exacerbate the taxonomic impediment in bees. We therefore advocate retaining a single genus Megachile for non-parasitic Megachilini (excluding Noteriades and Gronoceras), as the classification best supported by phylogenomic evidence and most robust to future taxon sampling.

Animals

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&#x202f;&#xd7;&#x202f;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

Comparison of opioid-free versus opioid-based total intravenous anaesthesia in elderly patients undergoing short-duration surgery: a randomized controlled trial.

INTRODUCTION: Older adults who undergo short-duration surgery are vulnerable to opioid-related complications. It is uncertain whether an opioid-free total intravenous anaesthesia (OFA) can reduce these events. We aimed to determine whether OFA reduces the incidence of major postoperative adverse events compared with standard opioid-based total intravenous anaesthesia (OBA). PATIENTS AND METHODS: This single-center randomized clinical trial was conducted in China. From May to August 2025, 400 patients aged &#x2265;60&#x2009;years undergoing elective, short-duration surgery (anticipated duration of less than 90&#x2009;min) were randomized 1:1 to receive either OFA (n&#x2009;=&#x2009;200) or OBA (n&#x2009;=&#x2009;200). The primary outcome was a composite of postoperative hypoxemia, delirium, or nausea and vomiting (PONV) within 48&#x2009;h. RESULTS: A total of 400 randomized patients (mean [SD] age, 69.5 [7.0] years; 125 [31.3%] women). The primary composite outcome occurred in 50 patients (25.0%) in the OFA group and 87 patients (43.5%) in the OBA group (adjusted odds ratio, 0.40; 95% CI, 0.25 to 0.62; p < .001). Among the OFA group had a lower incidence of hypoxemia (15.0% vs 32.0%) and PONV (8.0% vs 16.0%). Intraoperative hemodynamic stability was greater in the OFA group. However, the OFA group had a higher incidence of intraoperative bradycardia (10.0% vs 3.0%; p = .005) and longer extubation times (mean, 9.5 vs 7.2&#x2009;min; p < .001). CONCLUSION: These findings suggest that OFA is a viable alternative to opioid-based anesthesia for improving postoperative outcomes by reducing the incidence of hypoxemia and PONV in this population, while warranting careful management of its associated side effects. TRIAL REGISTRATION: Chinese Clinical Trial Registry, ChiCTR2500102550.

Humans

Status of dementia care among healthcare practitioners in Nigerian tertiary hospitals: a cross-sectional study.

BACKGROUND/OBJECTIVES: Dementia is an escalating public health concern globally. This study evaluated the knowledge, attitudes, practices, and perceived barriers to dementia care among healthcare practitioners in Nigerian tertiary hospitals, aiming to identify practitioner-related sociodemographic predictors and systemic barriers affecting dementia care delivery. METHODS: We collected data from May 2024 to May 2025 for this cross-sectional study in 12 purposively selected tertiary hospitals across Nigeria's six geopolitical zones. Participants included physicians, nurses, pharmacists, and other professionals involved in geriatric psychiatric care. Using multistage and convenience sampling, 394 respondents were recruited (response rate: 99.5%). Data were collected via a validated Dementia Care Practice Questionnaire (Cronbach's &#x3b1; = 0.84) and analyzed with SPSS v22. Descriptive statistics, Chi-square tests, and odds ratios (ORs) identified associations (significance: p &#x2264; 0.05). RESULTS: Of 394 respondents, 51.5% were aged &#x2265;40 years, and 54.8% were female. While 62.9% demonstrated adequate knowledge, negative perceptions (51.3%) and attitudes (56.9%) were common. Despite this, 71.3% reported engagement in dementia care, and 75.6% demonstrated appropriate professional help-seeking behaviour when confronted with dementia care challenges. Practitioner-reported barriers included limited training opportunities, geographical barriers affecting patient access to dementia services, and inadequate staffing. Predictors of desirable care practices among healthcare practitioners included age &#x2265;40 years, female gender, Christian affiliation, and &#x2265;5 years of professional experience. CONCLUSION: Although many healthcare practitioners are involved in dementia care, gaps in perceptions, attitudes, and structural support persist. Interventions should focus on targeted training, system strengthening, and policy reform to improve dementia care outcomes.

Barriers to care

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