Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Clinical high risk”

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

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

2,121 records · Page 6Linked to original sources
PubMed2026

Frequent readmissions after hospitalization for alcohol withdrawal: a systematic review and meta-analysis.

BACKGROUND: Alcohol use disorder and alcohol withdrawal syndrome impose substantial clinical and economic burdens, with repeated hospitalizations being common. We aimed to systematically review readmission rates following inpatient detoxification, assess variation across study designs and hospital settings, and identify key risk and protective factors. METHODS: We performed a literature search in Embase and Pubmed on 10/04/2026 focusing on studies assessing in hospital alcohol detoxification. Exclusion criteria included studies on substance use other than alcohol and outpatient or residential treatment. Main outcome was rehospitalization, and meta-analysis was performed to estimate pooled readmission proportions. Secondary outcomes were risk factors and protective factors influencing the rate of rehospitalization. RESULTS: Twenty-five studies were included. The pooled proportion of readmissions following alcohol detoxification was estimated at 17% (95% CI: 14%-21%; 13 studies, n = 287,896) within 1 month, increasing to 44% (95% CI: 36%-52%; 8 studies, n = 2,877) at 1 year. Substantial between-study heterogeneity was observed. Subgroup analyses found no significant differences by hospital setting or time period. Findings for study aim and study design were mixed and based on limited data A small number of studies suggested associations with housing stability, employment, and treatment engagement. CONCLUSIONS: This meta-analysis suggests that approximately one in six patients are readmitted within 1 month and nearly half within 1 year after inpatient alcohol detoxification. However, readmission rates varied considerably across settings and populations. Future research should evaluate targeted interventions to reduce readmissions among high-risk patient groups.

Humans↗
PubMed2026

Predicting ACL injury risk in athletes: A systematic review of machine learning-based models.

BACKGROUND: Early ACL injury risk identification in athletes is essential. This systematic review examines machine learning (ML) models for predicting ACL injuries, evaluating their methodological quality, performance, and reliability. METHOD: A comprehensive electronic search was conducted across PubMed, Scopus, Web of Science, and IEEE Xplore databases, supplemented by Google Scholar for grey literature, covering articles published between January 1, 2015, and August 30, 2025. Eligible studies were appraised using the Prediction Model Study Risk of Bias Assessment Tool (PROBAST) for methodological quality and risk of bias, and the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) guidelines for quality of evidence. RESULTS: Ten studies were included. PROBAST showed eight studies had moderate risk of bias and two low risk. TRIPOD found only two studies met quality criteria. ML models included logistic regression (n = 5), support vector machines (n = 4), k-nearest neighbor (n = 3), decision trees (n = 3), random forests (n = 5), neural networks (n = 2), linear discriminant analysis (n = 1), and pre-trained CNNs (n = 1). AUC ranged from 0.63 to 0.98. Accuracy (reported in six studies) ranged from 26% to 95%; however, these values should be interpreted with caution due to the absence of confidence intervals, lack of class imbalance handling, and limited external validation across studies. Tree-based ensemble methods such as random forest achieved competitive accuracy (74-86%), while SVM, a non-ensemble classifier, reported accuracy ranging from 71% to 95%; however, the highest values were obtained in studies with notably small sample sizes (n = 12 to n = 39), raising concerns about overfitting and generalizability. CONCLUSION: Current ML algorithms show promise for identifying athletes at high ACL injury risk and detecting relevant risk factors. Although study quality was generally satisfactory, future research should prioritize external validation and model interpretability to support clinical translation.

Humans↗
PubMed2026

Systematic review of machine learning approaches for predicting sickle cell crisis and mortality risk at the climate-health nexus.

BACKGROUND: Sickle cell anemia (SCA) is a severe genetic blood disorder characterized by recurrent vaso-occlusive crises and increased mortality, with the greatest burden occurring in low- and middle-income countries. Climatic and environmental conditions, including temperature variability, humidity, rainfall, air pollution, and seasonal changes, have been associated with disease exacerbation. However, the extent to which these factors have been incorporated into predictive models remains unclear. This study systematically reviews the application of machine learning (ML) models for predicting SCA crises and mortality in relation to climate and environmental factors. METHODOLOGY: The PRISMA guidelines were used, and 34 peer-reviewed studies published between 2005 and 2026 were analyzed to identify the climate variables, ML approaches employed, and predictive performance. The reviewed studies applied a range of ML techniques, including artificial neural networks, random forests, support vector machines, decision trees, logistic regression, and deep learning models. Temperature, humidity, rainfall, wind speed, air quality indicators, and seasonal patterns were the most frequently examined environmental variables. RESULTS: The findings indicate that most existing models rely predominantly on clinical and demographic data, with limited integration of climate information and inadequate representation of high-burden regions, especially Sub-Saharan Africa. Studies incorporating environmental variables reported improved predictive performance and highlighted the potential of climate-informed early warning systems for SCA management. CONCLUSION: The review recommends development of interdisciplinary, climate-aware ML frameworks, expansion of longitudinal environmental datasets, and increased research in underrepresented regions to support climate-resilient and patient-centered SCA care.

Humans↗
PubMed2026

Atopic dermatitis and the risk of osteoporosis and fractures: a meta-analysis of cohort studies.

BACKGROUND: This meta-analysis aims to evaluate the risk of osteoporosis and fractures in patients with atopic dermatitis (AD) by synthesizing data from cohort studies. We also provide a comprehensive analysis of fracture risks across different severities of AD and anatomical sites. METHODS: Following the PRISMA 2020 guidelines, a systematic search was conducted in PubMed, Embase, and the Cochrane Library up to May 30, 2025. Studies that investigated the relationship between AD and osteoporosis or fractures were included in the analysis. Data extraction and screening were performed independently by two reviewers. Study quality was assessed using the Newcastle-Ottawa Scale (NOS). A random-effects meta-analysis was applied, alongside sensitivity and subgroup analyses. Publication bias was evaluated using funnel plots and Egger's test. RESULTS: Ten cohort studies, involving 368 to over 2 million AD patients, were included. NOS scores ranged from 7 to 8, indicating generally high study quality. The pooled analysis revealed a 56% increased risk of osteoporosis (OR = 1.56, 95% CI: 1.14-2.13; I2&#xa0;=&#xa0;99.9%, p&#x2009;<&#x2009;0.0001) and an 8% increased risk of all-cause fractures (OR = 1.08, 95% CI: 1.05-1.10; I2&#xa0;=&#xa0;82.1%, p&#x2009;<&#x2009;0.0001) in AD patients. Subgroup analyses demonstrated a progressive increase in fracture risk with the severity of AD. Specific risks were significantly higher for vertebral fractures (OR = 1.14, 95% CI: 1.08-1.20; I2&#xa0;=&#xa0;67.3%, p&#x2009;=&#x2009;0.009) and lower limb fractures (OR = 1.11, 95% CI: 1.08-1.13; I2&#xa0;=&#xa0;65.0%, p&#x2009;=&#x2009;0.014). Sensitivity analyses confirmed the robustness of these findings, and no significant publication bias was detected (p&#x2009;=&#x2009;0.316). CONCLUSION: AD is associated with an increased risk of osteoporosis and fractures, particularly among patients with severe AD and those experiencing vertebral or lower limb fractures. These findings highlight the importance of targeted bone health monitoring in the clinical management of AD patients.Registration: (PROSPERO: CRD420251066550).

Humans↗
PubMed2026

A Dynamic Nomogram to Predict Metabolic Dysfunction-Associated Fatty Liver Disease in Patients with Metabolic Syndrome.

BACKGROUND: Metabolic syndrome (MetS) involves multiple metabolic disorders. This study aimed to identify high-risk populations for metabolic dysfunction-associated fatty liver disease (MAFLD) in patients with MetS and to establish a dynamic predictive nomogram. METHODS: A total of 627 patients with MetS from six regions in Zhejiang Province were enrolled and categorized into MAFLD and non-MAFLD groups, then randomly assigned to training and validation sets at a ratio of 7:3. Independent predictors of MAFLD were identified using least absolute shrinkage and selection operator regression and multivariable logistic regression analyses. These predictors were then used to construct a dynamic nomogram. RESULTS: A total of 627 patients with MetS were included in the final analysis, of whom 77.0% (483/627) were diagnosed with MAFLD. Multivariable logistic regression analysis identified body mass index (BMI), waist circumference (WC), total cholesterol (TC), alanine aminotransferase (ALT), MetS-defined dysglycemia, and education level as independent risk factors for MAFLD. MetS-defined dysglycemia showed the highest odds ratio (OR) for MAFLD development [OR = 1.87, 95% confidence interval (CI): 1.07-3.29]. Although the number of MetS components and the metabolic syndrome score were significantly associated with MAFLD in univariate analysis, they were not independently associated with MAFLD in the multivariate model. A dynamic nomogram for predicting MAFLD risk in patients with MetS was developed and internally validated. The area under the receiver operating characteristic curve was 0.834 (95% CI: 0.787-0.880) in the training set and 0.839 (95% CI: 0.771-0.899) in the validation set, indicating strong predictive performance. Bootstrap internal validation demonstrated good agreement between predicted and observed outcomes in calibration curves. Decision curve analysis further indicated favorable clinical applicability of the nomogram. CONCLUSION: BMI, WC, TC, ALT, MetS-defined dysglycemia, and education level are independent risk factors for MAFLD. A dynamic nomogram for predicting MAFLD risk in patients with MetS was successfully developed and validated.

Humans↗
PubMed2026

Diagnostic Performance of Machine Learning for Systemic Lupus Erythematosus: Systematic Review and Meta-Analysis.

BACKGROUND: Early and accurate diagnosis of systemic lupus erythematosus (SLE) and its organ involvement is essential. Previous reviews of machine learning (ML) in SLE combined heterogeneous tasks and validation strategies and may have overinterpreted model performance. OBJECTIVE: This study evaluated the diagnostic performance of ML and deep learning (DL) models for 3 clinically distinct SLE-related tasks: SLE classification or diagnosis, lupus nephritis (LN) diagnosis, and neuropsychiatric systemic lupus erythematosus (NPSLE) discrimination. We also assessed methodological quality and certainty of evidence. METHODS: PubMed, Embase, Cochrane Library, Web of Science, and IEEE Xplore were searched from January 2014 to April 2026. Eligible peer-reviewed diagnostic accuracy studies developed or validated ML or DL models for 1 of the 3 prespecified tasks, used an accepted reference standard, and provided data for a 2&#xd7;2 contingency table. Bivariate random-effects meta-analyses with the Hartung-Knapp-Sidik-Jonkman adjustment were used to pool sensitivity and specificity. We reported 95% prediction intervals (PIs), assessed risk of bias using the Quality Assessment of Diagnostic Accuracy Studies for Artificial Intelligence tool (QUADAS-AI; Viknesh Sounderajah [Imperial College London]), and evaluated certainty of evidence using the Grading of Recommendations Assessment, Development, and Evaluation framework for diagnostic test accuracy. RESULTS: Twenty-nine studies were included: 17 for SLE classification, 5 for LN diagnosis, and 7 for NPSLE discrimination. In the primary task-stratified analysis, pooled sensitivity was 0.91 (95% CI 0.86-0.94; 95% PI 0.56-0.99), and pooled specificity was 0.94 (95% CI 0.91-0.96; 95% PI 0.69-0.99), with low heterogeneity (I&#xb2;=23.9% and 22.9%, respectively). DL models showed a sensitivity of 0.93 and specificity of 0.95, compared with 0.88 and 0.94 for traditional ML models. Certainty of evidence was high for most analyses but low for LN diagnosis because of inconsistency and imprecision. All studies were retrospective, and only 9 of 29 (31%) performed independent external validation. Overall risk of bias was high or unclear in 22 of 29 (75.9%) studies. No study reported model calibration, decision-curve analysis, or net clinical benefit. CONCLUSIONS: ML models showed promising diagnostic accuracy across 3 distinct SLE-related tasks, but wide PIs, limited external validation, and pervasive risk of bias restrict conclusions about real-world generalizability. Prospective multicenter studies with standardized tasks and reference standards, independent external validation, and formal assessment of calibration and clinical utility are required before clinical implementation.

Humans↗
PubMed2026

The hidden threat from food-derived carbon dots: Formation, biodistribution, and potential health risks.

Food-derived carbon dots (CDs) are a new class of carbon-based nanoparticles generated during the thermal processing of food matrices. These nanomaterials have been extensively studied for their unique fluorescence, good biocompatibility, and tunable surface chemistry in food detection, intelligent packaging, and biomedical applications. However, their nanoscale size and high surface activity have raised safety concerns regarding biological interactions, in vivo biodistribution, and potential long-term health hazards. Although CDs have traditionally been regarded as low-toxicity materials due to their favorable biocompatibility, the potential hidden risks of CDs have not received sufficient attention. CDs exhibit dose-dependent toxicity, not only accumulating in various tissues and organs but also potentially inducing oxidative stress and interfering with cellular metabolic functions. Therefore, this review summarizes the advances in sources, synthetic strategies, and core properties of CDs, with a special focus on in vivo biological interactions, fates, and potential safety challenges. In addition, it is proposed that the standardized detection and risk assessment system should be established to further explore the long-term health effects of CDs under real dietary exposure, thereby ensuring their safety and sustainable application.

Carbon Quantum Dots↗
PubMed2026

Three-Dimensional Fracture Mapping of the Terrible Triad of the Elbow: Morphological Characteristics and Clinical Implications.

BACKGROUND: The morphology of fractures in the terrible triad of the elbow (TTE) is complex, and precise management relies on a profound understanding of this morphology. This study aims to systematically analyze, for the first time, the distribution and morphological characteristics of TTE fracture lines using three-dimensional (3D) imaging technology. METHODS: Clinical data and thin-slice CT scans of 112 patients with TTE from January 2021 to December 2024 were retrospectively included. 3D fracture models were reconstructed using Mimics software. Virtual reduction and standardized alignment were performed using 3-matic software. Fracture lines were mapped onto standard ulnar and radial templates, and 3D fracture heat maps were generated using the E-3D software to demonstrate the high-frequency distribution zones of the fracture lines visually. Statistical analysis was performed using SPSS software (version 21.0, IBM Corp., Armonk, NY, USA). Continuous variables were compared using one-way analysis of variance (ANOVA), and categorical variables were compared using the chi-square test (&#x3c7;2 test). A two-tailed p&#x2009;<&#x2009;0.05 was considered statistically significant. RESULTS: The study revealed distinct patterns in the distribution of TTE fracture lines. In the coronoid process, the fracture "hot zone" presented as an annular high-density band extending from the lateral middle aspect to the tip. In the radial head, an oblique high-density band was observed in the anterolateral quadrant of the articular surface. The radial neck exhibited a circumferential high-density zone, which was most prominent in the anterolateral aspect. Statistical analysis indicated a significant correlation between age and fracture complexity; the proportion of Regan-Morrey type III coronoid fractures and Mason type III radial head fractures was significantly higher in elderly patients (>&#x2009;60&#x2009;years) (p&#x2009;<&#x2009;0.05), suggesting that advanced age is a significant risk factor for complex fractures. CONCLUSION: This study is the first to visually reveal the Collaborative Distribution Patterns of TTE fracture lines using 3D fracture mapping technology. This model provides morphological evidence for understanding the injury mechanism of TTE and offers an anatomical framework that may assist surgeons in individualizing surgical approaches and fixation strategies.

Humans↗
PubMed2026

Meaning in Life in Palliative Cancer Care: Psychosocial and Existential Outcomes-A Systematic Review.

BackgroundExistential distress, marked by hopelessness, loss of meaning, and spiritual suffering, is prevalent among patients with advanced illness, and is associated with psychological burden and a wish to hasten death (WTHD).PurposeThis systematic review aimed to synthesize current evidence on meaning in life (MIL) in adult palliative care (PC) populations, focusing on its associations with quality of life (QOL), mental health, existential and spiritual well-being (SWB), and WTHD.MethodsMEDLINE, Web of Science, Scopus, and the Cochrane Library were searched for eligible studies (English, 2016-2024) involving adult cancer patients receiving PC. MIL was examined as a central intervention component or outcome. Risk of bias was assessed: findings were synthesized narratively. The review was registered in PROSPERO.ResultsEight studies (n&#x2009;=&#x2009;1733 participants) were included: four cross-sectional, two randomized controlled trials, one longitudinal observational study, and one qualitative study. Several studies had small samples and substantial attrition. Risk of bias was high (n&#x2009;=&#x2009;7), and moderate in one cross-sectional study. MIL was inversely associated with depression, anxiety, demoralization, and WTHD; and positively associated with QOL and SWB. MIL may also mediate psychological outcomes (eg, purpose, coherence, and personal values). However, heterogeneity in MIL conceptualization and measurement, combined with low methodological quality, limited comparability and certainty of findings.ConclusionMIL may be relevant to psychosocial/existential outcomes in PC. Conclusions are constrained by a small and methodologically weak evidence base. Further high-quality, longitudinal research is needed before MIL-centered interventions can be recommended for routine clinical practice.

Humans↗
PubMed2026

The Effect of Breastfeeding on Cervical Dysplasias.

OBJECTIVE: This study aimed to investigate the relationship between breastfeeding and precancerous cervical lesions. MATERIALS AND METHODS: A case control study was conducted at a tertiary training and research hospital between September 1 and November 1, 2023. A total of 168 patients who attended the gynecology outpatient clinic and reported their breastfeeding experiences were included. Patients with abnormal cervical cytology formed the study group (n = 37), while patients with normal cytology formed the control group (n = 131). Breastfeeding duration and patterns were compared between groups. RESULTS: The control group had normal smear results. In the study group, 15 patients had high-grade squamous intraepithelial lesions, and 22 patients had low-grade squamous intraepithelial lesions. Human papillomavirus (HPV) was positive in 54.1% of the study group versus 9.2% of the control group. The mean breastfeeding duration was shorter in the study group (9.18 &#xb1; 3.43 months) than the control group (23.6 &#xb1; 3.35 months; p < 0.05). Most control group patients breastfed for 13-36 months (35.1%), while most study group patients breastfed for <6 months (48.6%; p < 0.05). Shorter breastfeeding (<6 months) and HPV positivity were the strongest predictors of abnormal cytology. Breastfeeding <6 months increased the risk 9.883-fold compared with >36 months, while HPV positivity increased the risk 27.612-fold. CONCLUSION: Breastfeeding and longer breastfeeding duration appear to be associated with a lower risk of cervical intraepithelial neoplasia. Given its multiple health benefits, including prevention of gynecological cancers, promoting breastfeeding through public health policies is strongly recommended. Early recognition and prevention of precancerous lesions remain essential to reducing the risk of cervical cancer.

Humans↗
PubMed2026

Optimising Exercise Prescription: A Meta-Analysis Examining the Dose Response of Exercise Duration on Cardiorespiratory Fitness Following HIIT and MICT.

BACKGROUND: High-intensity interval training (HIIT) is often promoted as a time-efficient alternative to moderate-intensity continuous training (MICT) for improving cardiorespiratory fitness, yet the duration of HIIT sessions varies considerably across studies. OBJECTIVE: We aimed to characterise the dose-response relationship between exercise session duration and the improvement in cardiorespiratory fitness for HIIT and MICT. METHODS: A dose-response meta-analysis of randomised controlled trials comparing exercise duration in HIIT and MICT, following Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines and registered in PROSPERO (CRD42022335590). Effect sizes were calculated using a random-effects meta-analysis. The primary outcome was maximal oxygen uptake (VO2max). Secondary outcomes included blood pressure, lipid profiles, glucose metabolism markers and body composition measures. A one-stage random-effects dose-response meta-analysis was performed to examine the relationship between exercise duration and adaptations. We searched PubMed and Google Scholar; eligibility criteria for selecting studies were randomised controlled trials in humans, published in English and exercise interventions lasting at least 4&#xa0;weeks. RESULTS: We identified 69 randomised controlled trials (2387 participants). High-intensity interval training elicited greater improvements in VO2max than MICT (d = 0.38, 95% confidence interval 0.27-0.49, p < 0.001). High-intensity interval training demonstrated a non-linear dose-response relationship between exercise session duration and VO2max, with 80% of maximal effect (changes in VO2max = 3.45&#xa0;mL/kg/min) achieved with only ~11&#xa0;min/session (95% confidence interval 9.5-40.2). Moderate-intensity interval training showed a linear dose-response relationship between exercise session duration and VO2max, requiring ~52&#xa0;min/session to achieve 80% of the&#xa0;maximal observed&#xa0;effect (95% confidence interval 30.4-55.8). The dose-response relationship was consistent across populations. High-intensity interval training and MICT had comparable effects in improving cardiometabolic risk factors. CONCLUSIONS: High-intensity interval training demonstrated a non-linear dose response, with 80% of maximal effect on VO2max in ~11&#xa0;min/session, whilst MICT required four to five times longer to reach similar responses. The different types of training had comparable effects on cardiometabolic risk factors.

Journal Article↗
PubMed2026

ESC quality indicators for post-myocardial infarction care: transition and chronic coronary syndrome phases.

AIMS: We aimed to develop the European Society of Cardiology (ESC) quality indicators (QIs) for myocardial infarction (MI), from 1 year after hospital discharge, corresponding to transition to the chronic coronary syndrome phases. METHODS AND RESULTS: We collaborated with the European Association of Preventive Cardiology (EAPC) and developed QIs for the long-term management of patients following MI. We applied the ESC methodology for QI development by (i) determining key domains of post-MI care; (ii) developing candidate QIs by performing a systematic review of the literature, and (iii) selecting the final set of QIs using a modified Delphi approach. In total, 18 QIs were identified across seven domains of care including (i) structural framework, (ii) risk assessment and follow-up, (iii) pharmacological management, (iv) rehabilitation, behavioural, and preventive interventions, (v) coronary revascularization, (vi) clinical outcomes, and (vii) patient-reported outcomes. CONCLUSION: We present the ESC QIs from 1 year after hospitalization for MI, to standardize and address gaps in care for this high-risk group. These QIs are supported by evidence from contemporary literature, endorsed by expert consensus, and aligned with the 2024 ESC guidelines on the management of chronic coronary syndromes. LAY SUMMARY: Measures to evaluate and improve the long-term management of patients following a heart attack are needed. In this paper, we identified key aspects of care that can help clinicians, decision-makers and patients improve the quality of care, from one year after a heart attack onwards, and help address inequalities and variations in clinical practice.

Humans↗
PubMed2026

Liver Cancer Risk and Incidence Attributable to Human Immunodeficiency Virus: A Meta-Analysis and Population-Attributable Modeling Study of Over 1.2 Million Individuals.

HIV-induced immune suppression and chronic inflammation elevate the risk of cancer progression. We conducted a systematic review and meta-analysis of studies published between January 1, 1984 and October 13, 2023 to assess the association between HIV infection and liver cancer. People living with HIV (PLHIV) had a higher risk (pooled relative risk&#x2009;=&#x2009;3.36, 95% CI: 2.72-4.15). The global PAF for HIV-attributed liver cancer was 1.43% in 2019, with a three-fold increase over the past 30&#x2009;years. The Asia-Pacific region recorded the second highest new cases of HIV-attributed liver cancer in 2019, and the highest age-standardized incidence rate (ASIR) in Eastern and Southern Africa. Particularly, the ASIR of HIV-attributed liver cancer increased rapidly in Eastern Europe and Central Asia, with the highest estimated annual percentage change reaching 22.98%. PLHIV have an increased risk and incidence of liver cancer. In regions with high burden of HIV-attributed liver cancer, it is essential to integrate prevention and effective treatment for HIV, viral hepatitis, alcoholic liver disease, nonalcoholic steatohepatitis, and liver cancer.

Humans↗
PubMed2026

No association between alcohol consumption and hip osteoarthritis: a diverse national analysis of 87,585 adults from the "All of Us" research program.

INTRODUCTION: Hip osteoarthritis (OA) is estimated to affect 62.6 million individuals by 2050. A probable link exists between alcohol use and hip OA. However, the results are inconsistent, and the relationship between alcohol and hip OA remains speculative. To address these gaps, this study aimed to utilize the diverse, nationally representative All of Us Research Program dataset to explore the association between alcohol consumption and hip OA. METHODS: This retrospective case-control study utilized data from the All of Us Research Program Controlled Tier Dataset v8. 17,517 hip OA cases and 70,068 controls were identified. A 1:4 case-to-control matching ratio was applied based on age and sex. Alcohol use frequency was categorized into five levels: Never, Monthly or Less, Two to Four Times per Month, Two to Three Times per Week, and Four or More Times per Week. Multivariable logistic regression models evaluated the association between alcohol use frequency and hip OA after adjusting for demographic and clinical variables. RESULTS: Multivariable analysis found that alcohol use frequency was not significantly associated with hip OA. Compared to never users, participants with low (OR 0.98, 95% CI 0.93-1.04, P&#x2009;=&#x2009;0.583), moderate (OR 0.99-1.01, all P&#x2009;>&#x2009;0.05), and high (OR 1.02, 95% CI 0.95-1.09, P&#x2009;=&#x2009;0.599) levels of alcohol consumption had no statistically significant differences in odds of hip OA. Female sex, Asian race, diabetes,&#xa0;hypertension, hyperlipidemia, and nicotine dependence increased the odds of hip OA. CONCLUSION: Any level of alcohol consumption was not significantly associated with the odds of hip OA. This study adds valuable insight to the current body of conflicting evidence. Further prospective studies appear warranted to shed light on the long-term effects of different alcoholic beverages on different joints. Key Points &#x2022; This study found no significant association between any degree of alcohol consumption and the odds of developing hip osteoarthritis. &#x2022; Utilizing data from 87,585 adults in the NIH "All of Us" Research Program, this is the first study to analyze this relationship in a large, nationally representative population. &#x2022; The research provides clarity to previously conflicting literature by demonstrating that alcohol lacks a clear harmful or protective effect on the clinical course of the disease. &#x2022; The analysis highlights that independent risk factors such as Asian race, nicotine dependence, and components of metabolic syndrome increase the odds of hip osteoarthritis.

Humans↗
PubMed2026

Long-term glycemic variability and risk of peripheral artery disease: a systematic review and meta-analysis of cohort studies.

BACKGROUND: A systematic review and meta-analysis to evaluate the impact of long-term glucose variability (GV) on the risk of developing peripheral artery disease (PAD). METHODS: The protocol was prospectively registered in PROSPERO (ID: CRD420251148763). Relevant longitudinal studies were identified through comprehensive searches of PubMed, Embase, and Web of Science. The primary outcome was the risk ratio (RR) of PAD comparing participants with high versus low GV. Summary effect sizes were calculated using a random-effects model to account for between-study heterogeneity. RESULTS: Eleven cohorts were included. Higher GV showed a positive association with PAD risk (RR: 1.42; 95% CI [1.21-1.66] p&#xa0;<&#xa0;0.001), although substantial heterogeneity was present (I 2&#xa0;=&#xa0;91%). This association was consistent across subgroups defined by region (Asian vs. Western), study design, diabetic status, GV metrics, PAD diagnostic methods, and adjustment for HbA1c (all p for subgroup differences > 0.05), except for follow-up duration. Studies with follow-up < 8 years showed a stronger association than those with &#x2265; 8 years (RR: 1.64 vs. 1.19; p for subgroup difference = 0.006). CONCLUSIONS: Elevated long-term GV appears to be associated with an increased risk of PAD. However, substantial heterogeneity across studies suggests that the magnitude of this association should be interpreted with caution.

Humans↗
PubMed2026

Applications of artificial intelligence in robot-assisted surgery: a systematic review.

To characterize applications of artificial intelligence (AI) in robot-assisted surgery, summarize technical and clinical performance, and assess the quality of the available evidence. PubMed, Web of Science Core Collection, and Scopus were searched for English-language journal articles published from 1 January 2020 through 31 October 2025. Randomized, observational, model-development, validation, and feasibility studies evaluating AI in robot-assisted surgery or closely related image-guided minimally invasive workflows were eligible. Two reviewers independently performed study selection, data extraction, and risk-of-bias assessment. Owing to heterogeneity in surgical procedures, AI tasks, analytical units, validation strategies, and outcomes, findings were synthesized descriptively without statistical pooling. The review was registered in the International Prospective Register of Systematic Reviews (CRD420251175699). Seventeen studies were included: seven clinical prediction or decision-support studies, eight intraoperative recognition, segmentation, or image-guided studies, and two training or workflow studies. Five prediction studies reported area-under-the-curve values of 0.74-0.95. Technical studies reported F1 or Dice scores of 0.525-0.995 and task-specific accuracies of 0.840-0.998. Two randomized studies suggested benefits for personalized suturing feedback and automated camera control, but neither established improved patient outcomes. Only one study had low overall risk of bias; the remaining studies were at high or unclear risk or raised some concerns. AI applications in robot-assisted surgery show promise for prediction, intraoperative perception, training, and workflow support. Evidence primarily demonstrates technical feasibility rather than established clinical effectiveness. Independent multicenter validation and prospective evaluation of patient, educational, and workflow outcomes are required before widespread implementation.

Robotic Surgical Procedures↗
PubMed2026

Editorial Commentary: Stiff Patients After Rotator Cuff Repair: How Many Had Underrecognized Preoperative Adhesive Capsulitis?

Stiffness after rotator cuff repair is one of the most common sources of disability and one of the most common complications. Smoking, diabetes, Workers' compensation status, and traumatic tears are among the strongest risk factors. This is important information in setting appropriate expectations for both the patient and the surgeon preoperatively. Some of these factors are also associated with preoperative stiffness, so surgeons should maintain a high index of suspicion for concomitant adhesive capsulitis in patients presenting with limited motion, particularly in diabetic and non-English speaking populations. In cases where both a rotator cuff tear and adhesive capsulitis coexist, performing a concurrent capsular release or manipulation during the index procedure may improve functional outcomes and reduce the necessity for secondary surgical intervention.

Humans↗
PubMed2026

Current Diagnostic Pathways for Rheumatoid Arthritis-Associated Interstitial Lung Disease Result in Substantial Underdiagnosis and Excess Mortality: A Multicenter Norwegian Quality Assurance Audit.

OBJECTIVE: Recent guidelines suggest risk-stratified screening for rheumatoid arthritis-associated interstitial lung disease (RA-ILD). However, the diagnostic gap between current routine care and this screening approach remains unquantified. We assessed currently detected RA-ILD in Norway, benchmarking findings against recent screening-based estimates of the true disease burden. METHODS: This 10-year quality assurance audit across six centers covered 43% of the Norwegian population. RA-ILD cases identified via ICD-10 codes were confirmed by manual chart review. Prevalence was calculated relative to a registry-derived total RA background population and benchmarked against a 10% expected target derived from recent prospective studies. Mortality was compared to a 3:1 frequency-matched RA control group using Cox proportional hazards regression. RESULTS: Among 17,305 RA patients, 188 (1.1%) had verified ILD; when benchmarked against an expected 10% prevalence, this indicates an 89% diagnostic gap in routine clinical care. Mean age at ILD detection was 67.5 years. Most cases (93.6%) possessed &#x2265;2 established risk factors for RA-ILD: 93.6% were seropositive, 76.1% had smoking histories, while RA onset age &#x2265;60 and persistently increased inflammatory laboratory markers were present in over half of patients. RA-ILD was associated with significantly increased mortality; 66 (4.1/100 person-years) deaths occurred in the RA-ILD group vs. 120 (2.3/100 person-years) among RA controls (HR 1.77; 95% CI: 1.31-2.39, p<0.001). CONCLUSION: When comparing to prevalence expectations, current routine care may leave a substantial proportion of cases undetected, primarily capturing a high-risk phenotype with excess mortality. Systematic, risk-stratified screening is needed to bridge this diagnostic gap, aiming to enable earlier intervention.

Interstitial lung disease↗