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PubMed2026

Effectiveness of a digi-physical tool and working method for paediatric obesity treatment in Abu Dhabi: a non-inferiority intervention study using an external historical comparator.

BACKGROUND: Effective paediatric obesity treatment requires high intensity, scalable interventions. A digi-physical tool for paediatric obesity treatment has shown positive results in Stockholm, Sweden. This study evaluates whether the same treatment method is effective in a different cultural setting. METHODS: This non-inferiority intervention study, using an external historical comparator, included 60 consecutively recruited children aged 6-15.9 years with obesity who initiated treatment at Sheikh Shakhbout Medical City in Abu Dhabi between June and December 2023. Patients were treated with Evira, a digi-physical tool and working method enabling high intensity individualized care, real-time monitoring, and interactive patient-clinician communication. The primary outcome was BMI z-score change at 26 weeks. Non-inferiority was assessed using a predefined margin of 0.10 BMI z-score, with outcomes compared to a prior published trial in Stockholm (n = 107). RESULTS: A total of 112 children were included in the analysis (Abu Dhabi cohort, n = 35; Stockholm cohort, n = 77). The adjusted mean change in BMI z-score was - 0.20 (95% CI: - 0.28, - 0.12) in the Abu Dhabi cohort and - 0.20 (- 0.26, - 0.14) in the Stockholm cohort (p = 0.88). Non-inferiority was confirmed, (predefined margin 0.10 was not exceeded). A clinically significant BMI z-score reduction (≥ 0.20 units) was achieved by 45.7% of participants in Abu Dhabi and 36.4% in Stockholm (p = 0.35). Non-retention rates at 26 weeks were 41.7% vs. 28.0%, respectively (p = 0.07). CONCLUSIONS: The findings provide promising evidence that treatment outcomes achieved with the digi-physical treatment tool were comparable in the Abu Dhabi and Stockholm cohorts, supporting its feasibility in a second cultural and healthcare setting.

Humans↗

PubMed2026

Comparison of paralog identification methods and their impact on species tree topologies in target capture phylogenomics within the Sindora clade (Detarioideae: Leguminosae).

Target capture is a common method of generating high throughput DNA sequencing data for phylogenetic reconstruction of species relationships, for which single copy genes are usually most informative. However, a pervasive problem with target capture is that putatively single copy genes may in fact be paralogs resulting from gene duplication, which are problematic for phylogenetic inference because their evolutionary history may differ from the divergence history of species. Here, we use as a case study a target enrichment dataset of 88 species of Detarioideae (Leguminosae) with a focus on the Sindora clade to examine approaches for handling paralogs, including the built-in paralog handling functions in HybPiper and CAPTUS, plus subsequent steps using Putative Paralog Detection and the tree-based Yang & Smith orthology inference approach. We compare the paralogs flagged using these methods and verify their performance with BLAST mapping against a reference genome sequence of Sindora glabra, and then subsequently compare the species tree topologies produced across these methods. Our comparisons of paralogs flagged across the Sindora clade show that the Putative Paralog Detection pipeline was the most accurate in identifying paralogs in terms of its similarity to the BLAST mapping, followed by the built-in paralog identification function of CAPTUS. However, the results we recovered for the Detarioideae subfamily suggest that the largest differences in species tree topology resulted from the use of paralog-filtered alignments (such as with the Putative Paralog Detection pipeline and the Yang & Smith orthology inference approaches) rather than just by removing the sequences of identified paralogous genes. This was the true for HybPiper-assembled datasets but was not seen in CAPTUS-assembled datasets. In all comparisons, the topological differences caused by different paralog handling methods tended to be confined to clades where processes such as hybridisation and introgression are prevalent. Our study provides a roadmap to establish the best approach to identify, eliminate or separate paralogs in the absence of a chromosomally contiguous reference genome for a study group, and highlights the importance of careful data inspection and processing in addition to understanding the extent of paralogy and paralog characteristics (e.g. sequence divergence between copies) for their study group.

Phylogeny↗

PubMed2026

Sensor-based measures of knee brace adherence have low agreement with self-report methods: A multi-measure study among knee osteoarthritis patients.

OBJECTIVE: To explore agreement between self-report and objectively measured adherence to brace wearing by patients with knee osteoarthritis. METHOD: A single-arm observational analysis nested within the PROP OA randomised controlled trial (ISRCTN28555470). Of 237 adults with symptomatic knee osteoarthritis randomised to brace treatment, 60 were included in this sub-study investigating three different methods of assessing knee brace wear time over 26 weeks: 1. Self-report questionnaires (SRQ) at 12 weeks and 26 weeks; 2. Short message service (SMS) questions (days worn in past week, typical hours per day when worn) administered from week 1 to week 24; 3. A skin temperature sensor embedded in the brace, sampling every 10 min for 26 weeks. The presence and reason for the sensor were concealed from participants. The estimated proportion of participants meeting "minimum brace use", defined a priori as ≥1 h on ≥2 days in past week, was described for each measurement method, overall and by brace type (unloader, neutral). For temperature sensor measurements, time spent above 24°C and time spent above 25°C were used. Agreement between the measures was summarised by percentage agreement and kappa (ĸ). RESULTS: The estimated proportions of participants meeting "minimum brace use" at 12 weeks were 83% (SRQ), 83% (SMS), 60% and 58% (temperature sensor, 24°C and 25°C thresholds, respectively). At 26 weeks, the corresponding estimates reduced to 72%, 71% (SMS at 24 weeks), 43% and 37%. Sensor data suggested the sharpest decline in brace use occurred within the first 12 weeks. Agreement between self-report measures was higher than between self-report measures and sensor (SRQ vs SMS at 12 weeks: 92% agreement, ĸ=0.67 (95%CI: 0.34, 1.00); SRQ vs Sensor at 12 weeks: 74%, 0.35 (0.10, 0.60); SMS vs Sens at 12 weeks: 76%, 0.36 (0.05, 0.66). Agreement between all measurement methods reduced at 26 weeks. CONCLUSIONS: This novel use of a temperature sensor to monitor brace adherence in knee osteoarthritis indicates that self-report adherence substantially overestimates knee brace wearing time, with implications for clinical trials and practice.

Humans↗

PubMed2026

"Everybody thinks that it won't happen to them": A mixed-methods study of HIV prevention strategies among people experiencing homelessness who use drugs.

BACKGROUND: HIV disproportionately affects people experiencing homelessness, particularly those who use drugs. Although effective prevention strategies exist, uptake remains suboptimal in high-risk populations. Limited research has examined how this population engages with HIV prevention strategies and the contextual factors shaping behaviors. METHODS: We conducted a mixed-methods study of adults (≥18 years) experiencing homelessness with recent drug use, recruited from three Boston sites (Feb 2024-Jan 2025). Participants completed a survey assessing HIV prevention strategy uptake. A subsample completed in-depth interviews on factors influencing behavior. Guided by the Theoretical Domains Framework, we coded qualitative data and identified themes to help contextualize uptake. RESULTS: Among 196 participants, mean age was 48; 61% identified as male and 44% as non-Hispanic White. Forty-two percent reported condomless sex, and among those who had ever injected drugs (n = 123), 24% reported syringe sharing in the prior three months. Only 9% reported current PrEP use, and 12% had ever used HIV self-tests. Qualitative findings highlighted perceived control as a key facilitator, while low perceived HIV risk hindered uptake across strategies. Additional barriers varied by strategy and included partner dynamics and substance use affecting condom use, structural constraints affecting syringe use, and knowledge, stigma, and cost concerns affecting PrEP and self-testing. CONCLUSION: In this cohort of people experiencing homelessness who use drugs, HIV prevention strategy uptake was suboptimal, with particularly low PrEP and HIV self-testing use. Qualitative findings suggest that interventions to promote HIV prevention strategy uptake in this population should leverage perceived control, address perceived risk, and target strategy-specific interpersonal and structural barriers.

Humans↗

PubMed2026

Perspectives of participating neurologists and study nurses - Mixed-methods process evaluation of a web-based program for relapse management in multiple sclerosis (POWER@M2).

BACKGROUND: Relapsing-remitting multiple sclerosis is a chronic inflammatory disease of the central nervous system and the leading cause of disability in young adults. In Germany, 90% of relapses are treated with high-dose intravenous glucocorticoids, despite limited evidence for long-term benefit and international preference for oral administration. Time constraints often hinder informed decision-making. The multicentre Randomized Controlled Trial (RCT) POWER@MS2 (N = 160, 2020-2023), conducted at 18 German MS-centres, aimed to promote self-determined relapse management through a complex intervention (dialogue-based decision aid, nurse-led webinar, online-chat). OBJECTIVE: While RCTs demonstrate effectiveness, process evaluations are essential to understand implementation, mechanisms of impact and contextual factors. This study explored healthcare professionals' experiences and attitudes toward implementing relapse self-management and self-medication in clinical practice. METHODS: A mixed-methods process evaluation followed the UK Medical Research Council- framework. Quantitative data were collected via validated questionnaires at up to three time points and analysed descriptively. Interview guides were developed based on these results. Qualitative data from neurologist and study nurse interviews were thematically analysed. Results were triangulated using a joint display. RESULTS: Data were collected from 55 neurologists and 17 study nurses (quantitative) and from 7 neurologists and 4 nurses (qualitative) (2020-2024). Most neurologists opposed routine steroid use, reserving it for severe relapses. Some voiced concerns about self-management, but informed patients were generally viewed as capable of safe self-medication. Study nurses gave mixed feedback on the intervention, citing overload and improved guidance. CONCLUSION: Clinicians showed openness toward implementing the intervention. Enhancing accessibility and addressing specific concerns may support broader adoption.

Humans↗

PubMed2026

Measuring economic efficiency in adult intensive care units: A systematic review of methods, metrics, and evidence.

OBJECTIVES: Intensive care units (ICUs) consume substantial hospital resources, yet "efficiency" is inconsistently defined and measured. This study systematically reviewed how economic efficiency has been conceptualised and quantified in adult ICUs and appraised the quality of evidence. METHODS: Following PRISMA 2020 and a PROSPERO-registered protocol (CRD420251107866), we searched MEDLINE, Embase, CINAHL, Cochrane Library and Web of Science (2000-August 2025), plus global grey sources. Eligible studies explicitly defined efficiency and reported an efficiency metric/model linking ICU inputs (e.g., staff, beds/capacity, time, consumables, or costs) to outputs/outcomes (e.g., throughput/discharges, length of stay/resource use, risk-adjusted mortality). Dual independent screening and extraction were performed. Study quality was appraised using MMAT, and findings were synthesised narratively (SWiM), given heterogeneity. RESULTS: 39 studies (2001-2025) from 17 countries were included, all from high-income or upper-middle-income settings. Four methodological families were identified: (1) frontier modelling (predominantly DEA; occasional SFA/RFDH), (2) benchmarking indicators (risk-adjusted mortality and LOS/resource-use ratios; "efficiency matrix" quadrant classification), (3) cost-outcome evaluations, and (4) operational/process metrics. Across families, variation in decision-making units, input/output selection, and risk adjustment limited comparability; long-term and patient-reported outcomes were absent, and equity considerations were uncommon. CONCLUSIONS: ICU efficiency research is feasible but fragmented and often methodologically limited. Standardised definitions, validated risk adjustment, uncertainty quantification, and inclusion of patient-centred and equity-relevant outcomes are needed before efficiency metrics can reliably inform value-based decision making.

Intensive Care Units↗

PubMed2026

A systematic review of human avoidance learning: Cognition, computation, and methods.

Avoidance behaviour is fundamental for survival but can become maladaptive in clinical conditions. A large body of literature has accumulated on the dynamics of human avoidance learning. However, current theories and overviews do not provide an exhaustive account of this evidence. In this systematic review, we identify N = 116 studies on human avoidance learning. We analyse these studies with the goal of distilling robust empirical phenomena as a basis for theory-building, and examine their diagnostic value in differentiating between competing theories. We find that the evidence is difficult to reconcile with foundational two-factor and classical safety-signal accounts, and most strongly supports expectancy- and inference-based views, in which avoidance responses are selected with respect to represented consequences. At the same time, no current framework provides a complete account of the evidence: several findings point to an additional role for operant valuation, Pavlovian influences, and contextual or latent-state control over the expression of avoidance. Methodologically, we observe that the problem setting in the most common experimental paradigms is radically simpler than real-world avoidance and therefore unlikely to expose the limits of inferential or reflective mechanisms. Consequently, we argue that paradigms with greater computational demands and more realistic action affordances are required to identify the mechanisms underlying avoidance learning. Collectively, these insights provide a foundation for theoretical refinement, computational modelling, and methodological innovation, with implications for advancing interventions targeting maladaptive avoidance.

Humans↗

PubMed2026

Routine methods misidentify Serratia spp.: Limitations of MALDI-TOF MS revealed by whole-genome sequencing.

Accurate species-level identification within the genus Serratia remains challenging due to extensive phenotypic overlap and high genomic relatedness among closely related and recently described taxa. This study presents an evaluation of routine and genome-based identification approaches applied to clinical Serratia isolates, integrating phenotypic assays, MALDI-TOF MS (Bruker Daltonics), 16S rRNA gene sequencing, and Whole-Genome Sequencing (WGS). A total of 103 isolates collected from a teaching hospital were analyzed. WGS was performed on a subset of isolates. Conventional biochemical methods classified all isolates as Serratia marcescens, whereas MALDI-TOF MS identified 60.1% as S. marcescens, 11.6% as S. ureilytica, and 28.1% just at the genus level. Peak analysis from MALDI-TOF MS revealed specific peaks associated with S. marcescens and S. ureilytica, but limited discriminatory power. WGS of six isolates initially identified as S. ureilytica by MALDI-TOF MS revealed reclassification as Serratia sarumanii (n = 5) and Serratia montpellierensis (n = 1), supported by Average Nucleotide Identity (ANI), Average Amino Acid Identity (AAI), and Digital DNA-DNA Hybridization (dDDH) thresholds. In contrast, 16S rRNA analysis showed limited species-level resolution. Phylogenomic and SNP-based analyses confirmed these classifications with strong support. Overall, this study underscores the critical role of high-resolution genomic approaches for precise species identification and highlights the need for continuous expansion and curation of MALDI-TOF MS reference databases to support reliable clinical diagnostics and epidemiological surveillance of emerging Serratia species.

Spectrometry, Mass, Matrix-Assisted Laser Desorpti↗

PubMed2026

Systematic review of microorganism disinfection performance by chemical and ultraviolet light water treatment methods.

Safe drinking water is critical for public health, yet microbial contamination remains a significant global challenge. We conducted a systematic review to update World Health Organization guidance on water disinfection technologies by synthesizing peer-reviewed literature from 1997 to 2021 on the performance of free chlorine, chlorine dioxide, ozone, and ultraviolet (UV) light against bacteria, viruses, and protozoa. Following PRISMA guidelines, we analyzed log10 reduction values (LRVs) and contact times (Ct) or fluence (for UV) from laboratory and field studies. We included studies from multiple databases and expert-recommended studies. Results show mean Cts for 2 LRV of non-opportunistic bacteria as 6.0 (free chlorine), 0.4 (chlorine dioxide), and 1.2 (ozone) mg/L*min, and a mean UV fluence of 8.2 mJ/cm² (all bacteria). Viruses required lower Cts, except for UV-resistant adenoviruses, while protozoa required higher Cts or fluences. Opportunistic bacteria required significantly higher Cts than non-opportunistic bacteria for free chlorine and chlorine dioxide. Temperature and pH effects were inconsistent, highlighting data variability and gaps in field studies. These findings support global guidance on water treatment and may be used alongside other context-specific data to understand the roles these technologies play in reducing waterborne exposures. We recommend standardized reporting from performance studies to enable straightforward synthesis of evidence.

Disinfection↗

PubMed2025

Outcomes of Experiencing Interpersonal Violence in Autism: A Mixed Methods Systematic Review and Meta-Analysis.

In this review and meta-analysis, we aimed to examine outcomes of interpersonal violence among autistic people. Intersectionality and minority theories suggest that negative outcomes are heightened among people with multiple marginalized identities. Thus, we also aimed to investigate gender-related outcomes of interpersonal violence among autistic people. We conducted a systematic database search with inclusion criteria including mixed methods, peer-reviewed research examining any harmful interpersonal act (e.g., physical, sexual, and psychological) experienced by autistic people. We undertook a random-effects meta-analysis with pooled data from 9 studies, comprising 3,647 autistic participants aged 1 to 80 years. Violence was associated with worsened mental health, with the strongest association for internalizing symptoms (d = 0.66, p < .001; 95% CI [0.51, 0.80]) and suicidal thoughts and behavior (d = 0.63, p < .001; [0.44, 0.82]). Narrative synthesis of 57 studies comprising 37,418 participants (13,127 autistic, 24,291 non-autistic) found violence was associated with numerous adverse health, development, and functional outcomes, including worsened mental health and behavioral difficulties compared to non-autistic controls from childhood. Females and gender minorities reported greater intra- and interpersonal health and development difficulties related to violence, emerging in early childhood and enduring into adulthood. Findings provide strong evidence of lifelong negative outcomes associated with interpersonal violence experienced by autistic people, providing evidence for the relevance of minority stress and intersectionality theories in understanding risk. Indeed, our results raise concerns that autistic people, and particularly non-male (female, gender diverse) individuals, have higher susceptibility for abuse from a young age, while being conditioned to respond with social desirability, superficial adaptivity, and dissociation.

Humans↗

PubMed2025

Defining Gaslighting in Gender-Based Violence: A Mixed-Methods Systematic Review.

In both public and academic discourse, gaslighting has gained increased attention, especially regarding psychological abuse, power imbalance, and gender-based violence (GBV). However, the term gaslighting is often inconsistently defined and conflated with broader forms of manipulation. It is also largely examined in the context of intimate partner violence (IPV), which ignores its occurrence in other forms of GBV. The present study presents a systematic review that synthesizes interdisciplinary academic literature to create a comprehensive framework of gaslighting. This framework includes the specific tactics that are used by perpetrators of gaslighting, the social-psychological outcomes experienced by survivors, and the role of systemic inequalities and social power dynamics. A search across multiple databases identified 96 records that discussed gaslighting in relation to GBV. Thematic analysis revealed a two-part framework for understanding gaslighting: (a) gaslighting tactics, which were categorized into cognitive and perceptual manipulation, emotional and psychological abuse, power dynamics and control, and additional forms of manipulation and (b) survivor outcomes, including disruptions to perception and memory, emotional distress, social isolation, and resistance strategies. The findings show that gaslighting is more than just an interpersonal act; it is sustained within social structures, where perpetrators use identity factors and forms of marginalization to exploit survivors. Overall, this review presents a comprehensive definition of gaslighting that illustrates its epistemic nature and its intersection with systemic oppression. It is suggested that future research studies gaslighting in GBV contexts beyond IPV, while practice and policy efforts should seek to enhance recognition and support for survivors.

Humans↗

PubMed2026

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

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

Humans↗

PubMed2026

Unravelling bioanalytical innovations, degradation processes, and impurity landscapes of VEGFR inhibitors.

From pre-formulation studies to clinical trials, VEGFR-targeted small-molecule tyrosine kinase inhibitors (TKIs) require rigorous analytical standards. Bioanalysis, stability-indicating studies, and impurity profiling are used to examine chromatographic advances for VEGFR-targeted TKIs like sunitinib, pazopanib, axitinib, sorafenib, cabozantinib, vandetanib, apatinib, lenvatinib, nintedanib, and regorafenib. An LC-MS/MS and UPLC-MS/MS routinely show sub ng/mL performance, as shown by LLOQs (0.2 ng/mL) for sunitinib and axitinib, 1 ng/mL for pazopanib, 5-7 ng/mL for sorafenib, 0.5-1.5 ng/mL for regorafenib metabolic products, and 0.1-0.5 ng/mL for lenvatinib. These approaches are used for pharmacokinetics and therapeutic drug monitoring due to their good correlation coefficient of 0.1-10,000 ng/mL, accuracy of 95%-108%, and precision of 15% RSD. UPLC-QTOF-MS/MS distinguishes degradants and metabolites during forced degradation studies, enabling structural elucidation following ICH M7 risk evaluation protocol. HPTLC/MLC offers fast, sensitive screenings, while RP-HPLC/DAD or HPLC-UV offer reliable, cost-effective routine quality-control solutions with LOD/LOQ in the μg/mL range and linearity of 10-240 μg/mL. This review lists the structures and CAS numbers of ten VEGFR-2 TKI degradants and metabolites, as well as pharmacopeial impurities in SMILES forms. It will be useful for future method development and regulatory applications. To ensure VEGFR-targeted TKI quality, safety, and therapeutic efficacy, LC-MS/MS for trace quantification and HRMS for structure elucidation provide a robust, future-oriented framework. To improve VEGFR-targeted TKI quality, safety, and regulatory compliance, analytical development should focus on HRMS-based impurity characterization, AI-assisted degradation prediction, green chromatography, and harmonized bioanalytical validation.

Humans↗

PubMed2026

Men's experiences of multiple long-term conditions and/or disability in the UK Game of Stones weight management trial: a mixed-methods evaluation.

OBJECTIVES: To explore experiences, health outcomes and retention of men with multiple long-term conditions (MLTCs) and/or disability within the Game of Stones weight management randomised controlled trial (RCT). DESIGN: Mixed-methods process evaluation within an RCT where secondary outcomes included the Weight Self-Stigma Questionnaire, EuroQol 5-Dimension 5-Level (EQ-5D-5L), EQ-5D-5L anxiety and depression subscale, Patient Health Questionnaire-4 and retention. Semistructured interviews were conducted at 12 months and analysed using the framework method. SETTING: Conducted across three UK trial centres: Belfast, Bristol and Glasgow. PARTICIPANTS: 585 men with obesity (mean (SD) age, 50.7 (13.3) years) were randomised to one of three groups: behavioural text messages with financial incentives, texts alone or waiting-list control. Interviews were conducted with 54 participants from the two intervention groups. RESULTS: 235 (40%) participants lived with MLTCs, 181 (31%) had a single condition, 167 (29%) had no conditions and 165 (29%) had a disability. Of those with MLTCs, 99 were disabled and 93 were living in deprived areas. Participants with MLTCs and/or disability were older, fewer had a degree-level qualification and fewer were in full-time work. Retention at 12 months was higher for men with disability (76%) or no long-term conditions (75%) and lower for men with diabetes (65%). Self-reported weight stigma, well-being and quality-of-life scores improved or stayed the same for men living with MLTCs in the intervention groups; however, results for anxiety and depression screening scores were inconsistent. Participant experiences indicated complex dynamic health, social and life situations which could provide motivation to lose weight for some but not others. Hospitalisation and poor mobility, with inability to exercise, were demotivating for making changes to reach weight loss targets. CONCLUSIONS: Men living with MLTCs and/or disability varied from very successful weight loss and improved health to not prioritising or feeling helped by the programme or disengagement due to immobility or diabetes. TRIAL REGISTRATION NUMBER: isrctn.org Identifier: ISRCTN91974895.

Humans↗

PubMed2026

Evaluating the Effectiveness of an Intimate Partner Violence Training Intervention on Healthcare Providers' Preparedness, Knowledge, and Experiences: A Mixed-Methods Study From Nepal.

Intimate partner violence (IPV) places a considerable burden on health systems globally due to its profound effects on women's health, and women who experience violence often seek care from healthcare providers (HCPs). However, HCPs often lack the preparedness and confidence to respond effectively, resulting in missed opportunities for support and care. This study, conducted in Nepal, evaluated the impact of structured training intervention on HCPs' perceived preparedness, knowledge, and attitudes toward managing IPV and its mental health consequences, including self-harm and suicidal tendencies. The study was nested within a larger cluster randomized trial. A convergent mixed-methods design with a comparison group was conducted among 46 female HCPs in all public hospitals (except one) and 17 primary healthcare centers in Madhesh Province, Nepal. The intervention group (n = 24) received a 10-day intensive IPV and mental health training, while the control group (n = 22) completed 3-day training. Quantitative data were collected using a validated self-administered Physician's Readiness to Manage IPV questionnaire and IPV consequences scale. Paired and independent t-tests were applied to assess changes. Insights from key informant interviews were thematically analyzed to explore participant experiences and perceived impacts. At baseline, over 80% of participants had not received IPV management training. Post-intervention, significant improvements were observed in HCPs perceived preparedness (median change 2.1; 95% confidence interval (CI): 1.1- 2.9), knowledge (median change 2.7; 95% CI: 2.0-3.1), and awareness of IPV consequences (mean difference 1.2; 95% CI: 0.5-2.0), with greater gains in the intervention group. Qualitative findings revealed enhanced confidence in identifying IPV, addressing psychological impacts, and supporting survivors through safety planning and referral. The training significantly improved HCPs' knowledge, preparedness, and confidence to manage IPV and related mental health issues, underscoring the need to scale similar programs to frontline providers, particularly in rural and underserved settings, to strengthen health system's response to IPV.

Humans↗

PubMed2026

Machine learning vs. traditional methods for predicting postoperative cardiac complications after non-cardiac surgery: a systematic review and Bayesian network meta-analysis.

INTRODUCTION: Accurate prediction of peri-operative cardiac complications is critical to optimise pre-operative decision-making. Traditional risk prediction scores, such as the Revised Cardiac Risk Index, show only modest discrimination. Machine learning can model complex, non-linear relationships but their predictive performance compared with traditional scores remains unclear. METHODS: We performed a systematic review and Bayesian network meta-analysis. The primary outcome was postoperative adverse cardiac events following non-cardiac surgery. Prediction models were assessed relative to the Revised Cardiac Risk Index. As many studies evaluated multiple versions of each model type, the highest performing ('best version') and lowest performing ('worst version') results were analysed. Models were ranked using the surface under the cumulative ranking curve (SUCRA). RESULTS: Thirteen studies evaluating 54 models and 927,113 patients were included. Machine learning approaches generally outperformed traditional risk scores. Automated machine learning ranked highest (SUCRA 96.6) showed the greatest improvement in the best version analysis (mean difference (MD) 0.28 (95%CrI 0.16-0.40)) and remained superior in the sensitivity analysis (MD 0.30 (95%CrI 0.14-0.45)). Gradient boosting models showed superior performance over the Revised Cardiac Risk Index across analysis (best version: MD 0.20 (95%CrI 0.14-0.26), worst version: MD 0.18 (95%CrI 0.12-0.25), SUCRA 82.4). The Gupta Perioperative Risk for Myocardial Infarction or Cardiac Arrest score outperformed the Revised Cardiac Risk Index in the best version analysis (MD 0.16 (95%CrI 0.01-0.32)). Between-study heterogeneity was low. None of the included studies externally validated their machine learning models and only six were judged to be at low risk of bias. DISCUSSION: Most machine learning models showed better discrimination than traditional risk scores, with automated machine learning and gradient boosting models ranking highest. However, study quality, calibration reporting and absence of external validation limit immediate clinical adoption. Prospective, multicentre evaluation is required before integration of these models into peri-operative practice.

Humans↗

PubMed2026

Methods for defining equity-stratifying variables: a systematic review of validation studies.

BACKGROUND AND OBJECTIVE: Disease burden is often disproportionally higher among those who are socially disadvantaged by factors defined in the PROGRESS-Plus framework (ie, Place of residence, Race/ethnicity/culture/language, Occupation, Gender/sex, Religion, Education, Socioeconomic status, and Social capital, with "Plus" covering features like age and disability). The accuracy and applicability of case definitions to identify these variables from administrative and clinical health data are unknown. We conducted a systematic review to explore how equity-stratifying variables, as categorized by the PROGRESS-Plus framework, have been defined and validated in epidemiologic studies using administrative health, population-level, or electronic health record (EHR) data. METHODS: Medline, EMBASE, CINAHL, Web of Science, and Google Scholar were searched from the inception of the databases to 2024 for validation studies of equity-stratifying variables in adults using administrative health datasets, health registries, or EHR data. Titles and abstracts, followed by relevant full-text articles, were screened in duplicate by two reviewers for eligibility. The data sources utilized, algorithms employed, and their associated performance measures were extracted and synthesized from included studies. Given substantial heterogeneity in study design, equity-stratifying variable definition, and performance metrics, meta-analysis was not possible. RESULTS: Of the 9099 unique citations screened, 188 full texts were reviewed and 116 were included in this review. Most studies were published between 2019 and 2024 (n = 64, 55%) and were validation studies of race/ethnicity definitions that used race/ethnicity codes or surname list algorithms (n = 66, 57%). No studies examined religion. Regarding the reported performance measure estimates, the race/ethnicity/culture/language equity-stratifying variables category had the largest variability across sensitivity, positive predictive value (PPV), and Cohen's Kappa. Occupation validation studies had the lowest variation in sensitivity and PPV. CONCLUSION: Despite an increasing number of publications reporting on the validation of equity-stratifying variables relevant to the PROGRESS-Plus framework, performance measures varied widely across studies. The significant heterogeneity in equity-stratifying variable definitions and methods used to validate them support the need for further rigorous validation of equity-stratifying variables in administrative and clinical health data. PLAIN LANGUAGE SUMMARY: Disease burden is often higher in people who experience financial hardships, lower level of education, discrimination due to race/ethnicity, and unstable housing. These social factors can be considered health equity factors and are important for understanding health inequalities. Health researchers often use large datasets, such as hospital or electronic health records (EHRs), to study these health equity factors. However, it is not clear how accurately these data sources capture information about people's social circumstances and how these factors are defined. In this study, we reviewed existing research to understand how health equity factors have been defined across health data sources and how accurate they are at measuring aspects of health equity and social disadvantage. Of the more than 9000 studies we identified, we included 116 that met our criteria for this systematic review. Most included studies focused on identifying race and ethnicity, often using codes or surname-based methods. We found that the accuracy of these methods varied widely across studies, meaning results may not always be reliable or comparable. Overall, our findings show that there are inconsistencies in how social factors are defined and measured in health data. This makes it difficult to fully understand and address health inequalities using routinely collected health data. More work is needed to develop and validate better quality and more consistent methods for capturing these important social factors.

Humans↗

PubMed2026

Pictographs: feasibility and acceptability of a novel method of newborn identification to reduce wrong-patient errors in the NICU.

Wrong-patient errors cause serious harm in newborns. These errors involve ordering and administering tests, procedures, medications, and breast milk to an unintended patient. Newborns receiving care in neonatal intensive care units (NICUs) are at particularly high risk. Although more distinct newborn naming conventions as recommended by the Joint Commission significantly reduce wrong-patient orders, name similarities among multiple-birth infants and truncation of differentiating information in some electronic health record (EHR) systems contribute to this persistent increased risk. Accordingly, novel newborn identifiers are urgently needed. We propose Pictographs - images that are appealing, recognizable, and appropriate - to serve as visual identifiers for newborns in NICUs. Pictographs are selected by caregivers, uploaded into the EHR, and displayed at bedside. As part of a multicenter randomized controlled trial assessing effectiveness of Pictographs to prevent wrong-patient order errors, we initially evaluated feasibility and acceptability of Pictographs at two study sites. Pictographs as novel visual identifiers for newborns in the NICU were generally well received by caregivers and clinicians, and the vast majority of caregivers selected a Pictograph for their infant(s), which was posted at the bedside and uploaded into the EHR. Ordering clinicians - the primary target of the intervention to prevent wrong-patient errors - recognized the potential for Pictographs to provide a visual cue when placing orders, particularly for multiple-birth infants. Here, we describe the rationale, implementation, framework, feasibility, usefulness, and acceptability of Pictographs among key stakeholders. If found effective for preventing wrong-patient errors, Pictographs could be adopted as a patient safety solution in hospitals worldwide.

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