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Malaysia is a multicultural country with the main ethnic groups being Malays, Chinese, and Indians. This diversity creates a rich food culture with distinct dishes, cooking styles, and portion sizes, making dietary assessment challenging. Intake24 is a web-based 24-hour dietary recall (24hDR) system that automates data collection, reduces recall bias, and saves time. It supports self-reporting of the previous day's food and beverage intake using structured prompts, searchable food lists, portion-size images, and linked food composition data. As it was originally developed in the United Kingdom, adaptation for Malaysia is needed to address differences in language, food culture, mixed dishes, portion sizes, terminology, and local food composition data. This paper aims to describe a protocol for the development and relative validation of Intake24 Malaysia (Intake24-MY) for the Malaysian population. This paper describes 2 phases in adapting Intake24-MY: (1) the development process and (2) the validation study. Phase 1 consists of the following components: (1a) system translation, which will involve machine translation tools and bilingual translators; (1b) food list development, which includes Malaysian and globally familiar foods; (1c) 4 options for portion-size estimation and a photograph validation study; (1d) food composition data and recipe calculation; (1e) small-scale testing, which will involve 10 adults identifying the foods and technical issues, with pilot testing conducted among 100 adults to compare 2 days of dietary intake using Intake24-MY against an interviewer-led 24hDR; and (1f) user guide development. Phase 2 consists of the following components: (2a) a single-meal validation study that will be conducted among 100 adults, comparing Intake24-MY with observed intake and (2b) a cross-sectional study that will be conducted among 482 Malaysian adults, comparing 4 days of dietary intake using Intake24-MY against an interviewer-led 24hDR. A structured questionnaire will be used to assess the feedback on the usability of Intake24-MY. The Bland-Altman method will be used to determine the agreement between these methods. The study was funded in December 2023, with data collection starting in June 2024 and continuing. Data analysis is set to begin in August 2026, with results expected by 2027. This study has received approval from the Monash University Human Research Ethics Committee (MUHREC ID 41337). Intake24-MY is being developed as a multilingual digital dietary assessment tool for Malaysia. The planned validation study will determine its agreement with interviewer-led 24hDRs and assess its usability among Malaysian adults. If shown to be valid and acceptable, Intake24-MY can support more efficient dietary data collection in Malaysia's multicultural population.

Population-level data on people with limb loss (PwLL) are needed for effective prosthetic provision and rehabilitation. These data are rare in low- and middle-income countries, and low- and middle-income countries are routinely dealt with as homogenous entities. Here, we investigate intranational variation in PwLL populations in Sri Lanka using long-term routinely collected data from prosthetic and orthotic (P&O) clinics. Retrospective study. Until 2009, Sri Lanka experienced a 26-year civil war affecting primarily northern/eastern districts. Published data from 2 P&O centers in northern (Jaffna Jaipur Centre for Disability Rehabilitation, JJCDR; 1987-2018) and central (Centre for Handicapped, CFH; 1987-2024) districts were compared to investigate intranational variation in PwLL demographics and temporal trends. Summative statistics, &#x3c7;2, and Mann-Whitney U tests (&#x3b1; < 0.05) were used to quantify differences. Major differences included a larger population of males at the CFH (88.8%) compared with the JJCDR (77.4%) and-although war-related amputations were most common at both clinics-there were relatively more war-related amputees at the JJCDR (CFH: 44.8%; JJCDR: 62.7%). In addition, the JJCDR had a higher proportion of patients registered and injured in the same district (CFH: 62.22%; JJCDR: 66.11%). Intranational variation in PwLL populations exists in Sri Lanka as evidenced by differences in populations between northern and central P&O clinics. This points toward differences in provisional needs and temporal health/societal trends underlying limb loss, which must be considered when provisioning health services.

Systemic alterations are highly prevalent in the population and may interfere with peri-implant repair. The aim of this study was to investigate the association between systemic conditions with the loss of dental implants. This is a retrospective study following STROBE guidelines, including data from 602 medical records of patients who received dental implants between 2000 and 2017. Data on healthy status (presence or absence of disease or systemic conditions), use of prescribed medications (yes/no, and type), number of implants placed and lost, type of prosthetic rehabilitation, and follow-up period were collected, along with demographic data and local risk factor. Fisher's exact test assessed the association between systemic conditions and implant loss. Implant survival was analyzed using Kaplan-Meier and compared by the log-rank test (Mantel-cox). Binary logistic regression estimated odds ratios and confidence intervals for factors associated with implant loss. A total of 1872 dental implants were placed, including 743 in healthy patients (success rate: 96.76%) and 1129 in systemically compromised patients (success rate: 97.60%), with no significant difference between groups (p&#x202f;=&#x202f;0.1405). Kaplan-Meier analysis demonstrated similar implant survival rates between healthy and systemically compromised patients over a follow-up of 11 years (132 months, 93.84% and 94.92%, respectively). The curves showed substantial overlap, and no difference was observed (log-rank, p&#x202f;=&#x202f;0.1566). The loss of implants was not associated with the presence of systemic condition or local factors (p&#x202f;>&#x202f;0.05). Binary logistic regression analysis identified predictors of implant loss, with the model explaining 5.24% of the variance (R2&#x202f;=&#x202f;0.0524). A higher frequency of implant loss was observed in patients over 50 years of age, regardless of systemic status. According to the methodology of this study, no association was observed between systemic conditions and dental implant loss.

AI is increasingly embedded in health care systems; yet, validated instruments for assessing AI literacy among health care workers remain limited. Existing measures are often designed for students or general populations and may not adequately reflect competencies required in health care practice. This study aimed to develop and validate the Scale for AI Literacy in Health Care Workers (SAIL-HCW), a new instrument designed to assess AI literacy across domains relevant to health care practice. A 3-phase instrument development study was conducted. In Phase 1, conceptual domains were identified through a literature review, and an initial item pool was generated. In Phase 2, content validity was assessed by 4 subject-matter experts, and face validity was evaluated with 26 health care workers. Feedback from both groups informed item refinement. In Phase 3, psychometric testing was conducted using survey data from health care workers in a single health care organization. A total of 425 participants completed the survey. The dataset was randomly split into 2 subsamples for exploratory factor analysis (n=212) and confirmatory factor analysis (n=213). Model fit was evaluated using unidimensional, correlated-factor, higher-order, and bifactor models. Reliability was assessed using Cronbach alpha and McDonald omega. Item performance was examined using corrected item-total correlations (CITC), item discrimination analysis, and inter-item correlations. Construct validity was assessed using prior AI training, frequency of AI use, and self-rated AI literacy. Phase 2 feedback from experts and health care workers supported the proposed domain structure and informed item refinement, including revision of wording and removal of redundant items. The final SAIL-HCW consists of 14 items across 7 domains, including AI concept, data fluency, AI evaluation, AI in practice, ethics and regulation, AI in system, and continuous learning. In Phase 3, the bifactor model showed the best fit compared with alternative models (comparative fit index and Tucker-Lewis index>0.93; root-mean-square error of approximation<0.06; standardized root-mean-square residual<0.05), indicating a general AI literacy factor alongside domain-specific factors. Internal consistency for the total scale was high (Cronbach &#x3b1;=0.937; &#x3c9;=0.938). Domain-level reliability ranged from 0.635 to 0.797. All items significantly discriminated between high- and low-scoring groups (P<.001), with CITC values ranging from 0.570 to 0.785. Construct validity was supported, with higher SAIL-HCW scores observed among participants with prior AI training, higher frequency of AI use, and higher self-rated AI literacy (all P<.001). The SAIL-HCW provides initial evidence of validity and reliability for assessing AI literacy among health care workers. Findings suggest that AI literacy may be represented as a general construct with additional domain-level components. The scale may be useful for research and educational evaluations, although further validation in other settings is required.

Intensive care units (ICUs) rely on continuous physiological monitoring and frequent alarms to detect patient deterioration. Although alarm fatigue has been widely discussed as a patient safety and workflow issue, less is known about how monitoring systems shape nurses' attention, visibility, perceived accountability, emotional strain, and recovery after distressing events. Understanding these experiences is important for designing safer monitoring displays, alarm behavior, communication routines, and future AI-supported systems. This study aimed to explore how ICU nurses experience continuous monitoring and alarms as a digital work environment, with particular attention to digital gaze, vicarious trauma-related emotional strain, perceived accountability, and design-relevant system needs. We conducted a qualitative interview study with 15 ICU nurses from a tertiary hospital in Hangzhou, China. Semistructured interviews probed 6 topics: everyday monitoring routines and alarm exposure; responses to alarms, patient deterioration, and death; perceived pressure related to visible physiological data; after-shift experiences following distressing events; coping and recovery strategies; and suggestions for alarm governance and monitoring system design. Data were analyzed using reflexive thematic analysis. Four themes were generated. First, continuous monitoring created a form of digital gaze in which nurses maintained constant watch, experienced alarm-driven interruptions, and felt that visible physiological data made bedside responses open to scrutiny. Second, patient deterioration and death were experienced partly through monitoring technologies, including weakening waveforms, escalating alarms, numerical decline, and eventual silence. Third, monitoring-related stress extended beyond the ICU through lingering alarm sounds, monitor images, personal resonance, and work-related messages after shifts. Fourth, participants described recovery strategies but also emphasized system-level needs, including clearer alarm prioritization, fewer nonactionable alerts, gentler auditory design, more useful trend displays, postresuscitation buffering, and better digital communication boundaries. Continuous monitoring and frequent alarms shaped ICU nurses' work beyond workflow disruption and patient safety. Alarm-intensive care should be understood as a digital health and sociotechnical design issue that affects attention, perceived accountability, emotional strain, and recovery. Future monitoring systems should be co-designed and evaluated not only for alarm reduction and technical accuracy but also for how displays, alarm behavior, work-related communication, and AI-supported tools affect clinicians' work, recovery, and perceived surveillance.

Gastroesophageal reflux disease (GERD) is a common chronic condition, with variable prevalence worldwide and with a substantial impact on patients' quality of life (QoL). Data on the Albanian population are scarce and outdated. The aim of this study was to estimate the prevalence of probable GERD in a convenience sample of Albanian adults, explore its associations with demographic, socioeconomic, anthropometric and lifestyle factors and assess the impact of the condition on health-related quality of life. A cross-sectional study was conducted between March and May 2025 in Albania among 505 participants, recruited through convenience sampling. The sample was predominantly young and concentrated in Korce region. Data were collected through a semi-structured, self-administered online, questionnaire. GERD symptoms were assessed using the GerdQ questionnaire and a score of &#x2265;8 was used to define probable GERD. Score for GERD-related QoL was obtained through the 16-item GERD-QoL questionnaire. Demographic, anthropometric, dietary and lifestyle variables were analyzed as potential factors associated probable GERD. Logistic regression models were used to obtain odds ratio (ORs) with 95% confidence intervals (CIs). The prevalence of probable GERD in the study sample was 31.1%. Probable GERD was more frequent among men (45.7%) and participants aged 25-34 years. In multivariable analysis male gender (aOR=2.08, 95%CI: 1.27-3.39), 25-34 year-age group (aOR=1.84, 95%CI: 1.06-3.21), urban residence (aOR=2.16, 95%CI: 1.30-3.59) and frequent alcohol consumption (aOR=2.83, 95%CI: 1.61-4.96) were independently associated with probable GERD. Body mass index (BMI) and smoking status were no longer significant after adjustment. In unadjusted analysis, consumption of &#x2265;2 coffees /day was associated with higher odds of probable GERD compared with no or rare consumption (OR=5.05, 95%CI: 2.88-8.85). The inverse associations observed for citrus juices and tomato-based products may reflect symptom-based dietary avoidance rather than a true protective effect. Probable GERD was independently associated with a 15.90-point lower total QoL score (95%CI: -20.74 to -11.05, p<0.001). Among participants with probable GERD, women reported lower QoL scores than men across all domains while male gender was independently associated with a 12.36-point higher total QoL score. In this predominantly young, urban and geographically concentrated sample, probable GERD prevalence was higher than previously data reported in Albania. Male gender, age 25-34 years, urban residence and frequent alcohol consumption were independently associated with probable GERD. Probable GERD was also independently associated with lower health-related QoL. Among GERD-positive participants, women reported lower QoL scores than men across all domains.

Gait asymmetries and compensatory strategies are common among individuals with unilateral transfemoral (TF) and transtibial (TT) amputation. Although these characteristics have been widely described in the prosthetic gait literature, comparative evidence directly examining differences between the 2 amputation levels, particularly using large-scale clinical data derived from long-term databases, remains limited. This study aimed to clarify gait asymmetry characteristics in individuals with unilateral lower limb amputation by comparing spatiotemporal gait parameters between TF amputees and TT amputees. A retrospective analysis was conducted on clinical gait data collected between 2013 and 2024 from 66 individuals at a Japanese rehabilitation center using a pressure-sensitive walkway system. Spatiotemporal parameters and symmetry indices (symmetry indices; a quantitative measure expressing interlimb differences as a normalized percentage difference between limbs) were calculated for each limb. Intergroup comparisons were conducted using the Mann-Whitney U test, and within-group comparisons of amputated vs. nonamputated limbs were performed using the Wilcoxon signed-rank test. TT amputees exhibited significantly greater walking speed, cadence, and stride length than TF amputees. Temporal asymmetries were more pronounced in TF amputees, whereas spatial and support-related asymmetries were more evident in TT amputees. Stride length asymmetry was also identified in the TF group. Symmetry indices for stance and swing phase durations were significantly greater in the TF group, whereas those for step width and double support time were greater in the TT group. Gait asymmetry patterns in lower limb amputees differ according to amputation level. TF amputees showed predominantly temporal asymmetry, whereas TT amputees demonstrated more marked spatial and support-related asymmetries. These findings support the clinical utility of symmetry indices in prosthetic gait assessment.

The dengue virus (DENV) is an important arboviral pathogen that causes dengue fever in humans. It has become a hyperendemic disease in India due to the circulation of multiple serotypes. Molecular surveillance and characterization of DENV are essential to monitor the serotypes and predict outbreaks. The present study was designed to investigate the transmission of DENV serotypes and identification of circulating strains and the molecular epidemiology surveillance in central Karnataka. Samples from DENV-suspected patients were tested for the dengue NS1 antigen. The positive samples were subjected for serotyping and a subset was selected for gene amplification and sequencing to determine the genotypes. The collective clinical data record of patients was opted for principal component analysis (PCA) and investigative clustering investigations. Among 4,409 samples, seropositive cases and molecular detection rate were 26.2% (1,156) and 74.6% (1,123), respectively. Serotyping results showed that DENV-2 (79.6%) was the most predominant serotype, followed by DENV-3 (10.6%) and DENV-1 (4.4%). Co-infection with multiple dengue serotypes was identified in 5.2% cases. According to phylogeny, DENV-1 serotype identified in this study belonged to genotype I, DENV-2 to genotype II (cosmopolitan), and DENV-3 to genotype III. The K-means of PCA suggests the patient's dataset were grouped in the three clusters with a few anomalies. This study reports the circulation of three dengue serotypes and concurrent infections in Central Karnataka. This outcome provides baseline data for continuous molecular surveillance to predict future outbreaks and improve control measures.

This study analyzed temporal trends, the impact of the COVID-19 pandemic, and projections up to 2030 for oral cancer incidence and mortality rates in Brazil, stratified by sex and macro-region. This population-based observational study used secondary data from the Department of Informatics of the Brazilian Unified Health System (DATASUS) and the Hospital Information System (SIH/SUS), covering the period from 2013 to 2022. Malignant neoplasms of the oral cavity and major salivary glands (C00-C08, ICD-10) were included. Age-standardized incidence (ASIR) and mortality (ASMR) rates were analyzed using Prais-Winsten linear regression and classified according to the Annual Percentage Change (APC), with significance set at p&#x202f;<&#x202f;0.05. Projections to 2030 were estimated using double exponential smoothing, and the pandemic's impact was assessed through the ratio of observed-to-predicted rates (RR) for 2020-2022. The study recorded 40,078 deaths and 92,411 cases, 70.8% of which occurred in men, with the highest concentration in individuals aged 55-64 years. The trends revealed a significant increase in incidence across all macro-regions, particularly in the North and South regions, whereas mortality rates remained stable. During the pandemic, an apparent reduction in cases (RR <1) was observed, suggesting underreporting and diagnostic delays. The projections indicate a continuous increase in incidence and a slight rise in mortality through 2030. Limitations include reliance on secondary data that are subject to underreporting and delays, especially during the pandemic. These findings highlight the worsening of regional inequalities and underscore the urgency to strengthen prevention, screening, and early diagnosis policies, particularly in socially vulnerable contexts.

Antimicrobial resistance(AMR) in Klebsiella pneumoniae is an urgent clinical challenge. Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry(MALDI-TOF-MS) is routinely used for species identification, and reusing these spectra for same-day AMR prediction could accelerate targeted therapy. We developed and validated Light Gradient Boosting Machine(LightGBM) models to predict K. pneumoniae resistance directly from routine Bruker MALDI-TOF MS spectra of single bacterial colonies obtained on routine Bruker instruments, using a kernel density-encoded feature representation. Raw spectra were processed to extract peak-level attributes, including m/z, signal-to-noise ratio, peak area and intensity. The m/z axis was intervalized using a kernel density-guided strategy to preserve local spectral density and ordering, and peak attributes within each interval were aggregated into a structured high-dimensional matrix. A total of 424 isolates were included, and balanced binary datasets were constructed for 12 antibiotics, with an average of 98 &#xb1; 8 susceptible and 98 &#xb1; 8 resistant isolates per antibiotic; intermediate isolates were not included. The dataset included both environmental and human-derived isolates, and antimicrobial susceptibility labels were determined by broth microdilution for amikacin, aztreonam, ciprofloxacin, meropenem, piperacillin-tazobactam, cefepime, cefmetazole, cefoperazone-sulbactam, cefotaxime, ceftazidime, imipenem, and ceftazidime-avibactam, with stronger agreement for cefotaxime and comparatively lower agreement for imipenem. In internal hold-out validation, model accuracy ranged from 0.81 to 0.92 across 12 evaluable antibiotic-specific models, with AUROC values ranging from 0.88 to 0.96. These findings suggest that kernel density-encoded MALDI-TOF MS spectra combined with LightGBM may provide a proof-of-concept framework for AMR prediction, although independent external validation is required before clinical application can be considered.

KRAS mutations are common in colorectal cancer, but the impact of KRAS mutation subtypes on treatment response remains poorly understood. This research aimed to investigate whether different KRAS mutations influence pathological complete response (pCR) rates after neoadjuvant chemoradiotherapy in locally advanced rectal cancer (LARC). A systematic review and meta-analysis of studies describing genetic determinants of response to neoadjuvant chemoradiotherapy in LARC was conducted, searching for manuscripts published up to March 2026. The primary outcome of interest was the odds ratio for KRAS mutations and pCR. A random-effects model estimated the pooled effect size of KRAS mutations within and outside exon 2 on pCR. Genomic data sets were analysed to investigate the molecular characteristics of KRAS exon 2 and non-exon 2 mutant rectal cancers and their impact on overall and disease-free survival. Finally, a transcriptomic data set was analysed to elucidate the underlying response mechanisms. Out of 11 537 manuscripts identified, 15 studies (3354 patients) were included in the meta-analysis. The odds ratio for any KRAS mutation and pCR was 0.48 (95% confidence interval 0.32 to 0.70), indicating reduced odds of pCR in KRAS-mutant LARC. Subgroup analysis revealed that KRAS mutations in exon 2 accounted for this effect, whereas variants outside exon 2 had no influence (odds ratio 0.96, 95% confidence interval 0.11 to 8.49). Analysis confirmed poorer disease-free survival in patients with exon 2 alterations (P = 0.019) as well as poorer overall survival (P = 0.047). Transcriptomic analysis revealed that non-exon 2 KRAS-mutant tumours were enriched for inflammatory signalling pathways, suggesting that these tumours represent a subgroup with high immune infiltration. The presence of KRAS mutations adversely affects pCR odds after neoadjuvant chemoradiotherapy in LARC, but this effect is specific to exon 2 mutations.

Hemoglobin A1c (HbA1c) remains a cornerstone of glycemic assessment in diabetes mellitus care, yet discordance between HbA1c and measured glucose values is common in clinical practice. Failure to recognize this discordance can lead to inappropriate treatment escalation, increased hypoglycemia risk, and patient distress. This article reviews the biological and clinical factors that contribute to HbA1c-glucose discordance and translates these findings into practical strategies for routine care. Common causes include iron deficiency, chronic kidney disease, altered red blood cell turnover, hemoglobin variants, and rapid changes in glycemia. A stepwise, practice-oriented framework is presented to guide clinicians in evaluating discordant glycemic data using targeted laboratory testing and continuous glucose monitoring metrics. Emphasis is placed on avoiding reflexive medication intensification and using glucose monitoring data to individualize treatment decisions. The role of interdisciplinary care and patient-centered communication is also highlighted.

Evidence regarding the association of the diagnosis to treatment interval (DTI) and survival can inform clinical care and health policy. Data in this regard are currently lacking for cervical cancer. To examine the relationship between the DTI and overall survival (OS) in a contemporary cohort of cervical cancer patients receiving curative surgery. We conducted a retrospective cohort study using population-based data of incident cases of cervical cancer diagnosed January 2008-September 2023 followed to December 1st, 2023 in Ontario, Canada. Eligible patients were >&#x202f;18 years of age with stage I-III disease who received curative surgery. Multivariable Cox Proportional Hazards regression analyses were performed to evaluate the association between the DTI and OS adjusting for important confounders. The DTI was modeled categorically and using restricted cubic splines to visualize non-linear relationships. 1501 incident cases of cervical cancer receiving curative surgery were included. The majority of patients were diagnosed with stage I disease (n&#x202f;=&#x202f;1185, 79%). The median DTI was 80 (60-107) days. After multivariable adjustment, the hazard ratio (HR) estimates were elevated for the shortest and longest DTIs: >2-6 weeks HR: 2.33 (95%CI 1.14-4.77); >22-26 weeks HR: 1.76 (95%CI 0.59-5.27); in comparison to the middle referent interval >10-14 weeks. The restricted cubic splines exhibited a U-shaped pattern of risk, with higher effect estimates among the lowest and highest DTI values. In this population-based study we did not find that prolonged DTIs to be significantly associated with poorer survival. Cautious interpretation of the results is needed given the potential impact of the waiting time paradox.

Postamputation pain (PAP) is common and can disrupt the rehabilitation process. The current study's purpose was to examine the associations among early PAP, general and perceived health, during adaptation to prosthetic use through analysis of existing clinical records. Retrospective chart review. In this retrospective chart review, 536 eligible records of patients who were referred for prosthetic rehabilitation at the Portsmouth Enablement Centre were examined. Data were extracted and analyzed from the medical records of 44 patients, encompassing a primary assessment (baseline) after amputation and a 9-month follow-up. Analyses were performed to examine the predictive properties of baseline levels of EQ5D health scores, perceived health, and visual analog scale (VAS) pain ratings, and age, diabetes status, level of amputation, and sex on EQ5D health scores and perceived health at follow-up. Higher VAS pain intensity ratings at baseline were significantly associated with worse EQ5D health scores and perceived health 9 months later. After accounting for baseline EQ5D health scores and perceived health, VAS pain remained a significant predictor of 9-month EQ5D health scores. Early PAP is a risk factor for poorer health, suggesting a possible target for future research investigating multimodal interventions aimed at reducing pain. These interventions and the associated reductions in pain could potentially help facilitate engagement in rehabilitation exercises and prosthesis use to improve functional, psychological, and pain-related outcomes, thereby improving health. Nevertheless, complete data were available for only 44 of 536 eligible records, highlighting a substantial risk of selection bias.

Sleep disorders and disturbances affect more than one-third of the global population. Although certain drugs have been implicated, the real-world breadth and strength of these signals across therapeutic classes remain poorly characterised. This study aimed to systematically profile drug-induced sleep disorders and disturbances using large-scale pharmacovigilance data and to identify drugs with disproportionate reporting, including those not previously well recognised. We analyzed 21 years of post-marketing surveillance data using four disproportionality algorithms (Reporting Odds Ratio [ROR], Proportional Reporting Ratio [PRR] with &#x3c7;2, Bayesian Confidence Propagation Neural Network [BCPNN], and Multi-item Gamma Poisson Shrinker [MGPS]), leveraging their complementary strengths in sensitivity, bias reduction, stability, and rare-event detection. Positive signals were defined as meeting pre-specified thresholds for all four algorithms simultaneously. Among over 22 million reports, 411,736 involved sleep disorders (58.9% female). Overall, 131 drugs showed disproportionate signals; 24 (18.3%) lacked FDA-labelled warnings. Varenicline accounted for the most reports (n&#x202f;=&#x202f;16,200), whereas montelukast showed the strongest signal (ROR 11.78, 95% CI 11.40-12.18). Median time to onset was 36 days (IQR: 6-260), with an early failure-type profile (Weibull &#x3b2;&#x202f;=&#x202f;0.449, 95% CI 0.447-0.452). Among therapeutic classes, antineoplastic and immunomodulating agents (ATC L01) showed the highest disproportionality (ROR 9.19, 95% CI 8.86-9.53). Multiple drug classes show disproportionate reporting for sleep disorders and disturbances with an early-onset risk profile, supporting monitoring at treatment initiation. Approximately one in five of these drugs lack US labelling warnings, highlighting the need for clinical awareness and mechanistic studies.

Osteoporotic and fragility fractures impose a significant global health burden, especially with the aging population. Despite advancements in imaging, risk assessment, and surgical techniques, underdiagnosis and undertreatment persists. Artificial intelligence (AI), particularly machine learning (ML) and deep learning (DL), offers promise for enhancing fracture risk prediction, imaging-based diagnosis, clinical decision support, and postoperative outcome monitoring. To systematically review AI applications in the evaluation and treatment of osteoporotic and fragility fractures, summarizing performance, limitations, evidence gaps, and future directions for clinical translation. A PRISMA-compliant search was conducted in PubMed, IEEE Xplore, Google Scholar, and Web of Science from inception to October 2025. Inclusion criteria targeted original English-language studies in adults using AI/ML/DL for fracture risk prediction, diagnosis, treatment planning, intraoperative guidance, or postoperative management. Data extraction focused on study design, population, AI methods, performance metrics, and validation. Of 1286 records, 21 studies were included, clustering into three domains: fracture risk prediction (n&#xa0;=&#xa0;10) using clinical, biochemical, and imaging data, often outperforming tools like FRAX; bone mineral density (BMD) estimation and osteoporosis screening from CT, X-ray, or opportunistic imaging (n&#xa0;=&#xa0;6); and prognosis/postoperative outcomes (n&#xa0;=&#xa0;5). AI demonstrates robust performance in BMD estimation, fracture detection, and risk prediction, frequently surpassing traditional methods. However, methodological heterogeneity, bias risks, and limited prospective/multicenter validation hinder translation. Future efforts should prioritize transparent reporting, external validation, regulatory compliance, and user-centered integration.

Chronic spontaneous urticaria (CSU) is a common inflammatory skin disease characterized by severe itching and wheals, affecting approximately 1.4% of the global population. Both second-generation H1-antihistamines and omalizumab have limited efficacy in some patients. Previous studies suggest that combining traditional Chinese medicine with biological agents may improve efficacy and reduce adverse effects in inflammatory skin diseases. This study uses a trials within cohorts (TwiCs) design to evaluate the efficacy and safety of the shenqi formula (SQF) combined with omalizumab for the treatment of CSU. This TwiCs study is built upon an existing urticaria cohort established in November 2019 at Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine. Overall, 92 eligible patients with type 1 autoallergic CSU and qi and blood deficiency syndrome will be randomly allocated in a 1:1 ratio to receive either omalizumab alone or omalizumab combined with the SQF. The treatment period is 24 weeks, followed by 16 weeks of follow-up. The primary outcome is the 7-day Urticaria Activity Score. Data will be managed using Microsoft Excel (version 2016), analyzed with SPSS (version 27.0; IBM Corp), and visualized with GraphPad Prism (version 9.0). A complier average causal effect analysis will be applied to estimate causal effects using generalized linear latent mixed models. As of the manuscript submission (November 2025), the trial has been funded (December 2024) and registered with the International Traditional Medicine Clinical Trial Registry (registered January 28, 2025). Patient enrollment commenced in April 2025 and is projected to conclude by December 2027. Data analysis is expected to be completed by June 2028, with final results anticipated for publication in the fourth quarter of 2028. This study is the first to apply a TwiCs design to compare the efficacy and safety of SQF combined with omalizumab versus omalizumab alone in patients with CSU. The findings are expected to provide high-quality real-world evidence for the integration of traditional Chinese medicine with biological therapy in the management of CSU and to serve as a methodological reference for future TwiCs applications in dermatology research.

The number of opioid-related deaths in Germany has continued to rise in 2024. Take-home naloxone (THN) is an evidence-based intervention to prevent opioid-related overdose deaths. Pilot projects have existed in Germany since 1998; however, the implementation of THN is still scarce. The aim of this study is to explore external overarching barriers and facilitators affecting the implementation of THN in drug services. Twelve qualitative interviews were conducted with professionals who are involved in the implementation of THN in Germany. The data were analysed using qualitative content-analysis. Both data collection and analysis were guided by the Consolidated Framework for Implementation Research (CFIR). The analysis focuses on the "Outer Setting" domain of the CFIR. The prescription and distribution requirement for naloxone and the lack of funding hinder organizations in implementing THN. Successful collaborations with physicians and other local stakeholders act as facilitators. Stigma and legal uncertainties can hinder the initiation of such collaborations. The professional and political pressure to implement THN is low, resulting in many organizations struggling to find local partners for joint implementation. Central coordination of THN dissemination and long-term implementation could support the development of local networks, help reduce stigma, and clarify legal misconceptions. Allowing naloxone to be distributed free of charge and without prescription to people who use opioids (PWUO) appears essential for effective THN implementation. Legal clarity regarding naloxone prescription could encourage more physicians to engage in THN. The results might be relevant for the implementation of THN in other countries as well.

Despite the rapid global expansion of legal bans on child corporal punishment, little is known about whether these policies are associated with adolescents' experiences of peer violence. Drawing on cross-national data from the Programme for International Student Assessment (PISA) 2022, this study included 22,721 students from 31 OECD countries and regions to examine the association between national corporal punishment bans and bullying victimization among adolescents. Multilevel linear modeling was employed to account for the hierarchical structure of the data. The results indicate that more comprehensive and longer standing national bans on corporal punishment are associated with lower levels of bullying victimization among adolescents. Mediation analyses further reveal that peer cooperation partially explains this association, suggesting that social competencies may represent an important pathway linking institutional contexts to adolescents' peer experiences. In addition, moderation analyses indicate that the association between corporal punishment bans and bullying victimization is more pronounced among boys than among girls. These findings highlight the potential spillover effects of child protection legislation beyond the family context and underscore the importance of social competencies and gender sensitive perspectives in understanding adolescents' exposure to peer violence. Overall, the study contributes new cross national evidence on the broader societal implications of corporal punishment bans and provides insights for policies aimed at preventing violence against children and adolescents.