SEARCH · Search PubMed

Results for “World health organization”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

572 records · Page 2Linked to original sources

PubMed2026

Clinical insights into catathrenia: A real-world analysis from a tertiary sleep center.

INTRODUCTION: Catathrenia is a rare sleep-related breathing disorder marked by groaning during prolonged expiration, often underrecognized or misdiagnosed as obstructive or central sleep apnoea (OSA or CSA) or parasomnia. Understanding its clinical and polysomnographic features is essential for accurate diagnosis and management. MATERIALS AND METHODS: We performed a retrospective observational study of adult patients diagnosed with catathrenia at Serviço de Medicina do Sono de Coimbra. Diagnosis was established by attended overnight polysomnography (PSG) with synchronised audio-video recording. Demographic data, symptoms, comorbidities, PSG variables, treatment modalities, and outcomes were reviewed. Catathrenia events were defined as deep inhalation followed by prolonged exhalation with monotonous groaning. RESULTS: Ten patients were included. Median age was 46 years (range 27-78), mostly female (70%). Common comorbidities included obesity (n = 4), depression (n = 2), Parkinson's disease (n = 1), and restless legs syndrome (n = 1). Six patients (60%) had concomitant obstructive sleep apnoea (OSA). Seven patients had excessive daytime sleepiness (Epworth Sleepiness Scale > 10). All catathrenia episodes occurred exclusively during REM sleep. Continuous positive airway pressure (CPAP) therapy was the most frequently used treatment and was associated with objective or subjective improvement in most patients. Two patients experienced spontaneous remission. CONCLUSION: Catathrenia remains underdiagnosed and can mimic other sleep disorders. Recognition of its REM-sleep predominance and PSG pattern is essential. Individualised treatment, often involving PAP therapy, may improve symptoms and patient outcomes.

Humans↗

PubMed2026

2024-2025 BNT162b2 KP.2 COVID-19 full season vaccine effectiveness from vaccine registries linked to administrative claims in two states: A cohort study in non-immunocompromised adults.

BACKGROUND: Data on effectiveness of COVID-19 vaccinations during the 2024-2025 respiratory season are limited, particularly among those with underlying medical conditions (UMC). We estimated BNT162b2 KP.2 vaccine effectiveness (VE) against COVID-19-associated hospital admission, emergency department (ED), and urgent care (UC) visits in two U.S. states. METHODS: Retrospective cohort study of non-immunocompromised adults living in Louisiana or California, with ≥1 year prior continuous enrollment in insurance plans contributing to the HealthVerity claims database beginning August 22, 2024. The effectiveness of BNT162b2 KP.2 vaccine (2024-2025 formulation, hereafter referred to as BNT162b2), measured as a time-varying exposure against hospital admission, ED, or UC encounters with International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) code U07.1 was calculated as 1 - adjusted hazard ratio using Cox proportional hazard models adjusted for age group, sex, state, insurance payor, presence or absence of UMCs, and pre-index healthcare utilization. Stratifications included those aged 65 years and older, those aged 18-64 years with UMCs, and those aged 18-64 years without UMCs. RESULTS: The cohort included 6,256,421 individuals (93% California, 7% Louisiana); 330,565 (5%) received the BNT162b2 vaccine. Vaccinated individuals were older and had more comorbidities, wellness visits, and prior influenza vaccination. Overall, 66% of the study population had ≥1 UMC; the most prevalent conditions were obesity (25%), history of immunocompromised conditions (23%), and mental health conditions (19%). COVID-19-related encounter rates for ED, UC or hospitalization were lower among vaccinated compared to unvaccinated persons (25.1 vs 36.3 per 100,000 person-months). Among all adults, VE was 37% against hospitalization, 12% against ED/UC encounters, and 16% against ED/UC/hospitalization encounters. Results were similar across age groups and UMCs. CONCLUSIONS: BNT162b2 provided protection against COVID-19-associated outcomes of ED, UC or hospitalization among non-immunocompromised U.S. adults, including those with UMCs, over the course of the 2024-2025 respiratory virus season, supporting continued vaccine recommendations. REGISTRATION: This study was posted on clinicaltrials.gov prior to analyses (NCT06923137).

Adolescent↗

PubMed2026

Bi-compartmental CSF-serum analysis of NfL and GFAP differentiates central and peripheral pathology in neuroinfectious diseases: A monocentric real-world cohort study.

Neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP), established biomarkers of neuroaxonal injury and astroglial pathology, are frequently only assessed in blood, which limits conclusions regarding their origin. Bi-compartmental analyses of CSF and serum may help differentiate central or peripheral origin of biomarker elevation. Moreover, studies on NfL and GFAP in distinct neuroinfectious disease (NID) phenotypes, particularly those based on real-world cohorts, are limited. This retrospective monocentric study analyzed CSF and serum from patients with (meningo-)encephalitis/myelitis (TI+; n = 48), meningitis (TI-; n = 80), (cranial) nerve palsies/polyradiculitis (PND; n = 61), and 113 non-neuroinflammatory/non-neurodegenerative controls. A bi-compartmental model using scatter plots and simple linear regression was applied to assess the origin of blood biomarker levels and discriminate between central and peripheral pathology. CSF and serum NfL and GFAP z-scores were significantly higher in TI+ compared with TI- (CSF-GFAP p < 0.001/sGFAP p = 0.0083; CSF-NfL p = 0.003/sNfL p = 0.0004). TI+ and PND differed only in GFAP levels, which were higher in TI+ (CSF-GFAP p = 0.0049/sGFAP p = 0.003). The overall group effect (p ≤ 0.003) and principal findings remained significant after adjustment for age, sex, QAlb, and time since (symptom) onset to LP. Bi-compartmental analysis revealed simultaneous elevation of CSF and serum NfL in TI+, indicating predominantly central origin, whereas PND demonstrated a shift toward higher sNfL levels suggesting peripheral origin. Higher clinical severity (modified Rankin Scale 3-5) was associated with elevated serum and CSF GFAP and NfL (sGFAP p = 0.012/sNfL p = 0.002; CSF-GFAP p < 0.0001/CSF-NfL p = 0.0001), which also predicted unfavorable outcome at discharge (sGFAP p = 0.006/sNfL p = 0.004; CSF-GFAP p = 0.003/CSF-NfL p = 0.012). NfL and GFAP were associated with brain/myelon involvement in NID, predominantly reflecting central pathology. Despite strong CSF-serum correlations, bi-compartmental approaches provide additional insight into biomarker origin and disease compartment.

Humans↗

PubMed2026

From fear to empowerment: the impact of employees AI awareness on workplace well-being - a new insight from the JD-R model.

PURPOSE: The primary purpose of the study was to explore the impact of health workers' awareness of artificial intelligence (AI) on their workplace well-being, addressing a critical gap in the literature. By examining this relationship through the lens of the Job demands-resources (JD-R) model, the study aimed to provide insights into how health workers' perceptions of AI integration in their jobs and careers could influence their informal learning behaviour and, consequently, their overall well-being in the workplace. The study's findings could inform strategies for supporting healthcare workers during technological transformations. DESIGN/METHODOLOGY/APPROACH: The study employed a quantitative research design using a survey methodology to collect data from 420 health workers across 10 hospitals in Ghana that have adopted AI technologies. The study was analysed using OLS and structural equation modelling. FINDINGS: The study findings revealed that health workers' AI awareness positively impacts their informal learning behaviour at the workplace. Again, informal learning behaviour positively impacts health workers' workplace well-being. Moreover, informal learning behaviour mediates the relationship between health workers' AI awareness and workplace wellbeing. Furthermore, employee learning orientation was found to strengthen the effect of AI awareness on informal learning behaviour. RESEARCH LIMITATIONS/IMPLICATIONS: While the study provides valuable insights, it is important to acknowledge its limitations. The study was conducted in a specific context (Ghanaian hospitals adopting AI), which may limit the generalizability of the findings to other healthcare settings or industries. Self-reported data from the questionnaires may be subject to response biases, and the study did not account for potential confounding factors that could influence the relationships between the variables. PRACTICAL IMPLICATIONS: The study offers practical implications for healthcare organizations navigating the digital transformation era. By understanding the positive impact of health workers' AI awareness on their informal learning behaviour and well-being, organizations can prioritize initiatives that foster a learning-oriented culture and provide opportunities for informal learning. This could include implementing mentorship programs, encouraging knowledge-sharing among employees and offering training and development resources to help workers adapt to AI-driven changes. Additionally, the findings highlight the importance of promoting employee learning orientation, which can enhance the effectiveness of such initiatives. ORIGINALITY/VALUE: The study contributes to the existing literature by addressing a relatively unexplored area - the impact of AI awareness on healthcare workers' well-being. While previous research has focused on the potential job displacement effects of AI, this study takes a unique perspective by examining how health workers' perceptions of AI integration can shape their informal learning behaviour and, subsequently, their workplace well-being. By drawing on the JD-R model and incorporating employee learning orientation as a moderator, the study offers a novel theoretical framework for understanding the implications of AI adoption in healthcare organizations.

Humans↗

PubMed2026

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

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

Students, Medical↗

PubMed2026

The future of precision oncology and artificial intelligence in Belgium: scenarios and policy responses.

PURPOSE: Precision medicine, also known as personalized medicine, enables the provision of tailored health services to patients. In the prevention, early detection, and treatment of cancers, precision medicine is highly promising, given the increasing use of genomic profiling for diagnosis and adapting therapies in several tumor types. Artificial Intelligence (AI) can support this process by analyzing vast amounts of relevant data. However, high-quality data and financial investments in the health system are essential for the implementation of precision medicine and AI solutions in routine cancer care. DESIGN/METHODOLOGY/APPROACH: Building on the quantitative outcomes of a foresight exercise published in another study, this article collects qualitative data to gain more detailed insights into the future of precision oncology in Belgium and discusses the role of AI in this field. It reports the results of a series of expert workshops, focusing on four hypothetical future scenarios that are centered around technological and economic issues that must be overcome for the widespread use of precision oncology in Belgium. FINDINGS: The study concludes that all four scenarios discussed in the workshops would require supportive policy measures in Belgium, which should go beyond mere technological and economic considerations, such as involving patient associations and the public in policy design or creating multi-disciplinary expert groups for precision medicine. ORIGINALITY/VALUE: To the best of our knowledge, this is the first study to employ foresight methodology to illustrate possible future scenarios, scrutinize feasible approaches for implementing precision oncology in Belgium, and discuss the use of AI in this context.

Belgium↗

PubMed2026

Factors influencing the enhancement of the new iron triangle in healthcare organisations.

PURPOSE: A new paradigm, "healthcare's new iron triangle," has been developed to emphasise the technological perspective of healthcare delivery, focusing on automation, value and empathy. The study aims to build a conceptual model and to identify factors for the enhancement of the new iron triangle in healthcare organisations. DESIGN/METHODOLOGY/APPROACH: The healthcare organisation is the primary focus point of the current study. To determine the factors, a survey of the literature and healthcare experts' opinions was conducted. The healthcare professionals validated the identified factors. Data for this study were gathered using a closed-ended questionnaire and scheduled interviews. The study employed "Total Interpretive Structural Modeling methodology and Matriced' Impacts Croise´s Multiplication Appliqué´ a UN Classement/Cross-Impact Matrix Multiplication Applied to a Classification (MICMAC) analysis" to address the "why" and "how" the factors interact and prioritise the identified factors. FINDINGS: The study found that organisational structure (F8), artificial intelligence (F1), innovation (F2) and human resources (F5) are the driving or key factors of the study. RESEARCH LIMITATIONS/IMPLICATIONS: The study primarily focused on identifying factors for the enhancement of a new iron triangle in healthcare organisations. The scope could eventually be expanded to explore more areas. PRACTICAL IMPLICATIONS: Academics and other stakeholders will have a better understanding of the key drivers for the enhancement of the new iron triangle in healthcare organisations. ORIGINALITY/VALUE: In this study, total interpretive structural modeling and cross-impact MICMAC analysis are proposed as an innovative approach to address the new iron triangle in healthcare organisations.

Humans↗

PubMed2026

Diffusion MRI radiomics in meningiomas: imaging correlates of tumor grade and intraoperative consistency.

OBJECTIVE: Despite advancements in imaging studies, the preoperative prediction of the biological behavior and intraoperative consistency of intracranial meningiomas remains limited. This study evaluated the association of volumetric diffusion-based and texture-derived radiomic features extracted from routine MRI with histopathological aggressiveness and intraoperative tumor consistency. METHODS: Ninety-seven intracranial meningiomas resected at two tertiary centers were retrospectively analyzed. Volumetric segmentation was performed on contrast-enhanced T1-weighted MRI and coregistered to apparent diffusion coefficient (ADC) maps. Data on first-order diffusion metrics and selected texture features were collected. The associations between World Health Organization (WHO) grade and Ki-67 index were assessed using nonparametric tests and Spearman correlation analysis. Independent factors associated with intraoperative tumor consistency (Zada grades 1-5) were evaluated via multivariate ordinal logistic regression analysis that adjusted for tumor volume, skull base location, calcification status, and WHO grade. Secondary receiver operating characteristic (ROC) curve analyses were performed to differentiate solid (Zada grades 4-5) from soft (Zada grades 1-2) tumors. ROC analyses were performed within the study cohort and were intended as exploratory assessments of discriminative performance. RESULTS: The mean ADC (ADCmean) and the 10th percentile of the ADC decreased significantly with increasing WHO grade (p < 0.001). ADCmean had a moderate inverse correlation with the Ki-67 index (r = -0.42, p < 0.001) and intraoperative tumor consistency (r = -0.45, p < 0.001). In the multivariate analysis, the ADCmean remained independently associated with increasing tumor firmness. Each 0.1 × 10-3 mm2/sec increase corresponded to a 38% reduction in the odds of belonging to a higher consistency category (OR 0.62, 95% CI 0.51-0.74, p < 0.001). The ROC analysis showed good discrimination for solid tumors (area under the curve 0.847, 95% CI 0.742-0.953) and soft tumors (area under the curve 0.824, 95% CI 0.714-0.935). Texture features had weaker associations with intraoperative tumor consistency. CONCLUSIONS: Volumetric diffusion-derived metrics, particularly ADCmean, are associated with both histopathological aggressiveness and intraoperative tumor firmness in meningiomas. Diffusion imaging may reflect a graded microstructural continuum rather than a purely dichotomous property, providing complementary preoperative insights into surgical complexity.

Humans↗

PubMed2026

Metal-organic frameworks nanozyme-integrated portable microneedle patch for visual bacterial monitoring in meat.

Foodborne microbial contamination is a major global health concern, with conventional methods often being time-consuming and complex. Herein, we developed a novel portable biosensor by integrating microneedle patch technology and a metal-organic framework (Fe/Cu-NBDC MOF) nanozyme, enabling rapid, on-site, visual detection of bacteria in meat. The sensing system works by encapsulating aptamer-functionalized MOF nanozymes within a hydrogel patch, where their catalytic sites are initially blocked by the aptamer. In the presence of Staphylococcus aureus (S. aureus) as the target, the specific aptamer's binding to bacteria exposes numerous catalytic sites, further activating the chromogenic reaction of the tetramethylbenzidine‑hydrogen peroxide (TMB-H₂O₂) system, enabling visual detection of S. aureus. The biosensor demonstrates a detection limit of 82 CFU/mL with excellent specificity to successfully apply to commercial mutton. By integrating sampling, enrichment, and visual detection into a single compact device, this platform offers a practical, efficient solution for rapid on-site screening of foodborne pathogens.

Biosensing Techniques↗

PubMed2026

Efficacy, tolerability, and threshold effect of atropine eye drops for myopia control: A systematic review and dose-response meta-analysis.

Atropine is an emerging therapy for myopia, yet the optimal concentration for prescription remains uncertain. We searched PubMed, Embase, Web of Science, Cochrane Library, World Health Organization International Clinical Trials, and ClinicalTrials.gov registry platforms. We included the randomized clinical trials (RCTs) that compared any dose of atropine against a placebo in myopic children. Among 3566 studies assessed, we identified 33 eligible RCTs involving 6301 children aged 4-18 years, with 10 different concentrations and a mean follow-up time of 19.5 ± 12.3 months. A nonlinear relationship was observed between atropine dosage and treatment efficacy (P < 0.001). Compared to placebo groups, the mean differences in reducing annual spherical equivalent refraction progression for atropine concentrations of 0.01%, 0.02%, 0.03%, 0.04%, and 0.05% were 0.21 diopters (D) (95% CI, 0.13-0.28), 0.35 D (95% CI, 0.23-0.46), 0.42 D (95% CI, 0.28-0.56), 0.45 D (95% CI, 0.30-0.60), and 0.46 D (95% CI, 0.32-0.61) respectively For higher concentrations, the estimates were 0.49 D (95% CI, 0.34-0.63) for 0.1% and 0.99 D (95% CI, 0.66-1.31) for 1%, although these were based on fewer and smaller trials. Higher doses of atropine were associated with decreased amplitude of accommodation (P = 0.02), increased pupil diameters (P = 0.01) and a higher frequency of photophobia (P = 0.02). Our findings suggest that the increase in treatment efficacy with higher concentrations may plateau beyond a certain range, and that the current practice of increasing atropine concentrations for children who show inadequate responses to lower doses should be confined to a specific concentration range. This analysis is limited by the number, design heterogeneity, and sample sizes of available trials for higher concentrations, and by the frequent lack of pre-intervention refractive history in included studies. Therefore, estimates-particularly for doses exceeding 0.1%-should be interpreted with caution.

Humans↗

PubMed2026

Assessing perinatal depression identifying abilities among maternal and child health workers in rural China using smartphone-based virtual patients: a multi-center cross-sectional study.

OBJECTIVE: To assess rural maternal and child health (MCH) workers' virtual patients (VPs)-assessed performance in identifying perinatal depression (PND) using smartphone-based VPs, and to identify factors associated with this performance in rural Hunan, China. METHODS: A multicentre cross-sectional study was conducted in Hunan Province, China. A standardized questionnaire collected demographic and work-related characteristics of rural MCH workers. Smartphone-based VPs were used to assess PND identification performance in a simulated clinical scenario. An overall score ≥60 was used as a prespecified operational benchmark across consultation, ancillary assessment, diagnosis, management, and health education domains. Data were analyzed using SPSS 26.0. RESULTS: A total of 375 rural MCH workers participated, yielding an effective response rate of 90.4%. Only 25.9% met the prespecified operational benchmark for VP-assessed PND identification performance. The mean accuracy scores for consultation, ancillary assessment, diagnosis, management, and health education were 94%, 48%, 64%, 58%, and 74%, respectively. Complete consultation accuracy was higher among MCH workers from township health centers than among those from county-level MCH hospitals. MCH workers aged 18-39 years showed higher odds of complete diagnostic accuracy for PND than those aged ≥40 years. CONCLUSIONS: Smartphone-based VP assessment was feasible in rural MCH settings and revealed suboptimal PND identification performance. Mobile VPs may help identify frontline performance gaps and inform targeted training, but further validation against real-world clinical performance, or standardized patient encounters is needed before large-scale implementation. These findings may support targeted capacity-building for rural MCH workers and more equitable perinatal mental health care.

Humans↗

PubMed2026

Assessing the public health impact of routinely collected electronic healthcare record data in NICE guidelines: A systematic review of CPRD research.

OBJECTIVES: Evidence used in NICE guidance has traditionally prioritised randomised controlled trials, but increasing availability of electronic health record (EHR) data has expanded opportunities for real-world evidence. The Clinical Practice Research Datalink (CPRD) is a commonly used UK primary care EHR resource, yet the extent to which CPRD studies have informed NICE guidelines in the past decade is unclear. STUDY DESIGN: The systematic review was conducted in accordance with PRISMA guidelines. METHODS: We conducted a systematic review of CPRD studies in PubMed, MEDLINE, and Embase published between 04/16-09/25. For each eligible CPRD study, targeted searches of NICE guidelines were performed to identify explicit citations in NICE guidelines. Two reviewers screened and extracted data independently, resolving disagreements by consensus or third reviewer. Guideline information, number of guidelines over time, type of guidelines, and disease area guidelines (using British National Formulary (BNF) chapters) were described. RESULTS: 7181 records were identified. After de-duplication, 2704 unique CPRD studies were screened against NICE guidelines. Of these, 92 CPRD-based studies met inclusion criteria and were cited across 67 NICE documents. The annual number of NICE guidelines citing CPRD studies increased between 2016 and 2025; 1.5% of identified guidelines published in 2016 and 27.7% in 2025. The guideline citing the most CPRD studies was cancer related. The most common types of guidelines included clinical guidelines (49.3%) and technology appraisals (32.8%). Guidelines made up 12 different BNF categories, most frequently central nervous system related (23.9%; n = 16). CONCLUSION: Observational CPRD studies are increasingly referenced in NICE guidelines across multiple disease areas, supporting the growing role of EHR data in national guideline development.

Clinical studies↗

PubMed2026

Transabdominal lumbar approach (TALA) versus retroperitoneal approach for robot-assisted renal surgery: a prospective randomised controlled trial.

PURPOSE: Common robotic nephrectomy approaches access the kidney via transperitoneal (TP) or retroperitoneal (RP) routes, each with distinct trade-offs. We developed the transabdominal lumbar approach (TALA), combining advantages of both accesses with improved visualisation and strategic trocar placement, and compared it with conventional RP in a prospective randomised controlled trial using technique-oriented intraoperative endpoints. METHODS: In this single-centre, prospective, open-label RCT, 40 patients were randomised to TALA (n = 18) or conventional RP (n = 22). Eligible patients were ≥ 18 years with a renal tumour or non-functional kidney requiring robot-assisted total or partial nephrectomy. Exclusions included prior surgery on the affected kidney, renal vein tumour thrombus, and pregnancy. Both groups were followed for 30 days. The primary endpoint was time from first skin incision to renal artery identification. RESULTS: TALA achieved a median time saving of 16 min compared to conventional RP (38 vs. 54 min, p = 0.001). Perioperative safety was comparable between groups, with three patients (7.5%) experiencing Clavien-Dindo grade III-IV complications. CONCLUSIONS: TALA met its primary endpoint with a significantly shorter time to renal artery identification than conventional RP access, and improving perceived surgical exposure and instrument handling.

Humans↗

PubMed2026

Improving insurance deduction identification: a hybrid artificial intelligence model using machine learning and expert systems.

PURPOSE: Financial challenges in healthcare systems worldwide, especially in low- and middle-income countries like Iran, have increased hospitals' reliance on insurance reimbursements. Unrecognized insurance deductions often cause severe financial shortages, making efficient deduction management crucial. This study aimed to design a hybrid intelligent system for identifying and predicting insurance deductions by combining machine learning and expert system frameworks. DESIGN/METHODOLOGY/APPROACH: A mixed-methods design was applied in four stages. First, a scoping review identified the causes and patterns of insurance deductions. Second, interviews with 15 insurance experts produced a validated checklist and a dataset from inpatient billing records. Third, using the CRISP-DM methodology, machine learning algorithms were developed and tested in SPSS Modeler alongside a fuzzy expert system developed in MATLAB. Finally, the model was validated using the holdout method. FINDINGS: Four categories of deduction drivers were identified: service provision, registration errors, document submission issues, and revenue conversion processes. The CHAID decision tree outperformed other algorithms with a 99% precision rate and the lowest Mean Absolute Error (9.43). A brief assessment of potential overfitting was conducted to ensure that the CHAID model's high accuracy was interpreted cautiously and supported by the validation results. The fuzzy expert system with validated rules was adaptable for deduction classification, especially for cases unsuitable for quantitative modeling. ORIGINALITY/VALUE: The hybrid model improves detection and prevention of deductions, offering actionable insights for hospital administrators, insurers, and policymakers. Its implementation can enhance hospital information systems, streamline claims processing, and optimize revenue management amid financial constraints.

Machine Learning↗

PubMed2026

Microplastic contamination in South Asian commercially important seafood: A comprehensive assessment of occurrence, source, and human health risk.

Seafood is a cornerstone of global food security and human nutrition, serving as the primary source of animal protein for more than one-fourth of the global population, with South Asia representing one of the world's fastest-growing seafood-consuming regions. However, escalating microplastic (MP) pollution in marine ecosystems poses an emerging threat to seafood safety and human health, yet a comprehensive regional assessment of MP contamination in South Asian seafood remains lacking. This study presents the first region-wide systematic synthesis of the literature on MP contamination in commercially important seafood across South Asia, integrating occurrence patterns, human exposure assessment, polymer-specific hazard evaluation, and bibliometric analysis to address this critical knowledge gap. The meta-analysis estimated an average microplastic exposure of 145 particles/person/day through seafood consumption in South Asia, with fish contributing the highest intake (121 particles/person/day). The detected polymers were classified into PHI hazard levels I-IV, with polyvinyl chloride (PVC), polyurethane (PU), and polyacrylamide (PAM) representing the highest hazard categories. The mean pollution load index (PLI) was 7.71 (Category I), with crustaceans exhibiting the highest contamination (PLI = 10.07). Polypropylene was the predominant polymer, whereas fragments and blue particles were the most frequently reported microplastic characteristics. These findings provide the first regional baseline for assessing microplastic contamination, polymer-associated hazards, and human exposure through seafood consumption in South Asia, underscoring the need for standardized monitoring and targeted mitigation strategies to safeguard seafood safety and public health.

Animals↗

PubMed2026

"Orphaned bereavement": Toward a public health model for bereavement.

Bereavement is increasingly recognized as a public health concern, yet support systems in many welfare states continue to allocate support according to the circumstances of death rather than the functional needs of bereaved families. Existing bereavement frameworks have substantially advanced understanding of social recognition and public legitimacy but provide more limited guidance for understanding how institutional responsibility for bereaved families is organized. using Israel as a bereavement-saturated case, this study introduces the concept of orphaned bereavement to describe bereavement in which no institution holds clearly defined and continuing responsibility for identifying needs, coordinating support, and ensuring continuity of care. Drawing on 25 semi-structured interviews with five bereaved family members and 20 professionals, analyzed using reflexive thematic analysis, the analysis generated three interrelated themes: institutionalized invisibility and unequal recognition; reorganizing life in the absence of institutional support; and pathways toward a needs-based model of bereavement support. The findings extend existing theories of disenfranchized grief and grievability by introducing institutional responsibility as a complementary lens for understanding bereavement inequality and support a needs-based public health approach in which support is organized according to families' evolving functional needs rather than the circumstances of death.

Journal Article↗

PubMed2026

Associations between smart infusion pump-electronic health record interoperability and healthcare outcomes: A systematic review.

OBJECTIVE: This study synthesized available evidence on the associations between smart infusion pump-electronic health record (EHR) interoperability and healthcare outcomes. METHODS: A systematic review of PubMed, CINAHL, Embase, and Scopus databases identified 901 records, which were imported into Rayyan® for duplicate removal, independent screening by three reviewers, and resolution of discrepancies. Eligible studies were peer-reviewed, data-driven, and reported associations between smart infusion pump-EHR interoperability and healthcare outcomes. Studies focused solely on technical validation or interoperability prototypes were excluded. A backward citation search identified additional studies. Two reviewers independently extracted and cross-validated study characteristics using standardized templates. Methodological quality was assessed with the Joanna Briggs Institute Critical Appraisal Tools. RESULTS: Twenty records of 14 full-text studies and 6 conference proceedings were included. Most records reported positive associations between smart infusion pump-EHR interoperability and outcomes related to safety (e.g., medication administration errors, safety-reported events, pump alerts, and compliance with interoperability and drug library), operational efficiency (e.g., programming and documentation time and technical issues), financial performance (e.g., charges captured, and cost avoided), and user experience domains. Most studies used observational designs, reflecting real-world interoperability implementations, where controlling confounding factors is challenging. Limited reporting of baseline characteristics, pump type, and sample sizes limited comparability across studies. CONCLUSIONS: Smart infusion pump-EHR interoperability was associated with improvements in patient safety, efficiency, charge capture, and user experience, with variable findings across studies. Future research should use rigorous methodologies and standardized measures, examine relationships across outcome domains, assess limitations of pump-EHR interoperability, and evaluate underexplored outcomes, including team communication, cognitive workload, and AI-enabled pumps. IMPLICATIONS FOR CLINICAL PRACTICE: Interoperability should be viewed as a component of a broader sociotechnical system, in which technology, user, workflow, clinical content, and organizational practices collectively determine overall effectiveness.

Humans↗

PubMed2026

Prevalence of psychosis in South Asia: A systematic review and meta-analysis.

BACKGROUND: Psychotic disorders are a major contributor to global disability, yet prevalence data from South Asia which inhabits a quarter of the world's population, remain limited. Reliable estimates are essential for health service planning, policy, and closing the substantial treatment gap. This review provides the first comprehensive synthesis of psychosis prevalence across South Asia. METHODS: We searched PubMed, Embase, Web of Science, Global Health, and Medline to 18 December 2024 for DSM- or ICD-based prevalence studies in Afghanistan, Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan, and Sri Lanka. Cross-sectional and longitudinal studies in community or clinical populations were included. Study quality was assessed using the Joanna Briggs Institute checklist. Random-effects meta-analyses estimated pooled prevalence using the logit transformation. Heterogeneity was explored with meta-regression of key methodological variables (publication year, diagnostic system, residential setting). FINDINGS: Thirty-one studies from five countries were included. Among community-dwelling adults, pooled point prevalence was 0.85% and lifetime prevalence was 1.40%, with inter-country differences (India 1.18%, Pakistan 2.13%, Nepal 2.90%). Clinical samples showed substantially higher proportions of individuals with psychosis in service settings (11.44%), reflecting concentration of cases in treatment-seeking samples. Data for children and adolescents were limited and summarised narratively. Heterogeneity was high across meta-analyses, and exploratory meta-regression did not identify any significant moderators. INTERPRETATION: Psychosis prevalence estimates in South Asia appear higher than global averages but should be interpreted cautiously due to substantial heterogeneity and methodological variation; nevertheless, they highlight the need for culturally sensitive screening, improved detection, and strengthened mental health services.

Humans↗