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Exploring determinants of vaccine hesitancy among healthcare professionals: a systematic literature review.

INTRODUCTION: This systematic review aims to assess determinants of vaccine hesitancy (VH) among healthcare professionals, to identify knowledge gaps and inform targeted training programs. RESEARCH DESIGN AND METHODS: A systematic search of PubMed and Scopus was conducted in February 2024. PRISMA criteria were applied, and methodological quality was assessed using a cross-sectional study evaluation tool. Studies addressing HCWs' VH determinants, including knowledge, attitudes, communication, and organizational factors, were included. RESULTS: Out of 1394 records, 221 articles were included. Reported prevalence of VH among HCWs varied across studies, reflecting differences in professional roles, settings, and vaccines studied. Key determinants included gaps in knowledge, personal beliefs, organizational barriers, and communication skills. The review highlights the importance of evidence-based information, continuing education, and effective communication in addressing VH among HCWs. CONCLUSIONS: Educational and organizational interventions are essential to improve HCWs' knowledge, attitudes, and practices regarding vaccination. Strengthening vaccine education, fostering effective communication, and addressing organizational challenges can reduce hesitancy and support HCWs in promoting vaccination among patients. Future initiatives should consider the diversity of educational settings, professional roles, and training requirements across healthcare systems.

Humans

Evaluation of three Aspergillus antibody assays for screening of chronic pulmonary aspergillosis: prospective diagnostic accuracy study.

OBJECTIVES: Chronic pulmonary aspergillosis (CPA) is a frequent complication of pulmonary tuberculosis (PTB), particularly in high-burden settings where access to reliable serological diagnostics remains limited. We evaluated the diagnostic performance of two immunochromatographic technology (ICT) lateral flow assays (LFAs) and an ELISA for CPA screening among patients with active or previously treated PTB. METHODS: In this two-year prospective multicentre diagnostic evaluation, serum from adults with prior or active PTB was tested using the Era Biology Aspergillus IgG ICT LFA, LDBio Aspergillus IgG/IgM ICT LFA, and Bordier Aspergillus fumigatus IgG ELISA. CPA diagnosis was established using a consensus composite reference standard incorporating clinical, immunological, radiological, and microbiological criteria. The Bordier ELISA was used as part of the immunological component of the consensus CPA diagnosis, with a cutoff optical density of ≥1.0. Diagnostic accuracy, agreement statistics, receiver operating characteristic analysis, and latent class analysis (LCA) were performed. RESULTS: Among 340 participants, 24 (7.06%) had CPA. Proportion of participants with positive antibody tests among all tested individuals were 6.76% for LDBio ICT LFA, 20.0% for Era Biology ICT LFA, and 11.47% for Bordier ELISA. Against consensus CPA diagnosis, Bordier ELISA showed 87.50% sensitivity and 94.30% specificity, LDBio ICT LFA 58.33% sensitivity and 97.15% specificity, and Era Biology LFA 66.67% sensitivity and 83.54% specificity. LCA estimated CPA prevalence at 7.72%. LCA-derived sensitivities and specificities were 86.58% and 99.92% for LDBio ICT LFA, 83.39% and 85.31% for Era Biology LFA, and 79.10% and 94.19% for Bordier ELISA. CONCLUSIONS: The Bordier ELISA showed high sensitivity and specificity, while the LDBio ICT LFA demonstrated very high specificity with strong LCA-derived performance. These findings support the use of ELISA for laboratory diagnosis and ICT as a point-of-care screening tool for CPA in resource-limited settings. Era Biology Aspergillus IgG LFA demonstrated moderate sensitivity and acceptable diagnostic performance, indicating its potential utility as a supplementary screening assay for CPA in settings where rapid, point-of-care testing is required.

Humans

Experiences of stigma, bias, and communication challenges among pregnant healthcare workers: A systematic review of qualitative evidence.

BACKGROUND: Healthcare work environments are fraught with occupational hazards that can impact pregnant healthcare workers' health as well as patient care. Despite the feminization of healthcare globally, systematic discrimination against pregnant workers persists across diverse healthcare settings and cultural contexts. The intersection of stigma, bias, and communication challenges creates substantial barriers to career advancement and wellbeing. However, no systematic review has synthesized qualitative evidence on how these three constructs interact across healthcare professions and cultural contexts using an integrated theoretical framework. OBJECTIVE: To systematically review and synthesize qualitative evidence on experiences of stigma, bias, and communication challenges among pregnant healthcare workers across different healthcare settings and cultural contexts using an integrated theoretical framework. DESIGN: Systematic review of qualitative studies following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines with thematic synthesis. DATA SOURCES: Seven databases were searched from inception to January 2026. REVIEW METHODS: Included qualitative studies were appraised using the Critical Appraisal Skills Programme (CASP) checklist and synthesized through theory-guided thematic synthesis. Confidence was assessed using the Grading of Recommendations Assessment, Development and Evaluation-Confidence in the Evidence from Reviews of Qualitative research (GRADE-CERQual) approach. RESULTS: Fourteen studies encompassing 1223 participants across 17 countries revealed four major themes: (1) professional identity stigma and workplace discrimination through systematic labeling and stereotyping; (2) gender-based institutional bias rooted in masculine organizational logic; (3) multilevel communication failures creating fear-based climates; and (4) individual and collective resistance strategies developed despite constraints. Occupational hazards specific to pregnancy included exposure to infectious diseases, imaging, physical tasks, cleaning products, patient violence, and medication administration. Support from coworkers and supervisors was identified as the most critical facilitator for avoiding hazards and making necessary modifications, while the desire to be 'supernurses' and fear of consequences emerged as significant barriers. These patterns were consistent across healthcare professions, settings, and cultural contexts, with specialty culture and healthcare system type moderating discrimination intensity. Confidence in core findings was rated high using GRADE-CERQual. CONCLUSIONS: Pregnant healthcare workers globally experience interconnected stigma, bias, and communication challenges that are systematically embedded within healthcare organizational structures. These challenges operate synergistically, requiring comprehensive multilevel interventions beyond policy compliance. Healthcare organizations must implement evidence-based strategies addressing stigma reduction, bias interruption, and communication transformation simultaneously to retain skilled workers and ensure quality patient care.

Female

Impact of Commercial Artificial Intelligence on Radiologist Reading Time for Pulmonary Nodule Evaluation at Chest CT.

Background Chest CT is a primary method for identifying pulmonary nodules, yet interpreting scans remains time-intensive and demanding. Currently, artificial intelligence (AI) is expected to reduce reading times, but the effect of AI on reporting times in this setting is unknown. Purpose To evaluate the impact of a commercial AI software on radiologists' reading time for pulmonary nodule assessment on chest CT scans within a real-world clinical setting. Materials and Methods This retrospective study included patients who underwent chest CT examinations at a tertiary medical center between September 2021 and May 2024. The study period was divided into pre- and post-AI phases. The primary outcome was radiology reporting time. The association between AI implementation and reporting time was evaluated using a multivariable parametric Weibull shared frailty survival model adjusted for reader function, examination type, patient location, and requesting specialty, with clustering at the radiologist level. Interaction analyses assessed heterogeneity across prespecified subgroups. An exploratory extrapolation estimated projected workforce and financial impact. Results This study included 19&#x2009;433 patients (mean age, 62 years &#xb1; 14.2 [SD]; 21&#x2009;814 men; 39&#x2009;323 chest CT examinations, 19&#x2009;190 pre-AI, and 20&#x2009;133 post-AI). AI implementation was associated with faster report completion (adjusted hazard ratio, 1.17; 95% CI: 1.14, 1.21; P < .001). The adjusted median reporting time decreased from 21.3 minutes pre-AI to 18.2 minutes post-AI (14.6% reduction; P < .001). Heterogeneity was observed across reader function (P < .001), examination type (P = .048), and requesting specialty (P = .03). The largest relative reductions were observed for CT thorax electrocardiogram-gated examinations (-41.1%; P < .001) and thoracic radiologists (-25.0%; P < .001), whereas emergency department examinations showed increased median reporting time (7.1%; P < .001). At institutional scan volumes (approximately 20&#x2009;000-22&#x2009;000 chest CT examinations annually), exploratory modeling suggested an approximate reduction of 0.5 full-time equivalent radiologist workload. Conclusion Implementation of commercial AI-assisted pulmonary nodule assessment on chest CT scans reduced radiologist reporting time in a real-world clinical setting. &#xa9; The Author(s) 2026. Published by the Radiological Society of North America under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Iwasawa in this issue.

Humans

Artificial intelligence enabled social robotic interventions (PARO) in Australian dementia care: A systematic review and meta-analysis.

BACKGROUND: Although there is a growing body of research indicating that Personal Robot/Social Robot could be used in various aspects of care for individuals with dementia, little is known about how well these types of interventions work in an actual hospital setting in Australia. AIMS & OBJECTIVES: The objective of the present systematic review and meta-analysis is to assess the effectiveness of PARO-based socially assistive robotic intervention in terms of its effectiveness outcomes towards the reduction of dementia-related behavioural and psychological symptoms in Australian based healthcare settings. METHODS: A systematic search was conducted across five electronic databases, including MEDLINE (PubMed), EMBASE, CINAHL, PsycINFO, and the Cochrane Library, to identify randomised controlled trials (RCTs) investigating PARO-based socially assistive robotic interventions for dementia in Australian healthcare settings. This review was registered with PROSPERO (CRD420251251916) and followed the PRISMA 2020 guidelines. In addition, the Cochrane Risk of Bias tool (RoB 2) was used to evaluate the risk of bias across all studies. Pooled standardised mean differences (SMD) with 95&#xa0;% confidence intervals (CI) were calculated for agitation, anxiety, and depression. Heterogeneity across studies was evaluated using the I2 statistic. RESULTS: Six RCTs involving 1444 participants were identified for inclusion in this review. AI-enabled socially assistive robotic interventions, specifically the PARO therapeutic robot, significantly reduced agitation and anxiety when compared to standard treatment or control conditions. The pooled analysis showed that agitation [SMD&#xa0;=&#xa0;-0.44 (95&#xa0;% CI: -0.70, -0.18) p&#xa0;=&#xa0;0.0008] and anxiety [SMD&#xa0;=&#xa0;-0.59 (95&#xa0;% CI: -0.91, -0.27) p&#xa0;=&#xa0;0.0003] were reduced significantly, while the decrease in depression [SMD&#xa0;=&#xa0;-0.44 (95&#xa0;% CI: -0.95, -0.07) p&#xa0;=&#xa0;0.09] scores was non-significant among dementia patients receiving PARO-based socially assistive robotic interventions as compared to the control. The overall risk of bias across all six studies was considered low to moderate. CONCLUSION: PARO-based socially assistive robotic interventions may provide preliminary evidence of effectiveness in reducing agitation and anxiety in individuals with dementia in Australian healthcare, but the evidence regarding the reduction of depression remains unclear. Therefore, additional high-quality trials with consistent methodology and extended follow-up will be necessary to determine both the short-term and long-term clinical efficacy and practicality of implementing these interventions into practice.

Humans

List randomization for prevalence estimation of sensitive behavioral data among women with HIV of reproductive age in Lilongwe, Malawi.

Self-reported data are subject to reporting biases, including social desirability bias. List randomization is one method that can help mitigate the impact of such biases. Here, we examined the utility of list randomization among women of reproductive age living with HIV in sub-Saharan Africa. In the Family Planning and Antiretroviral Therapy study, participants were randomized to answer 5 blocks of true/false statements via either direct or list response. Each block contained 3 nonsensitive statements and 1 sensitive statement related to either condom use or HIV disclosure. For each sensitive statement, we calculated the prevalence difference (PD) comparing list response to direct response overall and stratified by socioeconomic status. The PD for 4 of the sensitive statements was negligible. However, we found that self-report of always using a condom was reported by 53.1% at list response visits vs 34.7% at direct response visits (PD, 18.5%; 95% CI, 6.2%-30.7%), a difference that was attenuated among those with higher socioeconomic status. In this setting, list randomization did not meaningfully change the estimated prevalence for most questions, except for one question, which unexpectedly produced a higher estimate for a positive behavior. Examining this method in other settings and populations is warranted.

Humans

Artificial intelligence-assisted detection and optical differentiation of colorectal lesions in Lynch syndrome surveillance (CADLY2): a multicentre, open-label, randomised controlled superiority trial.

BACKGROUND: Artificial intelligence (AI)-based computer-aided detection (CADe) systems improve adenoma detection in average-risk colorectal cancer screening. Meanwhile, evidence in Lynch syndrome surveillance is sparse and inconsistent. We assessed the effect of CADe on adenoma detection during Lynch syndrome surveillance. Computer-aided optical diagnosis (CADx) performance for optical differentiation of colorectal lesions was evaluated as a secondary aim. METHODS: CADLY2 was an international, multicentre, open-label, randomised controlled superiority trial at nine specialised hereditary cancer surveillance centres in Belgium, Germany, the Netherlands, and Spain. Adults aged 18 years or older with genetically confirmed Lynch syndrome scheduled for surveillance colonoscopy were randomly assigned (1:1) to high-definition white-light (HD-WL) colonoscopy alone or to HD-WL colonoscopy with computer-aided assistance from CAD EYE (Fujifilm, Tokyo, Japan). CAD EYE was used for CADe during withdrawal and for CADx after lesion detection. Randomisation was done centrally through a secure web-based system using Pocock's minimisation algorithm with a stochastic component and was stratified by centre, sex, previous colorectal cancer, underlying pathogenic variant, and interval since previous colonoscopy. Allocation concealment was ensured through the centralised web-based system. Patients were masked to group allocation until the start of withdrawal in procedures with mild sedation, or until completion of the procedure in procedures with propofol-based sedation. Endoscopists were not masked. The primary outcome was adenoma detection rate, defined as the proportion of patients with at least one histopathologically confirmed adenoma, analysed in the full analysis set (defined as all randomly allocated patients with available data for the primary outcome). The diagnostic performance of the CADx system was evaluated as a secondary outcome. The safety analysis set comprised all randomly allocated patients who underwent a study colonoscopy. This study is registered with the German Clinical Trials Register, DRKS00030695, and is completed. FINDINGS: Between May 9, 2023, and Oct 30, 2025, 757 patients were randomly allocated to HD-WL colonoscopy (377 patients) or to AI-assisted colonoscopy (380 patients); 733 patients were included in the full analysis set (369 HD-WL and 364 AI-assisted). The median age was 49 years (IQR 38-59) in the HD-WL group and 50 years (38-59) in the AI-assisted group; 213 (58%) were female and 156 (42%) male in the HD-WL group, and 207 (57%) were female and 157 (43%) male in the AI-assisted group. The adenoma detection rate was 30&#xb7;9% (114 of 369 patients) with HD-WL versus 33&#xb7;8% (123 of 364 patients) with CADe assistance (odds ratio 1&#xb7;14 [95% CI 0&#xb7;83-1&#xb7;57], p=0&#xb7;41). For CADx differentiation of neoplastic versus non-neoplastic lesions in the paired lesion-level analysis, with histopathology as the reference standard and sessile serrated lesions and traditional serrated adenomas classified as non-neoplastic, CADx sensitivity was 85&#xb7;9% (95% CI 82&#xb7;0-89&#xb7;1) and specificity was 91&#xb7;4% (89&#xb7;4-93&#xb7;0). Three adverse events occurred in the AI-assisted group: two mild post-polypectomy bleedings and one serious pulmonary embolism or deep venous thrombosis unrelated to the procedure. No adverse events occurred in the HD-WL group. INTERPRETATION: CADe-assisted colonoscopy did not show the absolute improvement in adenoma detection rate that was assumed in the prespecified sample-size calculation. CADx did not clearly improve lesion differentiation beyond expert optical diagnosis in expert Lynch syndrome surveillance settings. FUNDING: Third-party research funding of the National Center for Hereditary Tumor Syndromes, University Hospital Bonn.

Humans

A genome-wide coverage-based pipeline for the identification of host-derived candidate DNA biomarkers from cell-free blood.

We have created a new data-analysis pipeline for the discovery of host-specific candidate DNA biomarkers derived from sequencing data of cell-free blood. Unlike approaches that rely on specific molecular or genetic signatures, our method leverages the coverage distribution of cell-free DNA sequences mapped to a reference genome, applying statistical analyses to identify informative short genomic regions for biomarker discovery. The pipeline is applicable to diverse diseases and can be used to analyze cell-free DNA sequences from plasma or serum to identify candidate biomarkers that are characteristic of disease states in mammals. Core functionalities were developed in Java and integrated with open-source software tools for the preprocessing of raw sequencing data, complemented by Python scripts for the machine-learning analysis and statistical validation. The pipeline is designed for HPC use and users can access the pipeline through a Galaxy workflow, which offers a user-friendly web interface for input selection prior to execution and analysis progress monitoring. Performance tests, carried out using duplicate sets of COVID-19 samples and controls, showed linear scalability of execution time with an increasing dataset size, as well as a substantial reduction in execution time through parallelized computation, whereby each HPC node is used to process the data of one chromosome. Further statistical tests confirmed the quality of the pipeline's results by showing that the set of identified candidate biomarkers remained stable across varying dataset sizes.

Biomarkers

A User-Friendly Protocol for Microinjection into Teleost Embryos to Study Gene Function.

Zebrafish (Danio rerio) and medaka (Oryzias latipes) are popular teleost models used in developmental biology and functional genomics. To achieve high-quality and reproducible microinjections, it is essential to have robust protocols for breeding, egg collection, and the precise delivery of genetic material. In this protocol, we present a comprehensive and optimized methodology for setting up breeding tanks under controlled photoperiod conditions to maximize egg yield while minimizing contamination. We provide detailed procedures for sex identification, pair selection, the use of grated breeding inserts, and methods to increase egg collection efficiency. We outline procedures for making injection gel beds, pulling needles, and calibration using one-microliter microcapillaries to achieve consistent nanoliter-scale injections. Our protocol outlines settings for the pico-liter injector that are optimized to deliver a precise amount per pulse with minimal variability. Finally, we demonstrate the application of these methods for gene knockdown using morpholino antisense oligonucleotides, gene knockout using CRISPR-Cas9, and gain-of-function mRNA overexpression experiments. Phenotypic assessments conducted at various developmental stages to evaluate gene-specific effects reveal consistent phenotypic outcomes between the morpholino and CRISPR-Cas9 approaches. This easy and comprehensive protocol enables efficient, precise, and scalable genetic manipulation of zebrafish and medaka embryos, thereby supporting advanced functional studies in developmental biology and disease modeling. To our knowledge, this is the first unified protocol for both zebrafish and medaka microinjection systems achieving 97.7% phenotype penetrance in CRISPR-Cas9 knockouts with precision together with a triple validation approach that confirms gene function across multiple techniques.

Animals

Population-level impact of HPV vaccination: a global systematic review of ecological, cross-sectional, and cohort studies.

BACKGROUND: Human papillomavirus (HPV) causes approximately 4.5% of cancers globally, with the highest burden in low- and middle-income countries (LMICs). Since their introduction in 2006, HPV vaccination programs have led to substantial declines in HPV-related outcomes, although impact varies across settings. RESEARCH DESIGN AND METHODS: We conducted a systematic review to evaluate the population-level impact of HPV vaccination on HPV infection, cervical intraepithelial neoplasia grade 2 or higher (CIN2+), genital warts, invasive cervical cancer (ICC), and oropharyngeal cancer (OPC), and examined the influence of coverage, age at initiation, and vaccine type. The review followed PRISMA 2020. RESULTS: Of 13,549 records screened, 63 were included: 9 assessed HPV infection, 24 on CIN2+, 25 on genital warts, and 7 on ICC. Greatest reductions were observed in settings with at least 70% coverage and early vaccination prior to sexual debut, typically achieved through school-based programs. Reported declines ranged from 58-100% for HPV infection, 30-88% for CIN2+, 60-90% for genital warts, and 70-88% for ICC. CONCLUSIONS: HPV vaccination offers strong protection, especially when delivered early and at high coverage within schools. Expanding access and prioritizing underserved populations are essential to achieving global cancer prevention goals. Limitations include heterogeneity across designs, outcome definitions, and follow-up.

Humans

Reliability-aware hierarchical learning for Chagas disease screening from 12-lead ECGs: tackling label uncertainty and class imbalance.

Objective.Chagas disease, a neglected tropical disease (NTD) with significant cardiovascular impact, remains underdiagnosed in resource-limited regions. Electrocardiogram (ECG) screening offers a low-cost tool for detecting cardiac involvement, yet algorithm development is challenged by label noise, data scarcity, and the latent nature of infection. This study proposes a robust ECG-based screening framework that explicitly addresses these constraints.Approach.We introduce aReliability-Aware Hierarchical Learningstrategy that calibrates supervision according to data provenance, prioritizing serology-confirmed labels over noisy self-reports. To mitigate data scarcity, we compare a specialized convolutional neural network (CNN) trained from scratch with a transfer learning approach based on a Spatio-Temporal ECG foundation Model (FM). Performance is evaluated across varying data scales, and the representation structure is analyzed to interpret model behavior.Main results.On the official hidden test set of the George B. Moody PhysioNet/Computing in Cardiology Challenge 2025, our approach achieved a Challenge Score of 0.163. We observe that while the specialized CNN performs competitively in data-rich regimes, the FM exhibits superior robustness in extreme low-resource settings. Furthermore, performance reaches a plateau imposed by underlying disease physiology. Bimodal score distributions suggest that models distinguish established cardiomyopathy from indeterminate infection, which remains electrophysiologically indistinguishable from healthy controls.Significance.These findings clarify both the potential and intrinsic limits of ECG-based AI screening for NTD-associated cardiac involvement. Reliability-aware supervision and data-efficient transfer learning provide a practical framework toward scalable and clinically meaningful ECG screening systems in resource-constrained environments.

Humans

Temporal redistribution of control reveals age-related differences in task switching at the level of preparation.

Task-switching studies often report minimal age-related differences in switch costs, leading to the conclusion that switching-related control processes are relatively preserved in aging. However, this conclusion is based on paradigms that confound preparatory and execution processes. This study examined whether age-related differences in semantic task-set reconfiguration may be underestimated due to this confound. In Experiment 1 (36 young and 30 older adults), participants performed an externally paced task-switching paradigm without control over preparation. In Experiment 2 (28 young and 28 older adults), a self-paced paradigm allowed participants to initiate stimulus onset, enabling measurement of preparation time. Across both experiments, reaction time (RT) and error rate (ER) showed reliable age effects but no interactions between age and condition, whereas switching-related condition effects varied across measures and experiments. The expression of switching-related costs differed across measures and task structures. Local switch costs were expressed in ER in Experiment 1 but in RT in Experiment 2. Global switch costs (all-switch vs. all-repeat) were observed in execution measures only in Experiment 1. In Experiment 2, preparation time showed reliable mixing, local, and global switching effects, with age-related amplification emerging specifically for global switching. These findings indicate that switching-related costs are redistributed across processing stages and behavioral measures. The results suggest that age-related modulation of semantic task-set reconfiguration may emerge more clearly during preparation than task execution, particularly under continuous switching demands. Preparation time is interpreted cautiously as reflecting participant-regulated preparatory processes rather than a pure measure of preparation efficiency.

Humans

Applications and outcomes of virtual reality in inpatient psychiatry: A systematic review.

BACKGROUND: Virtual reality (VR) has been widely used in outpatient psychiatric services and has demonstrated benefits across several clinical diagnoses, but its use and effects in inpatient settings remain to be explored. This systematic review aimed to examine the use of VR during psychiatric hospitalization, including types of VR applications, barriers and facilitators of implementation, and effects on various outcomes. METHODS: The review was registered in PROSPERO (#CRD42023446524). Following PRISMA guidelines, databases (Ovid, SciVerse, Web of Science, Cochrane Library, ProQuest, and WorldCat) were searched from 1983 to 2025 using keywords related to VR and psychiatric disorders. Studies involving the use of VR with psychiatric inpatients (&#x2265;85%) were included. Descriptive statistics and narrative syntheses were used to summarize findings. Study quality was assessed with the Mixed Methods Appraisal Tool. RESULTS: After full-text screening, 37 studies (N&#xa0;=&#xa0;1,004) met inclusion criteria. VR was used for both assessment and intervention, with cognitive-behavioral therapy/exposure (35%) and assessment (24%) being the most frequently used. VR use in inpatient units appeared feasible, acceptable, and safe for inpatients and clinicians, though findings remain preliminary. Several facilitators (e.g. adequate staff training and supervision) and common barriers (e.g. technical difficulties and limited resources) were identified. The most consistent improvements were observed in clinical symptoms (e.g. anxiety) compared with psychosocial, cognitive, and physiological outcomes. CONCLUSIONS: These findings suggest that inpatient settings represent a promising, yet understudied context for VR-based assessments and interventions. High-quality trials and systematic reporting of implementation are needed in future studies to inform research and clinical practice.

Humans

Adolescent health across Asia Pacific, 2000-23: a systematic analysis for the Global Burden of Disease Study 2023.

BACKGROUND: The Asia Pacific region is home to more than half of the world's 1&#xb7;93 billion adolescents (aged 10-24 years). Addressing adolescent health in this region is of global importance, but to date a systematic analysis of key contributors to disease in adolescents has not been done, which is a barrier to responsive action. This systematic analysis of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2023 aims to provide a comprehensive assessment of adolescent health across the Asia Pacific region, at both the subregional and national levels, encompassing burden of disease, mortality, and prevalence of adolescent risk factors. METHODS: As part of GBD 2023, we obtained estimates for cause-specific mortality, disability-adjusted life-years (DALYs), and risk factor prevalence by sex for adolescents aged 10-24 years and 5-year age groups (10-14 years, 15-19 years, and 20-24 years) across 44 countries and territories (hereafter referred to collectively as Asia Pacific), grouped by seven UN subregions, from 2000 to 2023. We extracted GBD 2023 population counts and estimates of number and rate (per 100&#x2008;000 population) for mortality and disease burden (DALYs). Risk prevalence estimates were obtained directly from the Institute for Health Metrics and Evaluation, and binge drinking estimates were sourced from WHO. Estimates are reported with 95% uncertainty intervals (UIs) where possible. UIs were estimated by running 250 draws of the posterior distribution, ordering the draws, and selecting the 2&#xb7;5th and 97&#xb7;5th percentiles for each metric. FINDINGS: In 2023, in adolescents across Asia Pacific, there were 637&#x2008;496 deaths and a total disease burden of 115&#xb7;8 million DALYs, representing 34&#xb7;1% of global adolescent deaths and 40&#xb7;6% of the global adolescent burden of disease. Non-communicable diseases (NCDs; particularly mental disorders) were the leading causes of disease burden and mortality (64&#xb7;8% of DALYs and 43&#xb7;9% of deaths). Unintentional and transport injuries were also leading causes of death (14&#xb7;7% of deaths due to transport injury and 13&#xb7;3% of deaths due to unintentional injury) and leading causes of disease burden particularly among males in south-eastern Asia. In Melanesia, Micronesia, and some parts of south-eastern Asia (Cambodia, Indonesia, Laos, the Philippines, and Timor-Leste), respiratory infections and tuberculosis remained important contributors. Southern Asia had the largest reduction (1&#xb7;5% per year) in all-cause DALYs over the study period, and Australia and New Zealand (0&#xb7;2% per year) had the smallest, with females in Australia and New Zealand showing a slight increase contrary to regional trends. Eastern Asia had the largest reduction (2&#xb7;8% per year) in all-cause mortality rate and Melanesia (0&#xb7;8% per year) the smallest. Risk factors generally had between-subregion and within-subregion variation; however, some regional trends stood out, with overweight and obesity increasing in all countries across the region, and binge drinking increasing in more countries than not. In 2023, prevalence of smoking in males exceeded that in females in every country, from 40% difference in Timor-Leste to less than 1% difference in Australia. Anaemia prevalence is decreasing in all countries, but female prevalence was higher and reducing at a slower rate than in males. Bullying prevalence was slightly higher in Polynesia, Micronesia, and Melanesia combined, Australia and New Zealand, and eastern Asia compared with southern and south-eastern Asian subregions. INTERPRETATION: Several patterns were consistent across the region: the dominance of mental disorders and NCDs, the universal rise in overweight and obesity (particularly high in Oceanic countries but increasing rapidly in south and south-eastern Asia), and persistent sex-specific challenges across subregions: unintentional injuries and smoking in males, and anaemia in females. Actions to tackle shared risk factors (while accounting for context-specific local health profiles, workforce deficits, cultural factors, and health system capacity) should not be forgone due to local variation. Future research could focus on subnational variation, intersecting inequalities, and multi-sectoral interventions targeting shared risk factors. Priority actions should include regional investment in adolescent mental health services and obesity prevention, targeted injury reduction strategies for high-risk populations, and sex-specific approaches to smoking cessation and anaemia reduction, delivered through local health systems with the capacity and cultural responsiveness to meet local needs. FUNDING: Gates Foundation and Australian Government.

Humans

Ibuprofen versus acetaminophen for acute mild-to-moderate pain management in pediatric populations: a systematic review and meta-analysis of their efficacy.

UNLABELLED: Ibuprofen and acetaminophen are the most widely used analgesics in pediatric practice for the management of acute mild-to-moderate pain. Despite their widespread use, the comparative analgesic efficacy of these two agents in children remains a subject of ongoing debate, with existing evidence largely derived from heterogeneous clinical settings and small individual trials. Therefore, this study aimed to systematically review and meta-analyze randomized controlled trials comparing the analgesic efficacy of ibuprofen versus acetaminophen in pediatric populations with acute mild-to-moderate pain. A systematic literature search was conducted up to May 2026 in PubMed, Scopus, and Web of Science. The review was conducted and reported in accordance with the PRISMA-Children and Adolescents (PRISMA-C) 2026 reporting guideline. Eligible studies were randomized controlled trials comparing ibuprofen with acetaminophen in children and adolescents (defined as individuals aged 0 to&#x2009;<&#x2009;18&#xa0;years) with acute pain, reporting at least one extractable efficacy outcome. Continuous outcomes were synthesized as standardized mean differences (Hedges' g) using random-effects models; dichotomous outcomes were pooled as risk ratios (RRs) with 95% confidence intervals. Risk of bias was assessed using the Cochrane RoB 2 tool and certainty of evidence was evaluated using the GRADE framework. Eight randomized controlled trials enrolling 1325 participants were included. Three pediatric trials contributed to the primary continuous pain outcome meta-analysis (n&#x2009;=&#x2009;196 analyzable participants), yielding a pooled SMD of&#x2009;-&#x2009;0.28 (95% CI&#x2009;-&#x2009;0.57 to 0.00; p&#x2009;=&#x2009;0.052; I2&#x2009;=&#x2009;0%), indicating a small effect favoring ibuprofen that did not reach conventional statistical significance. Given the small number of contributing studies (k&#x2009;=&#x2009;3), the I2 statistic should be interpreted with caution as it has limited power to detect heterogeneity in this context. For the dichotomous pain freedom outcome (2 trials, n&#x2009;=&#x2009;114), no significant difference was observed (pooled RR 1.03, 95% CI 0.53-1.99; p&#x2009;=&#x2009;0.93; I2&#x2009;=&#x2009;0%). A prespecified sensitivity analysis including an adult soft-tissue injury trial attenuated the pooled effect toward the null (SMD&#x2009;-&#x2009;0.15, 95% CI&#x2009;-&#x2009;0.38 to 0.09; p&#x2009;=&#x2009;0.23; I2&#x2009;=&#x2009;36.6%). Narrative synthesis of additional studies generally demonstrated comparable analgesic efficacy between the two agents across postoperative and outpatient pediatric settings. The overall certainty of evidence was rated as low for both primary outcomes, primarily due to imprecision and indirectness. CONCLUSION: Current evidence from randomized controlled trials does not demonstrate a superiority of ibuprofen over acetaminophen for acute mild-to-moderate pain management in children. Both agents appear to provide clinically meaningful analgesia across heterogeneous pediatric pain settings. The clinical choice between agents should be guided by individual patient factors, including contraindications to NSAIDs, the inflammatory nature of the pain etiology, and patient-specific characteristics. The low certainty of evidence underscores the need for adequately powered, methodologically rigorous trials to definitively establish the comparative efficacy of these two analgesics in the pediatric population. WHAT IS KNOWN: &#x2022; Ibuprofen and acetaminophen are the two most widely used non-opioid analgesics for acute mild-to-moderate pain in children, and both are recommended as first-line agents by major international guidelines. &#x2022; Prior meta-analyses in mixed pediatric-adult populations have suggested a modest analgesic advantage of ibuprofen over acetaminophen, but pediatric-specific evidence has remained limited and methodologically heterogeneous. WHAT IS NEW: &#x2022; This systematic review and meta-analysis, restricted to randomized controlled trials in pediatric populations, found that ibuprofen showed a small effect favoring pain reduction compared with acetaminophen (SMD&#x2009;-&#x2009;0.28, p&#x2009;=&#x2009;0.052), although this did not reach conventional statistical significance. &#x2022; The analgesic advantage of ibuprofen may be more pronounced in pain etiologies with a significant inflammatory component (e.g., fractures). At the same time, both agents appear broadly equivalent in most other acute pediatric pain settings, supporting individualized analgesic selection based on clinical context and patient-specific factors.

Humans

Emerging hantavirus risks in mass gatherings: epidemiology, diagnostic challenges, and outbreak preparedness.

Hantaviruses are emerging rodent borne zoonotic pathogens of increasing global public health concern because of their high mortality, expanding ecological distribution, and potential for international dissemination. Although traditionally associated with sporadic rural outbreaks, recent ecological disruption, climate variability, urbanization, and increased global mobility have heightened concerns regarding hantavirus risks in mass gathering settings. This review critically examines the epidemiology, transmission uncertainty, diagnostic and surveillance challenges, and preparedness strategies related to hantavirus infections in the context of mass gatherings, including religious events, refugee settlements, cruise tourism, sporting events, and temporary accommodations. Particular emphasis is placed on the 2026 multinational cruise ship associated outbreak linked to the MV Hondius, which highlighted vulnerabilities related to delayed diagnosis, international passenger dispersal, and uncertainties surrounding possible human to human transmission of Andes virus. Current evidence indicates that hantavirus transmission occurs primarily through inhalation of aerosolized rodent excreta; however, controversies regarding limited interpersonal transmission, environmental persistence, and asymptomatic infections continue to complicate risk assessment and outbreak preparedness. Diagnostic limitations, underreporting, insufficient environmental surveillance, and lack of mass gathering specific preparedness frameworks remain major public health challenges, especially in resource limited settings. Strengthening proactive preparedness through integrated One Health approaches, ecological surveillance, genomic monitoring, AI driven epidemic intelligence, and coordinated international response systems is essential for mitigating future risks. The review emphasizes the urgent need for multidisciplinary research and evidence based policy development to improve global preparedness against emerging hantavirus associated threats in increasingly interconnected mass gathering environments.

Humans

Care navigation for older adults after stroke - A systematic review and meta-analyses to guide social prescribing.

INTRODUCTION: Stroke affects many older people worldwide, and patient navigation and social prescribing (e.g., care navigation) may help recovery. We aimed to synthesize evidence on the effect of care navigation for people living with the effects of a stroke (PLWS) on anxiety, depression, quality of life, and well-being. Our secondary focus was to explore these models in rural settings. METHODS: We conducted a systematic review following guidelines, and searched for peer-reviewed randomized controlled trials for older adults (60 years+ or group mean age in this range) who had a stroke and received patient navigation or social prescribing. Two authors independently screened citations at Level 1 (title and abstract) and Level 2 (full text). The date of the last updated search was December 5, 2025. We synthesized data quantitatively using meta-analyses (random effects model and standard mean difference). RESULTS: We identified 11 studies using patient navigation, but no social prescribing interventions. The total number of PLWS participants at baseline was 7829 with an average mean age of 68 years (43% women). There were no differences between groups for anxiety or quality of life for PLWS, but there was a difference favouring the intervention for depression, although the findings were no longer significant with sensitivity analyses. Thus, results should be interpreted with caution. Only two studies provided data for caregivers, with mixed findings. No studies focused on well-being or rural settings. CONCLUSIONS: Care navigation for PLWS needs more research, including testing social prescribing within stroke rehabilitation in rural and urban locations. SYSTEMATIC REVIEW REGISTRATION: PROSPERO 2025 CRD420251077958.

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Applications of quantum AI in brain disorder diagnosis: A systematic review.

BACKGROUND AND OBJECTIVE: Brain disorder diagnosis and prediction remain challenging because neuroimaging, electrophysiological, behavioral, and multimodal data are high-dimensional, noisy, heterogeneous, and limited by small clinical cohorts. This systematic review synthesised applications of quantum artificial intelligence (QAI) for brain disorder diagnosis, prediction, detection, and monitoring. METHODS: Following PRISMA guidelines, studies published from 2016 to 13 January 2026 were retrieved from Scopus, Web of Science, and IEEE Xplore. After screening, 36 studies met the eligibility criteria and were qualitatively analysed according to disorder category, data modality, QAI method, implementation setting, validation strategy, and performance. RESULTS: At the broader disease-group level, neurodegenerative disorders were the most frequently investigated, followed by mental health and psychiatric disorders. At the individual level, Parkinson's disease and schizophrenia were the leading applications, followed by depression, anxiety, Alzheimer's disease, and stress-related tasks. MRI-based modalities were the most frequently used data source, followed by multimodal data and EEG. Methodologically, primary QAI approaches were dominated by quantum neural and QDL architectures, followed by quantum-inspired optimization or feature-selection methods and quantum-kernel/conventional QML classifiers. Qiskit/IBM Quantum and PennyLane were the most frequently reported quantum software frameworks. However, most studies relied on simulators, classical quantum-inspired implementations, or unclear implementation settings, with limited real-hardware evaluation. CONCLUSIONS: QAI shows emerging potential for brain disorder analysis, particularly through hybrid quantum-classical learning, quantum neural architectures, quantum-kernel methods, and quantum-inspired optimization. Nevertheless, current evidence remains preliminary and requires larger datasets, subject-level and external validation, fair classical benchmarking, noise-resilient circuits, real quantum hardware evaluation, explainability, and clinical validation.

Humans