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PubMed2026

Vitamin B12 Deficiency in Sickle Cell Disease: Method-Driven Estimates and Systematic Diagnostic Misclassification.

OBJECTIVES: To determine whether the reported 0%-70% prevalence of vitamin B12 deficiency in sickle cell disease (SCD) reflects true population variation or diagnostic misclassification. METHODS: We conducted a PRISMA 2020-compliant systematic review of observational studies (January 1, 2000-May 13, 2026; PROSPERO CRD420251087800) assessing B12 status in SCD. PubMed, AJOL, and Google Scholar were searched with citation tracking and dual screening. Diagnostic validity was assessed across biomarker strategy, analytical platform, thresholds, and confounder control using a proposed context-integrated framework to classify methodological robustness and discordance. RESULTS: Fourteen studies were included (57% high-income; 43% LMIC). The evidence base was dominated by limited diagnostic approaches: 71% used immunoassays, over one-third relied on circulating B12 alone, and functional biomarkers were inconsistently applied without systematic confounder adjustment. Prevalence estimates were strongly influenced by diagnostic methods rather than underlying population biology, ranging from 0% to 70% in single-marker studies (mostly 0%-7.1%, with outliers ~50%-70%) and 6.9%-53% in multi-marker studies. Discordance was substantial and greater in LMIC settings than HIC. CONCLUSION: Current diagnostic approaches in SCD appear method-dependent, generating heterogeneous prevalence estimates with uncertain clinical validity. These findings challenge existing estimates and have implications for clinical practice, research design, and diagnostic equity. TRIAL REGISTRATION: ClinicalTrials.gov identifier: CRD420251087800.

Humans↗

PubMed2026

How is goal setting used in interventions for chronic disease prevention and management in sub-Saharan Africa? A systematic review and narrative synthesis.

Non-communicable diseases are increasingly prevalent in sub-Saharan Africa, and goal setting is often used to promote healthy self-management behaviours. In this review, we aimed to synthesise literature around how goal setting is used, for application in future interventions in the region. A systematic search was conducted in six databases and results screened for eligibility. Study characteristics, intervention details, goal setting components, feedback from participants and facilitators were extracted. Data were analysed using narrative synthesis and thematic analysis. The Mixed Methods Appraisal Tool was used to assess study quality. We included 24 publications describing 18 unique interventions. Included studies were of high to moderate methodological quality. Goal setting intervention components were informed by a variety of frameworks and involved a range of tasks. Interventions were often facilitator-led; many were conducted in group settings. Participants reported goal setting as useful for putting self-management into practice but encountered challenges related to language and literacy levels. Adequate detail on goal setting intervention components was not always present. Through this review, we provide a comprehensive picture of the variability of goal setting approaches in chronic disease prevention and management in sub-Saharan Africa and recommend more standardised use and reporting of goal setting intervention components.

Humans↗

PubMed2026

Systematic Review of Pharmacologic Treatment for Migraine Prevention in Adults: Report of the AAN Guidelines Subcommittee and the American Headache Society.

BACKGROUND AND OBJECTIVES: This systematic review (SR) provides updated evidence-based conclusions regarding the use of pharmacologic migraine prevention in adults to inform a new joint American Academy of Neurology (AAN) and American Headache Society practice guideline. METHODS: A multidisciplinary panel conducted an SR following the 2017 AAN Clinical Practice Guideline Process Manual. Randomized controlled trials evaluating pharmacologic preventive treatments for adults with episodic or chronic migraine were included. Searches encompassed MEDLINE, Embase, and ClinicalTrials.gov from database inception through June 6, 2024. Studies were screened in duplicate, with dual independent risk-of-bias assessment. Outcomes included change in monthly headache days, ≥50% responder rate, and validated patient-reported quality of life (QOL) measures. Raw mean differences, standardized mean differences, and risk ratios were calculated. A modified Grading of Recommendations Assessment, Development, and Evaluation process was used to classify certainty of evidence. RESULTS: A total of 217 studies met inclusion criteria. For episodic migraine, high-confidence evidence showed that galcanezumab and erenumab are more effective than placebo in reducing headache frequency. Moderate-confidence evidence supported benefit from atogepant, eptinezumab, fremanezumab, propranolol, topiramate, and valproate. Several additional oral agents including amitriptyline, bisoprolol, flunarizine, fluoxetine, levetiracetam, metoprolol, nifedipine, pizotifen, and telmisartan had low-confidence evidence suggesting possible benefit. For chronic migraine, high-confidence evidence supported reductions in headache frequency with fremanezumab, galcanezumab, and onabotulinumtoxinA. Moderate-confidence evidence supported benefit from atogepant, eptinezumab, erenumab, topiramate and valproate. Across both episodic and chronic migraine populations, erenumab, fremanezumab, galcanezumab, eptinezumab, rimegepant, atogepant, topiramate and onabotulinumtoxinA demonstrated improvements in patient-reported QOL outcomes on validated instruments. Evidence comparing active treatments was limited and generally of low or very low confidence, restricting conclusions about comparative effectiveness. DISCUSSION: This SR provides a comprehensive synthesis of evidence on pharmacologic migraine prevention in adults. High- and moderate-confidence findings confirm the efficacy of several established and newer preventive therapies and demonstrate improvements in patient-reported outcomes across multiple validated measures. These conclusions informed the development of evidence-based recommendations, presented in a companion publication, to guide clinicians in selecting preventive medications for adults with episodic and chronic migraine.

Humans↗

PubMed2026

Comparative Efficacy of Different AI Systems for Polyp Detection by Size During Colonoscopy: Systematic Review and Network Meta-Analysis.

BACKGROUND: Colorectal cancer remains a leading cause of death despite being largely preventable through polypectomy. AI systems designed to enhance polyp detection during colonoscopy have shown promise, but the extent to which they improve detection of different-sized polyps remains unclear. OBJECTIVE: This study compared the size-stratified efficacy of AI-assisted colonoscopy vs standard colonoscopy using the Hartung-Knapp-Sidik-Jonkman (HKSJ) method, and generated exploratory rankings while acknowledging all cross-platform comparisons are indirect. METHODS: This systematic review and network meta-analysis (NMA) searched PubMed, Embase, Cochrane CENTRAL, and Web of Science from inception to July 25, 2026, supplemented by citation searching. We included randomized controlled trials (RCTs) comparing AI-assisted vs standard colonoscopy in adults (≥18 years of age), reporting mean polyp detection counts stratified by size (≤5 mm, 6-9 mm, and ≥10 mm). Two reviewers screened studies, extracted data, and assessed risk of bias using the Cochrane Risk of Bias 2.0. We conducted frequentist NMA using the HKSJ method with restricted maximum likelihood estimation, calculated 95% prediction intervals (PIs), and assessed heterogeneity using I2 and τ2. Certainty of evidence was rated using the GRADE (Grading of Recommendations Assessment, Development, and Evaluation) framework. RESULTS: A total of 13 RCTs (4156 participants) compared 8 AI systems to standard colonoscopy, forming a network without direct AI comparisons. For diminutive polyps (≤5 mm), AI showed a modest advantage (standardized mean difference [SMD] 0.21, 95% CI 0.07 to 0.35, 95% PI -1.12 to 1.54), but substantial heterogeneity (I2=86.6%) and wide PI crossing the null indicated high uncertainty. EndoScreener showed the most consistent evidence (SMD 0.36, 95% CI 0.18-0.54). For small and large polyps, effects were minimal (SMD 0.02, 95% CI -0.02 to 0.06, 95% PI -0.03 to 0.07; SMD 0.01, 95% CI 0.00-0.02, 95% PI -0.01 to 0.03). GRADE certainty was very low for diminutive polyps and low for small and large polyps. Sensitivity analysis excluding Tianjin YuJin did not materially change findings. CONCLUSIONS: AI may modestly enhance diminutive polyp detection, but effects on small and large polyps are minimal, with no platform superiority. Given very low to low certainty, findings are hypothesis-generating. This exploratory NMA provides size-stratified comparisons that can inform future head-to-head trial design. Unlike prior reviews aggregating all polyp sizes, we show the overall AI benefit is driven by diminutive polyp detection, providing a framework for targeted deployment-prioritizing AI for diminutive polyp screening, with limited value for larger lesions. Head-to-head trials are urgently needed. TRIAL REGISTRATION: PROSPERO International Prospective Register of Systematic Reviews CRD420251266932; https://www.crd.york.ac.uk/PROSPERO/view/CRD420251266932.

Colonoscopy↗

PubMed2026

Artificial intelligence in treatment prediction for skeletal Class III malocclusion: A systematic review.

In skeletal Class III patients, treatment options range from orthodontics to orthognathic surgery. Choosing the optimal approach requires a comprehensive clinical evaluation, which may be supported by AI tools. The aim of this study was to assess the performance of AI models in predicting the need for orthognathic surgery and in identifying predictors influencing treatment decisions. A PRISMA-guided electronic database search (PubMed, Web of Science; 2009-2024; English/French) was performed to identify studies using machine learning (ML) or deep learning (DL) on cephalometric and clinical data. After screening and assessment for eligibility, 15 studies were critically appraised. Model performance was summarized using accuracy, sensitivity, specificity, and the area under the curve (AUC). ML algorithms (particularly Random Forest and XGBoost) and DL models (ResNet-based convolutional neural networks (CNNs)) achieved high accuracy for predicting surgical need. Frequently selected predictors included Wits appraisal, ANB angle, the maxillomandibular ratio (Mx/Md), overjet, and the divergence of the lower gonial angle. AI methods show promise for assisting treatment decisions in Class III malocclusion, with Random Forest and XGBoost performing well on tabular cephalometric data and CNNs on imaging. Larger, multicentre datasets and external validation are needed to improve reliability, address bias, and support clinical implementation.

Humans↗

PubMed2026

Metagenome-scale modeling to assess microbiome metabolic complementarity for precision microbiota transplantation therapies.

Fecal microbiota transplantation (FMT) holds therapeutic promise beyond recurrent Clostridioides difficile infection, but clinical outcomes remain unpredictable and donor-selection strategies remain limited, in part because the role of donor‒recipient metabolic interactions in shaping the post-FMT community remains poorly understood. Here, we leverage metagenome-scale metabolic modeling to quantify metabolic niche complementarity between donor and recipient microbiomes and predict post-FMT community composition. Using MICOM-derived metabolic models, we show that donor genomes whose metabolic flux profiles are more dissimilar from the recipient community colonize at significantly higher rates in a murine FMT model. In a human IBS trial, the same metric predicted post-FMT community composition via leave-one-out cross-validation and captured known disease-associated alterations in short-chain fatty acid, sulfur, and gas metabolism. We then performed 2,548 in silico FMT simulations between IBS-D/M patients and donors from the OpenBiome biobank to evaluate personalized donor screening, identifying super-donors characterized by high taxonomic diversity, broad metabolic niche coverage, and community interaction networks dominated by cross-feeding rather than competition. Together, these results support metabolic niche complementarity as a potential determinant of post-FMT community composition and provide a mechanistic basis for evaluating donor-recipient metabolic compatibility. This framework offers a scalable approach for generating testable hypotheses for personalized donor selection.

Fecal Microbiota Transplantation↗

PubMed2026

Disparities in guideline-adherent cardiovascular preventive care for people with diabetes: A systematic review and meta-analysis.

BACKGROUND: Clinical practice guidelines offer guidance on delaying the progression of cardiovascular disease in people living with diabetes. We sought to determine whether guideline-recommended cardiovascular preventive care for people living with diabetes differs according to sociodemographic indicators, globally. METHODS: We conducted a systematic review of studies that compared the sociodemographic characteristics of people diagnosed with type 1 or 2 diabetes who received cardiovascular preventive care as recommended by guidelines to those who did not. Sociodemographic predictors were defined by PROGRESS+ (an equity framework). We searched MEDLINE, EMBASE, and APA PsychInfo from 2010 to January 21, 2026. Studies were screened independently by two people. One person assessed the risk of bias and extracted data, and another verified. We pooled results using a random-effects model and assessed the certainty of evidence using GRADE. RESULTS: Twenty-five studies were included. Meta-analyses showed female, Black, and Hispanic individuals had slightly lower odds of receiving guideline-recommended prescriptions for lipid-lowering medication compared to Male, and White individuals, respectively (OR:0.89, 95%CI:0.79,1.00, moderate certainty; OR:0.78, 95%CI:0.74,0.81, high certainty; OR:0.86, 95%CI:0.59,1.26, low certainty). Individuals aged 18-45 years had moderately lower odds (OR:0.33, 95%CI:0.19,0.57, moderate certainty), no observed association for Asian individuals. Asian individuals had moderately lower odds of antihypertensive medication prescription (OR:0.42, 95%CI:0.38,0.46, high certainty). Evidence suggests likely no association between HbA1c testing and sex/gender or between sex/gender and lipid panel testing. CONCLUSIONS: Some disparities in guideline-recommended cardiovascular preventive care among people living with diabetes were found. These results are consistent with previous reviews and highlight the need to ensure guidelines consider equity and with improved dissemination.

Humans↗

PubMed2026

Retinal microstructural alterations as early phenotypes of depression in radiogenomics analysis.

BACKGROUND: With the increasing prevalence of depression, there is an urgent clinical need for early screening in depression. The retina offers a promising window for early screening in depression due to its rapid, non-invasive, objective, eye-brain correlated characteristics, but previous research has yielded conflicting alterations in retinal microstructure in depression. METHODS: We screened retinal optical coherence tomography and brain magnetic resonance imaging data in the UK Biobank to enroll 23,225 participants for retinal study of depression occurrence, and 1475 participants for the eye-brain association study. We also used genetic data (ID: ebi-a-GCST90014267 and ukb-d-20,448) from the Integrative Epidemiology Unit Open Genome-Wide Association Study for Mendelian randomization analysis. We used Cox regression to assess the association between retinal microstructure and depression risk, Mendelian randomization to infer causality, and mediation analysis to explore retina-brain pathway association. RESULTS: The Cox regression analysis showed that retinal ganglion cell-inner plexiform layer (GCIPL) thickness remained a significant predictor of depression. The Mendelian randomization analysis indicated a positive statistical association between GCIPL thickness and depression. Moreover, there was a significant positive correlation (all p < 0.001) between the volume of specific depression-related brain regions and the GCIPL thickness. Adjusting for age, sex, and head size, the mediation analysis provided preliminary evidence for a potential anatomical pathway linking retinal GCIPL thickness to depression-related brain regions through primary visual cortex and secondary visual cortex volumes. CONCLUSION: Thickened retinal GCIPL is a potential early phenotype of depression and has a potential association pathway with depression-related brain regions using a radiogenomics approach.

Humans↗

PubMed2026

Male accessory gland proteins in Grapholita molesta: Identification and reproductive functional validation of four accessory gland-specific lipases.

Accessory gland proteins (Acps), synthesized in the male accessory glands (AGs), are transferred to females via spermatophores during mating and elicit diverse post-mating physiological and behavioral responses. However, Acps have not been comprehensively characterized in Grapholita molesta, a cosmopolitan orchard pest. Here, using data-independent acquisition mass spectrometry, we describe an integrated proteomic approach combining comparative AG analyses (virgin vs. newly mated) with spermatophore profiling to identify Acps in G. molesta. According to the established screening criteria, we identified 83 confirmed Acps, which were classified into nine categories. Tissue-specific expression patterns of 20 randomly selected Acp genes were evaluated, revealing that these genes were specifically or highly expressed in male AGs. Among the 83 confirmed Acps, four Acps harbored the PLN02872 superfamily domain and were classified into the canonical lipase family. Notably, their transcripts were all highly expressed in the AGs during the pre-maturation stage. These four Acps were selected for preliminary validation of their male reproductive functions. RNAi-mediated knockdown of three out of four lipase genes in G. molesta males significantly decreased the fertility of mated females, with phenotypes including a significant reduction in egg production and egg hatching rate. This study provides a comprehensive catalog of high-confidence Acps, lays a foundation for subsequent in-depth functional characterization of these reproductive proteins, and offers promising molecular targets for the development of novel genetic regulation-based integrated pest management strategies.

Animals↗

PubMed2026

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

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

Humans↗

PubMed2026

Future promise, current clinical ambiguity: a systematic review of machine learning algorithm outputs predicting risk of cardiovascular disease.

OBJECTIVE: To examine whether the outputs of machine learning algorithms designed to predict risk of cardiovascular disease (CVD) address known deficiencies of the Framingham Risk Score (FRS) and improve risk estimates. METHODS: For this critical review, Medline, Embase and IEEE were searched from inception to 1 January 2025. Included were studies describing machine learning algorithms designed to specifically compare output of cardiovascular risk assessment with the FRS. Commentaries, letters, unpublished work or non-peer-reviewed papers were excluded.Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, two reviewers screened titles and abstracts independently, then populated a purpose-built data extraction form. A subsequent qualitative thematic analysis focused on algorithms' strengths, added value, potential harms, unintended consequences and equity implications.The main outcome assessed was whether, among healthy adults, the algorithm improved CVD risk prediction relative to the FRS. RESULTS: Of 707 studies retrieved, 29 met inclusion criteria. 23 reported improved predictive ability relative to the FRS. Most datasets and/or medical records used included sociodemographic predictors of CVD not included among FRS inputs. Some added costly diagnostic tests like CT angiography to FRS screening indicators. When they were defined, inputs and outcomes such as hypertension or myocardial infarction did not always adhere to FRS values. Statistical significance was generally taken as a proxy for clinical significance. Some algorithms overestimated the number at risk compared with the FRS without discussing whether that larger proportion might be at risk of overdiagnosis rather than CVD, while a few decreased the proportion found to be at risk. CONCLUSIONS: Use of artificial intelligence to improve accuracy of risk assessment for CVD demonstrates the technological capacity to merge known sociodemographic predictors with biologic variables and examine non-linear interactions among these. Still needed to achieve patient benefit is clinical insight, adherence to screening principles and cost-benefit assessment of inputs selected.

Humans↗

PubMed2026

Temporal evolution of minimally invasive pediatric urolithiasis treatment over 30 years.

Urolithiasis in children has increased substantially over the past 30 years, and surgical management maintains an important role in treatment. Technological advances such as lasers and miniaturization have broadened treatment options, and researchers investigate the best indications for each procedure. The aim was to identify publication trends in the field and explore reasons why Extracorporeal Shockwave Lithotripsy is being gradually less applied in the treatment of pediatric urolithiasis. A Reverse Systematic Review of the literature was conducted regarding the surgical treatment of urolithiasis in children. Five databases were screened, gathering all articles from inception that were evaluated in systematic reviews. We examined 123 publications, 197 reports, and 15,878 procedures, consisting of the largest studied population in the field. There was an increasing number of publications, although in progressively less prestigious journals. The number of studies on miniaturized percutaneous techniques and flexible ureteroscopy has increased closely with the rise in popularity of these procedures worldwide, mainly driven by studies from Asia, Europe, and North America. A trend of self-renewed interest is fueled by technological innovation and has led to fewer publications on Extracorporeal Shockwave Lithotripsy over the years. This review highlights the fact that, despite positive results in recent studies, the low popularity of ESWL within the scientific community is driving a decline in the technique's indications. Moreover, based on the findings of this study, key research priorities include continued reporting of high-quality outcomes, and technological progress in ESWL would contribute meaningfully to the field.

Humans↗

PubMed2026

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

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

Humans↗

PubMed2026

Non-parametric differential methylation analysis characterizes histotype-specific promoter regions in epithelial ovarian cancer.

Epithelial ovarian cancer (EOC) is a heterogenous disease with frequent late-stage diagnosis and high mortality rates, for which no reliable screening tests exist. In recent years, epigenetic biomarkers in the form of DNA methylation in CpG-rich regions have gained increased attention in the scientific community due to their robust nature and accessibility, allowing for diagnosis without the need for invasive surgery. In this study, we investigated the aberrant methylation of promoter regions in early stage EOC through non-parametric methods, with the purpose of characterizing candidate epigenetic biomarkers. The approach was used on a cohort of early stage EOC samples, and results were compared to existing programs for differential methylation. Significant regions were then used to construct a CpG panel for stratifying EOC histotypes through predictive classification in external data. Identified promoter regions were highly reproducible across cohorts, and the constructed CpG model stratified histotypes in external cohorts through predictive classification. Comparisons against other DMP and DMR callers showed a degree of homogeneity between results but also revealed promoter regions that were overlooked despite clear signs of aberrant methylation. Finally, EOC histotypes were found to differ in their methylation distribution types, and results indicate that methods sensitive to non-normally distributed data may be poorly suited to compare groups with different distribution types. The non-parametric approach identified aberrantly methylated promoter regions that were highly reproducible across cohorts. Results from predictive classification indicate that these regions may be useful for the purpose of EOC histotype stratification.

Humans↗

PubMed2026

Effects of extended problem-based learning interventions on undergraduate nursing education: A systematic review.

OBJECTIVE: Exploring the effects of long-term PBL (problem-based learning) intervention on undergraduate nursing students. METHODS: The article retrieved literature from CINAHL Complete, Academic Search Complete, Web of Science, PubMed, EMBASE, OVID, and Cochrane Library up to January 2025. Studies had to meet all of these criteria: (1) They used a randomized controlled trial (RCT) and quasi-experimental design. (2) The PBL pedagogy intervention lasted 4 weeks or longer. (3) The participants were undergraduate nursing students. (4) They reported primary outcomes. These included critical thinking, problem-solving skills and self-directed learning. Two researchers screened articles, extracted data, and assessed quality independently using blinding. They used Cochrane ROB2 for RCTs and ROBINS-I for quasi-experimental studies to judge bias risk. Meta-analysis was performed using RevMan 5.4 software. For continuous variables, standardized mean difference (SMD) and 95% confidence interval were calculated. Heterogeneity was assessed by I2 statistic. When I2 > 50%, sensitivity analysis was conducted. The source of heterogeneity was explored by excluding studies one by one. The primary outcomes included standardized critical thinking, problem-solving, and self-directed learning assessment results. RESULTS: A total of 11 randomized controlled trials and quasi-experimental studies were retrieved and included for meta-analysis. The experimental group significantly outperformed the control group in critical thinking, problem-solving, and self-directed learning, with differences being statistically significant (P ≤ 0.05). However, high heterogeneity was observed. After sensitivity analysis, the heterogeneity was reduced and the results remained statistically significant, indicating that the findings were not solely dependent on the excluded studies.

Problem-Based Learning↗

PubMed2026

Accelerated Diagnostic Pathways for Suspected Acute Coronary Syndrome in Practice: A Randomized Trial of 0/1-Hour vs 0/3-Hour Troponin Testing.

BACKGROUND: For suspected acute coronary syndrome (ACS), guidelines recommend using high-sensitivity troponins (hs-cTn) in accelerated diagnostic pathways (ADPs) with 0/1-hour recommended over 0/3-hour ADP. However, implementation of these ADPs, with universal use of hs-cTns, has not been directly compared in randomized trials OBJECTIVES: This study sought to compare the efficiency and safety of the European Society of Cardiology (ESC) 0/1-hour and a 0/3-hour ADP when implemented in real-world clinical practice. METHODS: This pragmatic, randomized, noninferiority implementation trial compared the safety and efficiency of clinician decision making using these 2 pathways. To prevent incorporation bias, an independent hs-cTnI was used for formal adjudication using the fourth universal definition of myocardial infarction (MI). Efficiency was judged by the proportion of patients discharged within 4 hours. The safety endpoint was major adverse cardiac events (MACE) within 30 days (adjudicated index or representation type 1 MI, cardiovascular death, and urgent coronary revascularization) for those who were considered not to have ACS and discharged. The noninferiority margin, for absolute difference in sensitivity, between the ESC 0/1-hour and the 0/3-hour ADP was set at 3%, assessed with a 1-sided 97.5% CI. RESULTS: From December 2021 to July 2024, of 13,983 screened 3,543 individual patients with suspected ACS were recruited and consented from 2 major emergency departments in North-West England, with 100% follow-up achieved for all representations to any national hospital. The median age was 60 years (IQR: 49.5-70.5 years), 53% were men, 6.7%, and 7.6% had adjudicated index type 1 MI and MACE within 30 days, respectively. The turnaround time from sample to result for central laboratory hs-cTnT was 81 minutes (IQR: 69-101 minutes). The proportion of patients discharged within 4 hours was relatively low and did not differ substantially (21.8% vs 19.2%, P = 0.07). In addition, the 0/1-hour pathway was noninferior for safety, in patients discharged, compared with the 0/3-hour pathway, absolute difference in sensitivity was +4.2% (1-sided 97.5% CI: -2.5) in favor of the 0/1-hour pathway. The calculated sensitivities were 93.7% (95% CI: 88.4%-97.1%) vs 89.5% (95% CI: 82.7%-94.3%), respectively. CONCLUSIONS: Implementation of the ESC 0/1-hour pathway failed to discharge significantly more patients within 4 hours of presentation compared with the 0/3-hour ADP. In addition, The ESC 0/1-hour was noninferior to the 0/3-hour hs-cTn pathway for safety of discharge, although safety for both pathways was less than that imputed by observational studies. This trial demonstrates that perceived benefits to emergency department efficiency of a reduced sampling interval are mitigated by central laboratory turnaround times as well as system constraints. (Pragmatic Randomised Trial of the ESC 0/1 Versus 0/3 Hour Troponin Pathway [MACROS2]; NCT05322395).

Acute Coronary Syndrome↗

PubMed2026

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

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

Humans↗

PubMed2025

Systems Factors Contributing to Racial/Ethnic Disparities in Maternal Health: A Systematic Review.

INTRODUCTION: Despite ongoing efforts to reduce adverse maternal outcomes, including maternal mortality and severe maternal morbidity, racial/ethnic disparities in outcomes persist in high-income countries, including the United States (US) and Canada. Limited research has examined hospital-level factors that may drive disparities and contribute to adverse outcomes. This systematic review summarizes factors within the health system contributing to adverse outcomes and racial/ethnic disparities in the US and Canada to inform future policies and practices. METHOD: We searched SCOPUS, PubMed, EBSCOhost, and ProQuest Healthcare Administration for studies that reported hospital-level factors contributing to adverse maternal outcomes and racial/ethnic disparities. The review followed a two-stage screening process. The risk of bias of the included studies was evaluated using the Mixed Methods Appraisal Tool. The System Engineering Initiative for Patient Safety (SEIPS) 2.0 framework guided the identification and categorization of factors. RESULTS: Of 2441 studies retrieved, 30 met the inclusion criteria. Twenty-eight studies were conducted in the US, and 2 were conducted in Canada. The review included 16 qualitative, 11 quantitative, and 3 mixed-methods studies. We identified 60 factors associated with different system components, including person(s) (12%), tasks (28%), tools and technology (7%), internal environment (10%), organization (28%), and external environment (15%). Shortage of resources, including staffing, poor care coordination, and discriminatory organizational practices, were key factors described in the studies. CONCLUSION: Addressing health system factors in addition to broader societal factors is important to reduce adverse outcomes and promote equity for all women and birthing persons.

Humans↗