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PubMed2026

Pelvic lymph node dissection in prostate cancer: current evidence, controversies, and future directions.

BACKGROUND: Pelvic lymph node dissection (PLND) remains controversial in the management of prostate cancer. Although it provides the most accurate pathological staging, its therapeutic value beyond staging has long been debated due to conflicting evidence and concerns regarding procedure-related morbidity. OBJECTIVE: To critically evaluate the contemporary role of PLND, particularly extended pelvic lymph node dissection (ePLND), in prostate cancer management in the context of modern imaging, risk stratification tools, and evolving oncologic endpoints. EVIDENCE ACQUISITION: A narrative review of recent literature was conducted, focusing on high-level evidence including randomized trials, observational studies, and contemporary guideline recommendations addressing the indications, extent, oncologic outcomes, and complications of PLND. EVIDENCE SYNTHESIS: Recent randomized and observational studies suggest that ePLND improves nodal staging accuracy and may be associated with modest improvements in metastasis-free survival (MFS) in selected patients with intermediate- and high-risk prostate cancer, although the absolute benefit remains limited and causality is not definitively established. Advances in molecular imaging, particularly prostate-specific membrane antigen (PSMA) PET/CT, together with multiparametric MRI, validated nomograms, and emerging genomic classifiers, now allow more precise identification of patients most likely to benefit from ePLND. The integration of these tools supports a more individualized surgical strategy, including image-guided and sentinel lymph node approaches designed to maximize staging accuracy while minimizing unnecessary dissection. CONCLUSIONS: In the contemporary PSMA imaging era, ePLND continues to play an important role in nodal staging and may contribute to improved oncologic outcomes in carefully selected patients.

Humans↗

PubMed2025

Enhanced fracture detection on radiographs with AI assistance for clinicians: a systematic review and meta-analysis.

BACKGROUND: Emergency radiographic interpretation for fractures is prone to missed or misdiagnoses. Artificial intelligence (AI) is expected to become a powerful tool to assist clinicians in fracture detection. PURPOSE: A systematic review and meta-analysis was performed to assess whether AI improves clinicians' ability to detect fractures on radiographs. MATERIALS AND METHODS: A literature search was conducted in PubMed, Web of Science, and Cochrane Library for studies published between January 1, 2010, and October 10, 2025. A meta-analysis of diagnostic accuracy studies was performed using a Summary Receiver Operating Characteristic (SROC) curve. The quality of included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool. Subgroup analysis and meta-regression were conducted to explore potential sources of heterogeneity. RESULTS: A total of 26 studies were included . The pooled sensitivity of clinicians increased from 77% (95% CI: 72-81) to 87% (95% CI: 83-90) with AI assistance, while the pooled specificity improved from 88% (95% CI: 85-90) to 92% (95% CI: 89-94). The corresponding AUC values were 0.90 (95% CI: 0.87-0.92) before and 0.95 (95% CI: 0.93-0.97) after AI assistance. Eight studies were rated as high risk of bias. Subgroup analysis and meta-regression identified potential sources of heterogeneity, including fracture location, AI model type, high risk of bias, and reference standards. CONCLUSION: AI assistance significantly improves clinicians' diagnostic performance in detecting fractures on radiographs for extremity and trunk fractures.

Humans↗

PubMed2026

How prevalent is fear of cancer recurrence beyond 5 years: a systematic review of validated assessments across tumour types.

PURPOSE: Fear of cancer recurrence (FCR) is an established challenge for cancer survivors. Research however has largely focussed early in treatment, with varying assessments and often single tumour sites. This systematic review set out to determine prevalence of FCR in survivors beyond 5 years across all tumour types. METHOD: We designed a search strategy to identify publications assessing FCR in survivors beyond 5 years with sample size greater than 50, using validated measures. Applying PRISMA methodology and with defined inclusion and exclusion criteria two authors independently assessed the studies for eligibility. Data extraction recorded number of participants, tumour type, study design, FCR tool, time points for assessment and reported prevalence. Risk of bias was assessed to address quality. RESULTS: Ten papers were included, reporting FCR from 5 years to beyond 20 years. Validated tools employed were FCRI-SF and FOP-Q-SF. Sample sizes ranged from 64 to 5983 participants, with a heterogeneous mix of tumour types and age. Only two studies reported longitudinal measurements. Prevalence of FCR above defined threshold ranged from 13 to 33.9% for those studies with acceptable risk of bias reporting distinct cohorts beyond 5 years. CONCLUSION: The limited evidence suggests that clinically relevant FCR persists in some survivors at 5 years. Our review demonstrates the challenge of heterogeneous patient populations in FCR research emphasising the need for improved consensus on measurements and more prospective longitudinal research representing a comprehensive variety of tumour types. We address the clinical implications of persistent FCR and the need to implement effective interventions.

Humans↗

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

A narrative systematic review of definitions and diagnostic criteria for disordered eating and eating disorders in type 1 diabetes.

AIMS/HYPOTHESIS: Type 1 diabetes and disordered eating (T1DE) affects 8-37.1% of adults and is associated with high rates of morbidity and mortality. The absence of a standardised case definition of T1DE and its severity hinders effective screening, diagnosis and treatment. This systematic review aimed to (1) synthesise existing case definitions and diagnostic criteria for T1DE in adults and (2) identify key characteristics to inform consensus for future diagnostic criteria. METHODS: A systematic review was conducted following the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) guidelines. Eligible studies involved adults (≥18 years) with type 1 diabetes assessing disordered eating; paediatric studies, mixed samples without disaggregated data, non-empirical designs and non-English publications were excluded. PubMed, MEDLINE, EMBASE, CINAHL and PsycINFO were searched up to November 2025 for peer-reviewed studies involving adults with T1DE. Qualitative and quantitative data on definitions, diagnostic criteria and assessment tools were extracted. Study quality was appraised using a modified Graphical Appraisal Tool for Epidemiological studies (GATE) checklist. Due to heterogeneity of data, a narrative synthesis of findings was performed to describe current definitions of T1DE. RESULTS: Sixty-one studies met the inclusion criteria, with a pooled sample of 111,208 participants (76% women) from over 22 countries. T1DE was defined using a heterogeneous array of terms, diagnostic frameworks and assessment tools (29 distinct methods). The Diabetes Eating Problem Survey-Revised (DEPS-R) was the most used questionnaire, but many studies relied on criteria adapted from general eating disorder classifications or generic questionnaires. Approximately three-quarters of the studies assessed insulin omission behaviours, but the operationalisation of the cognitions for insulin omission varied widely. Beyond physiological markers such as HbA1c and BMI, studies explored various diabetes-related and psychological constructs, although often considering diabetes and disordered eating separately rather than as an integrated condition. CONCLUSIONS/INTERPRETATION: This systematic review highlights the lack of a unified, evidence-based definition of T1DE, resulting in inconsistent screening, diagnostic and reporting practices. Establishing clear, consistent, evidence-based diagnostic criteria and screening questionnaires for T1DE is critical to improving early detection and developing targeted interventions. These findings provide a foundation for refining T1DE definitions as a stepping stone to an international consensus definition. STUDY REGISTRATION: PROSPERO registration no. CRD420250223622 FUNDING: King's College London and King's College Hospital through the KMRT KCH Joint Research Committee studentship. This work was also conducted as part of the National Institute for Health Research (NIHR; CS-2017-17-023)-funded STEADY project (Safe management of people with Type 1 diabetes and EAting Disorders studY). NZ's salary was part-funded by the NIHR via the NIHR Clinician Scientist award to MS; JT and KI are part-funded by the NIHR Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London. MS was funded through her NIHR Clinician Scientist Fellowship (CS-2017-17-023).

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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.

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PubMed2026

The future of pediatric vesicoureteral reflux management.

BACKGROUND AND OBJECTIVE: Vesicoureteral reflux (VUR) is a common condition in pediatric urology, yet important uncertainties persist regarding risk stratification, imaging strategies, and prevention of long-term renal damage. Emerging technologies may help address these challenges. This review provides a forward-looking overview of recent advances in artificial intelligence (AI) and immunomodulation that may influence future management of pediatric VUR. METHODS: A forward-looking literature review was performed using the PubMed database (January 2000-March 2025), focusing on studies addressing AI, immunomodulation, or vaccination in the context of VUR and urinary tract infections. Criteria of inclusion were the relevance to pediatric VUR, the novelty of the proposed concept, the potential clinical implications and, for the AI literature, the existence of a clinical evaluation of the algorithm on a dataset from patients. KEY FINDINGS AND LIMITATIONS: AI-based models show promising performance in supporting clinical decision-making, including prediction of the need for voiding cystourethrography, automated grading of VUR, estimation of recurrent urinary tract infection risk and prediction of chemoprophylaxis. These tools may facilitate more individualized diagnostic and therapeutic strategies, although current evidence is largely retrospective and requires prospective validation. Immunization and immunomodulatory approaches aim to reduce infection burden and modulate inflammatory pathways associated with renal scarring. While early experimental and adult clinical data are encouraging, pediatric-specific evidence remains limited, and clinical applicability in children with VUR is not yet established. CONCLUSION: Artificial intelligence and immunologically targeted strategies represent complementary, emerging approaches that may contribute to more personalized management of pediatric VUR. At present, both should be regarded as exploratory tools whose clinical impact will depend on further validation and appropriately designed pediatric studies.

Humans↗

PubMed2026

Risk prediction models for blood transfusion in patients undergoing total hip and knee arthroplasty: a systematic review and meta-analysis.

OBJECTIVE: To systematically review and evaluate published risk prediction models for perioperative blood transfusion in patients undergoing total hip or knee arthroplasty (THA/TKA). METHODS: We systematically searched PubMed, Web of Science, the Cochrane Library, and Embase from inception to May 31, 2025. Two researchers independently screened the literature, extracted data, and assessed the risk of bias and applicability using the Prediction model Risk Of Bias Assessment Tool (PROBAST). The area under the receiver operating characteristic curve (AUC) values were pooled via a meta-analysis using Stata 18.0. RESULTS: d Fourteen studies containing 36 prediction models were included. The incidence of blood transfusion among THA/TKA patients ranged from 3.2% to 30.8%. Preoperative hemoglobin (Hb) level, tranexamic acid (TXA) use, operative duration, intraoperative blood loss, and age were the most frequently incorporated predictors. Model sensitivity ranged from 58% to 94.5%, and specificity ranged from 71.3% to 94%. Meta-analysis showed that the pooled AUC value of the 13 validated models was 0.87 (95% CI: 0.85-0.90), suggesting good discriminatory performance. All models were rated as having a high risk of bias. The applicability of four studies was rated as unclear. CONCLUSION: Although the included studies demonstrated promising discriminative ability of prediction models for blood transfusion in THA/TKA, all were assessed as having a high risk of bias using the PROBAST tool. Therefore, future research should prioritize the development of models with larger sample sizes, rigorous study designs, and multicenter external validation.

Humans↗

PubMed2026

The Role of Artificial Intelligence for Intimate Partner Violence Prevention: A Systematic Review.

INTRODUCTION: Intimate partner violence (IPV), encompassing physical, sexual, emotional and economic abuse, remains a pervasive global health concern. Traditional prevention efforts face obstacles such as underreporting, delayed detection and limited personalised support. Emerging artificial intelligence (AI) approaches offer new opportunities to enhance IPV prevention. AIM: This systematic review maps and synthesises evidence on AI-driven tools in IPV prevention based on studies published between 2004 and 2024. METHODS: Following PRISMA 2020 guidelines and PROSPERO registration, we searched PubMed, Embase, CINAHL, PsycINFO, IEEE Xplore and Web of Science. Eligible studies explicitly evaluated AI technologies targeting IPV prediction, screening, intervention or support delivery. Study quality was appraised using the Mixed Methods Appraisal Tool (MMAT). RESULTS: Of 1304 records initially identified, 41 studies met eligibility criteria. AI applications ranged from machine learning (ML) for risk prediction and natural language processing (NLP) for IPV detection in clinical and social media data, to image analysis for forensic evaluation and chatbot-based support. Predictive modelling demonstrated strong discriminative performance, while NLP-based screening detected IPV with notable sensitivity. Chatbots showed feasibility and user acceptability, but evidence of their direct impact on reducing IPV incidence was limited, with one randomised controlled trial showing a modest reduction. Key challenges identified included algorithmic bias, data privacy risks and barriers to integration across health and social care systems. DISCUSSION: AI-informed interventions show promise for improving IPV detection, risk assessment, and scalable support, but questions remain about long-term effectiveness, ethical fairness, transparency and equitable implementation. Future interdisciplinary research should address these concerns to responsibly deploy AI in IPV prevention. RELEVANCE TO CLINICAL PRACTICE: The findings highlight the importance of trauma-informed, culturally responsive care and provider training in AI applications. Nurse-led innovation and policy advocacy will be crucial for safe, equitable integration of AI in IPV prevention.

Artificial Intelligence↗

PubMed2026

Assessing the Concurrent Validity of the Australian Treatment Outcomes Profile in a Methamphetamine Dependent Treatment-Seeking Population.

INTRODUCTION: The Australian Treatment Outcomes Profile (ATOP) is a brief clinical tool assessing substance use, health and well-being used in Australian alcohol and other drug treatment services. It is validated for use with clients using alcohol, opioids and cannabis, but not yet for clients who primarily use methamphetamine. METHODS: An embedded validation study was undertaken in treatment-seeking adults enrolled in a randomised double-blind placebo-controlled trial of lisdexamfetamine for methamphetamine dependence with sites in New South Wales, South Australia and Victoria. Participant demographics were collected during study screening. The ATOP and comparators (Time Line Follow Back, Opiate Treatment Index, Depression Anxiety Stress Scale, WHOQOL-BREF and Personal Wellbeing Index) were collected at baseline. Continuous ATOP items were analysed using Pearson's correlation coefficient, and dichotomous items were analysed using Fleiss's κ. Agreement was rated as strong where measures were ≥ 0.50, moderate where agreement was 0.30-0.49, and weak where < 0.30. RESULTS: One hundred and eighteen study participants (2018-2020) had data for concurrent validity analysis. Strong validity was demonstrated for physical health, psychological health, quality of life, injecting drug use and crime items, and for days of use for amphetamines, alcohol, cannabis and cocaine. There was weak validity for days of use for benzodiazepines. Heroin use days and other opioid use days were endorsed by fewer than five participants and were therefore unable to be assessed. DISCUSSION AND CONCLUSIONS: The ATOP is valid for use in a treatment-seeking methamphetamine-dependent population, expanding the range of tools for assessment and standardised outcome monitoring across different settings and services.

Humans↗

PubMed2026

Diagnostic accuracy of bronchoalveolar lavage fluid-based testing for pulmonary cryptococcosis: A systematic review and meta-analysis.

BACKGROUND: Pulmonary cryptococcosis(PC) presents diagnostic challenges because of its non-specific clinical and radiological manifestations. Bronchoalveolar lavage fluid (BALF)-based testing, which includes latex agglutination (LA) and lateral flow assay (LFA), offers a minimally invasive diagnostic method, yet its pooled diagnostic accuracy remains unclear. METHODS: We systematically searched PubMed, Embase, Cochrane Library, and Scopus from inception to May 2026. Studies evaluating BALF-based testing for PC with extractable 2 × 2 data were included. The methodological quality of relevant studies was assessed by the QUADAS-2 tool. Pooled sensitivity, specificity, likelihood ratios, and diagnostic odds ratio (DOR) were estimated using a bivariate random-effects model. Subgroup analyses were performed by testing method and reference standard type. Heterogeneity was evaluated through paired forest plots, HSROC visualization, and exploratory bivariate meta-regression. RESULTS: The pooled sensitivity was 0.87 (95% CI: 0.81-0.91), and the specificity was 0.99 (95% CI: 0.982 - 0.995). The pooled positive likelihood ratio (PLR) was 88.00 (95% CI: 47.39 - 163.42), the negative likelihood ratio (NLR) was 0.13 (95% CI: 0.09 -0.20), and the DOR was 658.50 (95% CI: 285.36-1519.55). No significant threshold effect or publication bias was detected. Exploratory meta-regression suggested a possible assay-method effect in the joint model (P = 0.03), mainly driven by specificity (P = 0.01). CONCLUSIONS: The study demonstrates the high accuracy of CrAg in BALF for the diagnosis of pulmonary cryptococcosis, supporting its role as an important adjunctive diagnostic tool, particularly when tissue biopsy is not feasible or rapid results are needed. Larger prospective studies with standardized protocols are needed to validate these estimates.

Humans↗

PubMed2026

The impact of artificial intelligence on critical thinking and clinical reasoning in health professions education: A systematic review and meta-analysis.

BACKGROUND: Critical thinking and clinical reasoning underpin healthcare professionals' ability to navigate uncertainties and deliver safe and effective care. With artificial intelligence (AI) advancement and growing adoption, AI-based educational tools are increasingly used to support these cognitive competencies' development. OBJECTIVE: To synthesize randomised and controlled clinical trials on AI-based educational tools in health professions education and examine their effects on critical thinking and clinical reasoning among health professions students. METHODS: Six electronic databases were searched from January 1, 2014 to July 28, 2025 was reviewed: PubMed, Cochrane Central Register of Controlled Trials, CINAHL, Scopus, Embase and Web of Science. Two independent reviewers performed data extraction and quality assessment using standardized JBI checklists. The GRADE approach was used to assess the certainty of evidence. Studies were pooled via random-effects meta-analyses or narrative syntheses. RESULTS: Fourteen randomised controlled trials and seven controlled clinical trials were included (n = 21). Meta-analyses revealed small to medium effect sizes for the surrogate clinical reasoning outcomes of performance-based assessment scores (SMD 0.68; 95% CI [0.38, 0.98], p-value = 0.00; I2 = 38%) and knowledge test scores (SMD 0.39; 95% CI [0.09, 0.69], p-value = 0.01; I2 = 79%). Critical thinking and clinical reasoning skills and dispositions were narratively synthesized, with majority of included studies favouring AI-based interventions but the evidence had low to very low certainty. CONCLUSION: AI-based educational interventions may improve critical thinking and clinical reasoning among health profession students, but the evidence is very uncertain. This review offers preliminary insights but does not allow identification of optimal interventions or discipline-specific recommendations due to small sample sizes and substantial intervention heterogeneity. Further research is required to draw definitive conclusions. PROTOCOL REGISTRATION: CRD42025634074.

Humans↗

PubMed2026

Meningioma methylation profiling as a complement to WHO grading: a single-center experience.

OBJECTIVE: The methylation profile of meningiomas is a promising predictive tool that may improve risk stratification beyond WHO grading. This study aimed to evaluate the clinical relevance and real-world applicability of routine epigenetic testing in meningioma management. METHODS: The authors retrospectively analyzed patients who underwent meningioma resection between January 2021 and December 2023. Histopathological grading (WHO 2021) and methylation profiling (methylation class [MC]) with the MethylationEPIC v1.0 (850k) chip were performed by an independent neuropathologist. RESULTS: A total of 106 patients were included; 81 tumors (76%) were classified as WHO grade 1, 20 (19%) as grade 2, and 5 (5%) as grade 3. Epigenetically, 55 tumors (52%) were classified as benign, 18 (17%) as intermediate, and 2 (2%) as malignant; 31 (29%) could not be classified. Discordances between WHO grading and methylation profiling were observed in 18 of 74 cases. Tumor board decisions were made after a median of 8 days postoperatively, guided by WHO grading; however, the epigenetic report was only available after a median of 23 days. During follow-up, 20 patients experienced tumor progression. Progression was significantly associated with the MC (r = -0.4, p < 0.001) and tumor volume (r = 0.4, p = 0.0005), but not with WHO grading (r = 0.17, p = 0.084). However, the relatively high rate of unclassified tumors and delayed result availability limited the direct impact of MC profiling on immediate clinical decision-making. Interestingly, progression-free survival in MC-unclassified tumors mirrored that of the intermediate group. CONCLUSIONS: Methylation profiling demonstrates superior predictive accuracy for meningioma progression and complements WHO grading, especially in identifying malignant meningiomas. However, its current clinical utility is constrained by technical and logistical limitations. In real-world practice, epigenetic classification should therefore be considered a complementary tool rather than a replacement for established histopathological assessment.

Humans↗

PubMed2026

Female genital mutilation knowledge, attitudes and training needs among health professionals in non-practicing countries: A literature review.

BACKGROUND: With increasing globalization and migration, the number of women affected by female genital mutilation who reside in countries where the practice is not traditionally performed is constantly increasing. Healthcare providers in these settings are required to address the complex health needs of this vulnerable population. We aimed to synthesize recent literature on their knowledge, preparedness, and educational background. METHODS: We conducted a systematic review across PubMed, Scopus and Embase, identifying papers published from January 2015 onwards, examining providers' knowledge, education and attitudes toward female genital mutilation in non-practicing countries. Both quantitative and qualitative observational studies were eligible. Given heterogeneity in study populations, outcome definitions, and assessment tools, findings were synthesized narratively. The review protocol was registered with the International Prospective Register of Systematic Reviews (CRD420251044761). FINDINGS: 1046 records were screened by title and abstract, and 140 full-text articles were assessed for eligibility. 31 studies met the inclusion criteria (23 quantitative, 8 qualitative). Many providers reported clinical experience with women affected by female genital mutilation, yet substantial variability was observed in knowledge, training, and attitudes. Gaps were particularly evident regarding legislation, World Health Organization classification, clinical guidelines, referral pathways, workplace protocols. Midwives and younger professionals tended to demonstrate higher knowledge levels. Training exposure ranged from 5% to 91%, and many participants perceived it as insufficient. Qualitative findings echoed these patterns, highlighting challenges in female genital mutilation classification, legal awareness, documentation systems, the impact of providers' cultural beliefs on care delivery. CONCLUSION: Considerable efforts are needed to equip healthcare providers to deliver high-quality, culturally competent care to women affected by female genital mutilation. Research should develop validated tools to assess preparedness, adopt mixed-methods strategies to capture patient and provider perspectives, and guide standardized, up-to-date training programs, strengthening knowledge in managing female genital mutilation.

Humans↗

PubMed2026

An automated geometric modeling framework in GATE for the design and optimization of high-sensitivity converging-beam SPECT collimators.

Objective.The trade-off between detection sensitivity and spatial resolution is a fundamental challenge in designing organ-dedicated Single-photon emission computed tomography (SPECT) collimators. While converging-hole geometries offer a solution, their optimization is often hindered by the lack of flexible computational tools capable of modeling large-scale, non-parallel hole arrays. This study aims to develop an automated geometric modeling framework to facilitate the design and evaluation of complex converging- and diverging-hole collimators within standard Monte Carlo environments.Approach.We developed a specialized modeling framework by implementing custom C++ classes and a vector-based alignment algorithm within GATE. This platform enables automated, orientation-consistent construction of large-scale converging arrays not natively supported by standard implementations. A high-sensitivity pure cone-beam collimator (CBC) was designed using this framework. The evaluation used hot-rod, disc, and Jaszczak phantoms for physical characterization, while XCAT and dedicated brain models were employed for clinical tasks, including cardiac, brain perfusion, and DaTscan SPECT simulations.Main results.The CBC achieved a nearly fourfold sensitivity increase compared to a conventional low-energy high-resolution parallel-hole collimator at a 20 cm radius of rotation, while maintaining comparable spatial resolution. Despite a 52.3% field of view reduction, the CBC yielded a 2.2-fold noise reduction (CV: 11.7% vs 25.9%) and mitigated partial volume effects via geometric magnification. XCAT and brain phantom simulations confirmed enhanced anatomical definition and contrast recovery in cardiac, perfusion, and DaTscan tasks.Significance.This work provides an efficient computational tool for rapid design space exploration of advanced collimator geometries. The results demonstrate that the proposed CBC design offers a significant sensitivity advantage, making it highly suitable for high-performance, small-volume clinical applications such as brain and cardiac molecular imaging.

Tomography, Emission-Computed, Single-Photon↗

PubMed2026

Use of wearable technologies for physical activity promotion in older adults: A systematic review.

This systematic review, conducted according to PRISMA guidelines and registered in PROSPERO (CRD420251055299), examined the use of wearable technologies for promoting physical activity (PA) in adults aged 60 years and older. Searches across five databases (PubMed, Scopus, Web of Science, CINAHL, Cochrane) identified 2438 records, of which only six randomized controlled trials published between 2021 and 2025 met inclusion criteria, with sample sizes ranging from 36 to 551 participants and mean ages between 65 and 79 years. Given the small number of included studies, findings should be interpreted as preliminary. The studies ranged from the standalone use of commercial trackers (Fitbit, Polar, ActiGraph) to multicomponent interventions combining wearables with physiotherapist feedback, telephone counseling, web-based platforms, or interactive cognitive-motor training. Wearables used alone, as in the REACT trial, produced small or non-significant PA effects. In contrast, interventions integrating devices with personalized feedback, professional support, or digital platforms, such as PROMOTE and TASMANIA, were associated with more consistent improvements in PA, physical function, and cognitive outcomes. Multicomponent programs, such as PEER and ICMT, reported broader benefits, including cognition, balance, and reductions in sedentary behavior, though these findings derive from individual trials and require replication. Risk of bias, assessed with the Cochrane Risk of Bias tool version 2 (RoB 2.0), was rated as "some concerns" for five studies and low for only one, mainly due to gaps in randomization reporting, missing data, and lack of preregistration. Tentatively, and based on a very limited evidence base, wearables may have greater impact when embedded within broader behavioral systems, incorporating feedback, coaching, or interactive components, rather than when used in isolation as passive monitoring tools. Adherence and psychosocial outcomes appeared related to comfort and perceived usefulness among older adults, though larger and more robust trials are needed to confirm these patterns.

Humans↗

PubMed2026

Artificial intelligence in genitourinary oncology: publication trends and systematic review.

OBJECTIVE: To conduct an analysis of publication trends and a systematic review of randomized controlled trials (RCTs) to characterize the current state of artificial intelligence (AI) use in genitourinary (GU) oncology, as AI has emerged as a transformative tool in healthcare with potential applications in diagnostics, treatment planning, and prognostication. METHODS: We searched the Medical Literature Analysis and Retrieval System Online (MEDLINE), Excerpta Medica dataBASE (EMBASE; Ovid), and Cumulative Index to Nursing and Allied Health Literature (CINAHL) Ultimate for studies related to AI and GU oncology, excluding non-English papers, non-human studies, review articles, and articles using AI solely for manuscript writing. Publication trends were analysed from 2013 to 2023 and categorized by study design and cancer type. RCTs were evaluated through systematic review using Covidence (Veritas Health Innovation Ltd, Melbourne, Victoria, Australia) for screening and data extraction. Two reviewers independently assessed all studies, with risk of bias (RoB) evaluated using the Cochrane RoB 2.0 tool. RESULTS: Of 2409 articles identified, 1220 met inclusion criteria. These included 962 retrospective articles, 175 prospective studies, 79 studies with combined retrospective/prospective methods, and four RCTs. Studies most commonly addressed prostate (n = 923), renal (n = 274), and urothelial (n = 194) cancers. Publications grew from 14 in 2013 to 362 in 2023, with substantial acceleration in 2019. Four RCTs were identified - one in urothelial cancer and three in prostate cancer. Two RCTs evaluated AI-based diagnostics, demonstrating improved performance over conventional methods; the remaining two RCTs evaluated AI in prognostication and treatment planning, showing improved gains in imaging interpretation and operational efficiency. RoB varied across studies, primarily related to randomisation and deviations from intended interventions. CONCLUSIONS: Artificial intelligence research in GU oncology has grown, although high-level evidence from RCTs remains limited. Existing trials underscore AI's promise in diagnostics, prognostication, and treatment planning, and the rapidly evolving nature of this field warrants continued prospective investigation.

Humans↗

PubMed2026

The musculoskeletal pain literacy questionnaire (MSK-PLq) - Part 1: Development of a preliminary version through a systematic review and Delphi consensus.

OBJECTIVE: Chronic musculoskeletal (MSK) pain is a leading cause of disability worldwide, and self-management is a first-line approach recommended by international clinical guidelines. Access to evidence-based information that enhances health literacy may support patients' engagement in their self-management and treatment decision-making, potentially reducing disease burden and pain. However, no tool currently exists to assess health literacy specifically in MSK pain. This study aimed to develop and describe the preliminary version of a knowledge-based questionnaire to evaluate MSK pain literacy, the Musculoskeletal Pain-Literacy questionnaire (MSK-PLq). METHODS: A systematic literature review identified existing health literacy instruments and generated a preliminary list of domains. A two-round Delphi study with 22 panellists (19 experts and three people living with chronic MSK pain), followed by consensus meetings, was used to refine domains and items (≥70% agreement). Readability was assessed using the Flesch Reading Ease (FRE) score and three stakeholders were consulted to review the questionnaire for comprehensibility, clarity, and face validity. RESULTS: Six domains were retained (Understand, Access, Appraise, Apply, Digital, Beliefs), comprising 20 items in the preliminary version of MSK-PLq. Readability was acceptable (mean FRE 74, indicating fairly easy reading), and subject feedback supported the questionnaire's clarity and face validity. CONCLUSIONS: The preliminary version of the MSK-PLq is proposed as the first knowledge-based tool to assess functional, interactive, and critical aspects of MSK pain literacy. It may have applications in clinical practice, research, education, and digital health, by informing tailored patient education and supporting self-management strategies, although further psychometric validation is required.

Humans↗