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PubMed2026

An introductory practical guide to secondary data analysis in pediatric urology.

INTRODUCTION: Secondary data analysis (SDA) has become an increasingly important approach in pediatric urology, enabling the study of long-term outcomes, care variation, and disparities in populations with chronic or congenital urologic conditions. With the growing availability of large datasets, a structured approach to designing and conducting SDA studies is increasingly relevant. OBJECTIVES: To provide an introductory, practical guide to SDA in pediatric urology by (1) summarizing commonly used data sources with representative studies, (2) outlining a stepwise approach to designing and executing SDA studies, and (3) highlighting key methodological considerations, limitations, and opportunities for future work. STUDY DESIGN: Narrative review of existing literature and commonly used datasets relevant to pediatric urology, including administrative claims, hospital encounter databases, clinical registries, electronic health record networks, and population-based surveys. RESULTS: Data sources differ in scope, clinical granularity, longitudinal follow-up, and representativeness, and each is suited to specific research questions. We present a practical workflow for SDA, including dataset selection, cohort definition, and analytic planning. Linkage across datasets can provide a more comprehensive view of care patterns and outcomes, although feasibility is influenced by legal, technical, and data-quality constraints. DISCUSSION: SDA enables population-level analyses and the study of rare conditions that are challenging to evaluate through single-center or prospective designs. However, careful cohort definition, feasibility assessment, and awareness of data limitations are essential to ensure validity and interpretability. CONCLUSION: SDA provides a scalable, cost-efficient framework for generating meaningful evidence in pediatric urology. Continued efforts to harmonize data elements, improve linkage infrastructure, and support cross-institution collaboration will enhance the quality and impact of future research. This article provides a practical framework and examples to support the design and execution of SDA studies.

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

Efficient homologous replacement and deletion of large genomic fragments through template-jumping prime editing in rice.

Homologous replacement of genomic sequences with large DNA fragments (> 100 bp) holds great potential for crop breeding, yet an efficient method to achieve such edits is lacking in plants. Here, in rice, we developed template-jumping prime editing (TJ-PE), a recently reported PE strategy for large targeted insertion, as an efficient tool for homologous replacement with DNA fragments ranging from dozens to hundreds of base pairs, and using TJ-PE, we replaced genomic fragments of up to 340 bp with homologous fragments of the same length. In addition, our TJ-PE tool also enabled precise deletion of 944- to 2024-bp fragments in rice, with efficiencies of up to 34.6% for c. 2000-bp precise deletions. Collectively, this study expands the editing scope of PE in rice and establishes TJ-PE as a generalist tool for precise deletion and replacement of large DNA fragments.

Oryza↗
PubMed2026

Cost-Effectiveness of Electronic Patient-Reported Outcome Measure Interventions in Cancer: Systematic Review and Parameter Extraction for Economic Modeling.

BACKGROUND: Complex digital interventions that integrate electronic patient-reported outcome measures (ePROM) into clinical practice in cancer have the potential to improve quality of life, increase survival, and reduce health resource use and costs. Such systems can help patients with cancer self-manage chemotherapy symptoms, reduce clinicians' workloads through automated decision support, and resolve problems earlier. However, more research on the cost-effectiveness of ePROM monitoring is needed. OBJECTIVE: This paper comprises two complementary components: (1) a systematic literature review summarizing and evaluating the quantitative and qualitative evidence related to the cost-effectiveness of ePROM monitoring and (2) a health economic model parameter extraction. We also conducted supplementary targeted searches and scoping to provide context to our findings. METHODS: We searched Ovid (including MEDLINE and Embase), Scopus, and the International Health Technology Assessment Database for original English-language papers published on or before March 2025 using search strings that combined terms related to ePROMs, health economics, and cancer/oncology. We included papers reporting health economic-related outcomes for ePROM interventions designed for adult cancer populations and excluded screening tools and conference abstracts. RESULTS: We included 34 publications from 27 unique studies and identified and analyzed 26 ePROM-integrated interventions within these. Most (23/26) of the included interventions explicitly described some form of alert handling and automated decision support based on remote ePROM monitoring. Of the 34 publications, 5 presented full cost-effectiveness analysis results, of which 3 were highly uncertain and lacked clear differences in costs and health outcomes between ePROMs and standard care; conversely, 2 presented strong evidence of cost-effectiveness due to quality-of-life improvements, reduced hospitalizations, and potentially more autonomy in health-related travel (eg, ePROM-monitored patients can drive or walk to the hospital instead of using taxis or ambulances). A further 5 publications reported partial health economic results (eg, cost-consequence and budget impact), of which 1 detected no difference in strategies; in contrast, 4 reported lower health resource use and costs of ePROMs, mainly due to hospitalization reductions. Overall, 12 of the 27 studies included a qualitative component but mostly focused on user experience and design-related themes; only 2 of these addressed economic-specific themes (eg, changes in workflow and resource use due to ePROM implementation and integration), indicating some potential for time saving due to ePROM monitoring. CONCLUSIONS: Some ePROM-integrated interventions demonstrated cost-effectiveness in cancer care, but the evidence base remains limited. Where evidence does exist, cost-effectiveness appears driven by reduced hospitalization and improved quality of life. Qualitative research within the included studies rarely addressed economic questions. We provide a detailed parameter extraction for use in future economic modeling and recommend research priorities, including quantitative mapping of ePROM symptom data onto health resource use patterns, and qualitative work exploring how ePROM implementation affects clinical workloads and patient-perspective costs.

Humans↗
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

Genomic epidemiology of clinically critical antibiotic resistance in Salmonella enterica causing bloodstream infections across six Chinese provinces, 1994-2023.

Clinically critical antibiotic-resistant Salmonella enterica (S. enterica) causing bloodstream infections remains a public health challenge. Here, we aim to reveal the emergence and trends of clinically important antibiotic resistance in S. enterica causing bloodstream infections using 833 isolates from six Chinese provincial-level administrative areas during 1994-2023. We identified 48 serovars and 64 sequence types (STs). Overall, 8.52% of 833 isolates were resistant or had decreased susceptibility to ciprofloxacin, 4.32% and 6.84% reported resistance or decreased susceptibility to third- and fourth-generation cephalosporins (3GCs and 4GCs), 1.80% reported resistance to fosfomycin, and 2.16% reported resistance to azithromycin. Across these six regions, azithromycin and fosfomycin resistance is increasing, as is decreased susceptibility or resistance to ciprofloxacin, 3GCs, and 4GCs, especially among younger children and elderly people. Clinically prioritized antibiotic resistance also varies by region, serovar, and age group. S. Paratyphi A genotype 2.3.3 strains are mainly divided into 2 lineages distributed in Guangxi and Shanghai. Within the scope of this passive surveillance dataset, S. Typhi genotype 4.3.1.2.1 was identified as the earliest documented case among the collected isolates. Our retrospective and longitudinal genomic epidemiology study provides critical data for the formulation of treatment guidelines and policies for bloodstream infections and for the monitoring and control of antimicrobial resistance.

Humans↗
PubMed2026

The Animal Variant Classification Guidelines v2: An Update With New Criteria and Improved Clarifications.

The Animal Variant Classification Guidelines (AVCG) were developed to standardize and objectify the classification of putative disease-causing variants. These guidelines are sufficiently reproducible and are used to classify previously published and new disease-causing variants across species. Here, the guidelines are updated (AVCG.v2), based on a three-phase decision process. Overall, four new criteria and seven clarifying comments were added. The number of criteria has increased from 23 to 27, with three new criteria supporting pathogenicity and one new criterion supporting benign classification. Pharmacogenomic variants were determined to fall within the scope of the guidelines. These updated guidelines are being used by the Variant Pathogenicity Working Group (VPWG), part of the Animal Genetic Testing Standardization standing committee, which is a committee of elected members of the International Society for Animal Genetics (ISAG). Under the auspices of ISAG, the VPWG retrospectively classifies published putative disease-causing variants. The pathogenicity label for a variant will be presented in the variant tables of Online Mendelian Inheritance in Animals (OMIA; https://omia.org/). The AVCGv.2 criteria and recommendations were developed by the expertise of the animal genetics community and the ISAG Executive Committee through the Animal Genetics Testing Standardization Committee endorses and strongly encourages their use to evaluate the evidence supporting pathogenicity of putative disease-causing variants.

Animals↗
PubMed2026

Lipid metabolism is a key central, systemic and gut microbial feature of the decline in rat hippocampal function during middle age.

Middle age is emerging as a turning point in brain ageing, prognostic of future cognitive health and amenable to intervention. Metabolic and proteomic differences during this period are not yet fully understood and may potentially influence functions of the hippocampus, a brain area that regulates memory and anxiety. While the gut microbiota is implicated in brain ageing, the relationship between the gut microbiota, the metabolic state, and hippocampal proteome in middle age has not been investigated. We hypothesise that peripheral metabolic or protein features are associated with hippocampal vulnerability in middle age. Therefore, young adult and middle-aged rats were assessed for behavioural, proteomic, metabolic, and gut microbiota differences. Proteomic profiling of the hippocampus revealed differential expression of proteins indicative of altered synaptic signalling. Concurrently, adult hippocampal neurogenesis was decreased in middle age. Hippocampal microglia exhibited a lipid rich, inflammatory phenotype in middle age which correlated with poorer memory performance. CSF and serum proteomic and metabolomic analyses identified dysregulated lipid-related pathways potentially contributing to hippocampal vulnerability in middle age. Furthermore, 16S rRNA sequencing revealed reduced abundance of bacteria involved in lipid metabolism regulation. However, faecal microbiota transfer from young to middle aged rats was not sufficient to robustly improve hippocampus-dependent spatial memory. Together, these findings highlight dysfunctional lipid metabolism as a key feature of middle age that may contribute to decline in hippocampal function. Given that the scope for intervention is limited during older age, targeting biomarkers involved in metabolic and lipid homeostasis may be pivotal for the development of pharmacological or lifestyle-based interventions during middle age which could ultimately delay future cognitive ageing.

Animals↗
PubMed2026

Long-term hormone therapy for perimenopausal and postmenopausal women.

BACKGROUND: Hormone therapy is widely provided to control menopausal symptoms and has been used for the management and prevention of cardiovascular disease, osteoporosis and dementia in older women. This is an updated version of a Cochrane review first published in 2005. OBJECTIVES: To assess the long-term effects of prolonged use (at least one year) of hormone therapy on mortality, cardiovascular outcomes, cancer, gallbladder disease, fractures and cognition in perimenopausal and postmenopausal women. SEARCH METHODS: We used the Cochrane Gynaecology and Fertility Group Specialised Register, CENTRAL, MEDLINE, three other databases and two trial registers, together with reference checking, citation searching and contact with study authors to identify the studies included in the review. The latest search date was 26 September 2024. SELECTION CRITERIA: We included randomised, double-blind trials in which peri- or postmenopausal women took hormone therapy or placebo for at least one year. We included various oestrogen formulations, with or without progestogens. We focused on studies assessing hormone therapy's effects on long-term clinical outcomes, including death, coronary events and cancer. Hormone therapy's efficacy in managing menopausal symptoms was beyond the scope of this review, and is assessed in other Cochrane reviews. DATA COLLECTION AND ANALYSIS: Two review authors independently selected studies, assessed risk of bias and extracted data. We calculated risk ratios (RRs) for dichotomous data and mean differences (MDs) for continuous data, along with 95% confidence intervals (CIs). We assessed the certainty of the evidence using GRADE. MAIN RESULTS: We included 24 studies - with two newly added in this update - involving 45,660 participants. We derived nearly 70% of the data from two well-conducted studies: the Heart and Estrogen/progestin Replacement Study (HERS 1998) and the large, multi-component Women's Health Initiative research programme, which included two hormone therapy arms (WHI 1998). Across all the studies, most participants were postmenopausal American women with one or more comorbidities. The mean participant age in most studies was over 60 years. Only one included study focused on perimenopausal women. We present full results for all included studies with available data in the main review. The results presented below are drawn from WHI 1998, in which the combined hormone therapy arm and the oestrogen-only arm were run concurrently, with women assigned to the appropriate trial based on their uterus status. One study with 16,608 postmenopausal women with an intact uterus compared combined continuous hormone therapy (conjugated equine oestrogen and medroxyprogesterone acetate) to placebo, and measured outcomes at an average of 5.6 years of follow-up. Based on this study, combined continuous hormone therapy probably makes little to no difference to the risk of a coronary event (RR 1.17, 95% CI 0.95 to 1.44; moderate-certainty evidence). It may increase the risk of stroke (RR 1.39, 95% CI 1.09 to 2.09; low-certainty evidence) and venous thromboembolism (RR 2.03, 95% CI 1.55 to 6.64; low-certainty evidence). Compared to placebo, combined continuous hormone therapy probably increases the risk of breast cancer (RR 1.27, 95% CI 1.03 to 1.56; moderate-certainty evidence) and probably makes little to no difference to the risk of lung cancer (RR 1.06, 95% CI 0.77 to 1.46; moderate-certainty evidence). It may increase gallbladder disease requiring surgery (RR 1.64, 95% CI 1.30 to 2.06; 14,203 participants; low-certainty evidence), and probably reduces the risk of all clinical fractures (RR 0.78, 95% CI 0.71 to 0.86; moderate-certainty evidence). One study including 10,739 postmenopausal women who had undergone a hysterectomy compared oestrogen-only (conjugated equine oestrogen) hormone therapy to placebo, and measured outcomes at an average of seven years' follow-up. Based on this study, oestrogen-only hormone therapy probably makes little to no difference to the risk of coronary events (RR 0.94, 95% CI 0.78 to 1.13), venous thromboembolism (RR 1.32, 95% CI 1.00 to 1.74) and breast cancer (RR 0.79, 95% CI 0.61 to 1.01), all with moderate-certainty evidence. It may make little to no difference to the risk of lung cancer (RR 1.04, 95% CI 0.73 to 1.48; low-certainty evidence). Oestrogen-only hormone therapy probably increases the risk of stroke (RR 1.33, 95% CI 1.06 to 1.67) and gallbladder disease requiring surgery (RR 1.78, 95% CI 1.42 to 2.24), and probably reduces the risk of all clinical fractures (RR 0.73, 95% CI 0.65 to 0.80), all with moderate-certainty evidence. We judged most included studies to have a low risk of bias for most domains. The overall certainty of evidence for the main comparisons was moderate. The main limitation was that only about 30% of women were 50 to 59 years old at baseline, the age group most likely to consider hormone therapy for vasomotor symptoms. AUTHORS' CONCLUSIONS: Long-term follow-up of women using hormone therapy suggests that the risk profiles vary between combined hormone therapy and oestrogen-only therapy. Oestrogen-only hormone therapy probably makes little to no difference to coronary events, and probably increases the risk of stroke and gallbladder disease. It probably makes little to no difference in the risk of breast cancer, and probably reduces the risk of all fractures. Combined hormone therapy may increase the risk of thromboembolism and probably increases the risk of breast cancer. These results should be interpreted with caution as they are based on one study using oral hormone therapy, which may not represent the risks of the hormone therapy currently used in clinical practice.

Humans↗
PubMed2026

Validation of a Turkish Translation of the Stress in Emergency Healthcare Professionals: The Stress Factors and Manifestations Scale.

AIM: The primary duties of emergency healthcare professionals (EHPs) are to provide emergency patient care to acutely ill and injured individuals. Due to the nature of their work, EHPs operate under constant stress, often requiring rapid decision-making, swift action, and the delivery of necessary medical care in life-or-death situations, sometimes under inadequately safe conditions. Therefore, the aim of this study is to determine the validity and reliability of the Emergency Healthcare Professional Stress Factors and Symptoms (SEHP:SFMS) Scale in Turkish for identifying stress factors and symptoms in emergency medical care professionals providing emergency patient care services. DESIGN: A methodological study design was used in this study. METHODS: The study was conducted with the participation of 211 EHPs from employees working in emergency care institutions affiliated with the Muğla Provincial Health Directorate between November 2023 and June 2024. Data were collected via a face-to-face survey. Data were analysed using Lawshe content validity ratio, Kaiser-Meyer-Olkin coefficient, Bartlett test, exploratory factor analysis, principal component analysis, Varimax factor rotation method, confirmatory factor analysis, Cronbach's α internal consistency coefficient, convergent validity, discriminant validity, test-retest, and Spearman correlation coefficient tests. RESULTS: The linguistic translation and cultural adaptation of the SEHP:SFMS showed strong performance. The scope validity index of the scale is 0.83. The item-total correlation values of the scale were found to be between 0.486 and 0.794, and the factor loadings were between 0.474 and 0.816. Confirmatory factor analysis fit indices: χ2 = 248.727; df = 101; n = 211; p = 0.000; χ2/df = 2.463; RMSEA = 0.083; CFI = 0.914, SRMR = 0.052, which was found to be compatible and acceptable with the proposed 3-factor model. The Cronbach's α reliability coefficient of the scale was 0.931, and the total variance was 61.97%. CONCLUSIONS: SEHP:SFMS is a valid and reliable tool to assess stress factors and symptoms of Turkish emergency healthcare professionals. Its use improves the quality of emergency care. PATIENT OR PUBLIC CONTRIBUTION: These study findings have been used to create a tool with Turkish validity and reliability that allows for the examination of stress factors among healthcare professionals working in emergency and critical services. Identifying and reducing stress factors among healthcare professionals is crucial for the delivery of quality healthcare services. It can also be used to develop targeted interventions and ongoing strategies to facilitate improved clinical supervision and mentoring. IMPLICATION FOR NURSING PRACTICE: Nurses in emergency departments, which are among the most stressful, dynamic, intense, life-saving, and critical environments in healthcare institutions, and where life-saving treatment is administered, are at high risk of experiencing psychological trauma. Trauma experienced in the work environment is a significant problem for nursing. The consequences of trauma negatively affect nurses and institutions. Studies show that post-traumatic stress, anxiety, depression, and burnout are commonly observed in emergency department nurses. In this sense, understanding the stress and stress factors experienced by nurses can guide future interventions. The results of this study are considered important in making visible the stress and stress factors experienced by nurses in the emergency department, and also in guiding managers and nurses working in this field in terms of preventive and protective measures.

Humans↗
PubMed2026

Effectiveness of exercise-based prehabilitation on pre and postoperative outcomes of patients undergoing cardiac surgery-An umbrella review of systematic reviews.

AIMS: Individuals undergoing cardiac surgery are becoming older, frailer, and less mobile. Prehabilitation has shown to improve postoperative outcomes by optimizing preoperative physical function. This umbrella review aims to pool the systematic reviews assessing the effectiveness of exercise-based prehabilitation in cardiac surgery. METHODS AND RESULTS: The review followed the PRIOR checklist. PubMed, Embase, CINAHL, Cochrane library, Scopus, Web of science, ProQuest NAHD, ProQuest HMC, Open Grey and MedNar were searched using relevant keywords from inception to 16th December, 2024. Two reviewers screened and extracted data from the included reviews and assessed primary study overlap with the corrected covered area. Methodological quality of the reviews was evaluated with the A MeaSurement Tool to Assess systematic Reviews-2 scale. Certainty of evidence was assessed using a previously developed criteria for overview of reviews. Six systematic reviews with 30 unique trials and 6705 participants were included. The interventions assessed included breathing exercises, inspiratory muscle training, and exercise training. Prehabilitation reduced length of hospital stay, postoperative pulmonary complications, and clinically improved functional capacity with a very low to moderate certainty of evidence. However, there was uncertainty regarding the effects pertaining to adverse events and quality of life. The methodological quality of all reviews was critically low. The primary trials scored poorly in the domains of selection and detection bias. CONCLUSION: Exercise-based prehabilitation might reduce length of hospital stay and postoperative complications, and improve functional capacity. However, the quality of evidence is poor, and individual discretion is required before implementing them into practice. REGISTRATION: PROSPERO: CRD42023480100.

Humans↗
PubMed2026

Identifying and Prioritizing Core Components of Relationship Education Programs: a Case Study of an Artificial Intelligence (AI) Assisted Systematic Review.

The field of prevention science seeks to identify and implement effective strategies to address social, emotional, and health challenges. A critical aspect of this endeavor is determining the core components of prevention programs that drive positive outcomes. This article presents a case study utilizing artificial intelligence (AI)-assisted systematic review methods to identify key components of healthy marriage and relationship education programs. Given the growing body of research in this domain, AI tools offer a promising means to enhance the efficiency and accuracy of literature reviews. This study employed AI to screen, code, and validate research articles, demonstrating its effectiveness in expediting systematic reviews while maintaining high accuracy in inclusion screening. This case study involved a systematic review of 22,028 resources (identified from PsycINFO, Academic Search Ultimate, and Google) and a final data set of 268 relevant studies. AI screening was integral in effectively conducting multiple rounds of screening. However, findings also highlight challenges in AI-assisted qualitative data abstraction, underscoring the continued need for human expertise in complex coding tasks. The study contributes to the ongoing discourse on integrating AI into prevention science methodologies and offers insights for optimizing AI applications in systematic reviews.

Artificial Intelligence↗
PubMed2026

Health risk assessment of inorganic arsenic: an umbrella review.

Inorganic arsenic (iAs) is a toxic environmental pollutant linked to serious health risks, prompting global regulatory efforts. This study identifies major health conditions associated with iAs exposure using text network analysis, and assesses health risk assessments through an umbrella review and dose-response analysis. It synthesizes previous systematic reviews to offer a broader perspective on iAs-related health effects. An optimized text network analysis-based search strategy was applied across multiple databases to identify relevant systematic reviews. An umbrella review framework was employed to synthesize and reinterpret findings across systematic reviews. The methodological quality of included systematic reviews was assessed using the A MeaSurement Tool to Assess systematic Reviews 2 tool. Extracted data on study characteristics, exposure levels, and risk estimates were analyzed to evaluate the dose-response relationship between iAs exposure and health outcomes. From 922 systematic reviews, 36 were included and categorized into 10 health condition groups. For example, seven SRs found a significant dose-response relationship between iAs and bladder cancer, with one systematic review reporting relative risks of 2.70, 4.20, and 5.80 at 10, 50, and 150 µg/L, respectively. Individual study analysis further showed that each 10 µg/L increase in iAs raised bladder cancer risk by 3.11 % (p=0.003). iAs exposure is associated with hypertension, diabetes, cardiovascular disease, and adverse fetal outcomes. Dose-dependent increases in bladder cancer, lung cancer, and hypertension risks were observed. These findings support more precise health risk assessments and regulatory strategies.

Humans↗
PubMed2026

Association of media use with sleep of children and adolescents: an umbrella review.

Adequate sleep is essential for child and adolescent development, driving extensive research across scientific disciplines. This umbrella review provides a comprehensive overview of existing evidence on media consumption and sleep and thereby lays the foundation for identifying key concepts and gaps. An inclusive systematic search for reviews reporting literature searches was conducted in 02/2021 and updated last in 09/2024. Methodological quality of the included reviews was assessed using AMSTAR-2. We included 84 reviews reporting on the association between media use and sleep in individuals aged 0-18 years. The field is dominated by reviews of low methodological quality, mainly including original cross-sectional studies with subjective measures in older children and adolescents. A total of 475 original articles were covered by the reviews; only 10 of them appeared in at least seven and at most nine reviews. Screen time generally had a negative impact on sleep, though evidence varied from very low to strong. Evidence for effects of conventional books on sleep remains inconclusive. High quality systematic reviews are needed to evaluate robust studies using objective measures of sleep and contemporary media use across all age groups up to adolescence and to explore the impact of non-digital media use on sleep, considering age and gender differences.

Humans↗
PubMed2026

What's the meta now? More updates on the problems with systematic reviews.

BACKGROUND: Systematic reviews are intended to provide trustworthy evidence synthesis, yet previous iterations of this living review have identified numerous recurring problems in their conduct and reporting. This article presents the third version and second update of the living systematic review examining issues raised across the academic literature. METHODS: Using consistent eligibility criteria and methods from earlier versions, literature searches were updated to May 2025. Eligible meta-research and editorial articles describing problems with systematic reviews were analyzed to identify emerging themes. Additionally, four basic indicators of methodological quality of the included meta-research were presented across review versions. RESULTS: The update included 209 additional articles. Critically low methodological quality and absence of protocols remained among the most frequently reported issues in systematic reviews across disciplines and journals but notably in evidence underpinning clinical practice guidelines. Spin in abstracts and conflicts of interest continued to be common. Apparent improvements in reporting quality were inconsistent, with modest gains in some full-text reporting but persistent deficiencies in abstracts. Authorship diversity of systematic reviews improved in gender representation but remained geographically concentrated in high-income countries, and primary research included in reviews similarly lacked global representativeness. The issue of misalignment between systematic review evidence bases and global burden of disease bring the total number of problems with systematic reviews to 69. Emerging use of automation and artificial intelligence was variably reported. Descriptive comparison of meta-research articles over the three versions of this living review suggests a greater proportion meeting basic quality indicators in more recent updates. CONCLUSION: Across successive updates, problems with systematic reviews remain widespread and consistent rather than isolated. Incremental reporting improvements coexist with persistent concerns about transparency, bias, and representativeness. Future efforts should prioritize evaluating interventions and aligning research incentives to support genuinely trustworthy evidence synthesis.

Humans↗
PubMed2026

Artificial intelligence for dental caries detection: An umbrella review.

Artificial intelligence (AI) has been proposed as a tool to improve dental caries detection across imaging modalities; however, its clinical value remains uncertain. This umbrella review aimed to synthesize and critically appraise systematic reviews evaluating AI for caries detection and diagnosis. An umbrella review was conducted following PRIOR guidance (PROSPERO CRD420261340728). Searches were performed in MEDLINE, Embase, Scopus, Web of Science, and Google Scholar up to 15 March 2026. Methodological quality was assessed using AMSTAR 2, and overlap of primary studies was quantified using the corrected covered area (CCA). Seventeen systematic reviews were included, of which five reported diagnostic test accuracy meta-analyses using bivariate or HSROC models. Across these meta-analyses, pooled sensitivity ranged from 0.76 to 0.94 and specificity from 0.85 to 0.91. Most systems were based on deep learning models applied to bitewing radiographs and intraoral photographs. However, substantial heterogeneity was observed in imaging modalities, lesion thresholds, analytical tasks, and evaluation metrics. In addition, a high degree of overlap across reviews and recurrent methodological limitations, including reliance on retrospective datasets, limited external validation, and inconsistent reporting, substantially weaken the reliability of the evidence. Although AI models demonstrate high diagnostic performance under experimental conditions, current evidence does not support their use as stand-alone diagnostic tools. Their clinical applicability remains limited, and implementation should be restricted to decision-support contexts until robust prospective validation demonstrates meaningful impact on clinical decision-making and patient outcomes.

Dental Caries↗
PubMed2026

The environmental impact of diagnosis and therapy in obstructive sleep Apnea: A systematic review.

Healthcare contributes significantly to global greenhouse gas (GHG) emissions, yet the environmental impact of sleep medicine, particularly the diagnosis and therapy of obstructive sleep apnea (OSA), remains poorly characterized. We systematically searched PubMed, Scopus, and Embase (2015-2025) for studies on OSA care reporting environmental metrics (carbon footprint, energy use, resource consumption) or healthcare resource utilization. Supplementary searches identified additional non-peer-reviewed sustainability-focused studies that have been presented at conferences. Of 19 primary peer-reviewed studies on OSA care and utilization, only one reported environmental metrics (telemedicine CO2 savings related to reduction in travel-related emissions). Supplementary sources revealed that OSA care has a measurable carbon footprint driven by disposable equipment, device electricity, and travel and that OSA diagnostics create significant solid waste with opportunities for waste reduction through the use of reusable equipment. This review shows that while the environmental impact of sleep medicine has been rarely studied to this date, available evidence suggests significant opportunities for sustainability through virtual care, home testing, and equipment optimization. Future research should incorporate environmental impact into the assessment of clinical pathways.

Humans↗