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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

Assessing comorbidities and predicting risk: A primer for APRNs.

Today's clinical environments are rife with tools designed to comprehensively account for medical complexity and comorbidities while predicting risk for a host of adverse health-related outcomes. Therefore, it is imperative that advanced practice registered nurses (APRNs) understand the structure and function of these tools, their similarities and differences, their limitations, and strategies for appropriate incorporation into practice. This article offers a practical overview for APRNs, emphasizing clinical implications and guidance for aligning assessment tools with the clinical population of interest to improve care delivery, quality, and patient outcomes.

Humans↗
PubMed2026

Are There Any Effective Behavior Change Strategies for Communicating Genetic Risk in Obesity Prevention and Body Weight Reduction Interventions?

This systematic review examined how differences in intervention components may contribute to inconsistent findings in genetic risk communication studies, addressing obesity-related outcomes (e.g., weight reduction, nutrition behavior, exercise). The review was preregistered (PROSPERO #CRD42024524026) and followed PRISMA guidelines. Searches across eight databases identified 23 randomized controlled trials, covering 18 intervention trials. Risk of bias was assessed using the Risk of Bias 2 tool. A narrative synthesis was used to cluster studies by the content of intervention and control groups. Genetic risk communication alone (no behavioral counseling, addressing nutrition and exercise) or combined with phenotype-based risk was ineffective and sometimes counterproductive among low-risk individuals. When combined with personalized behavioral counseling, effectiveness improved, but only when compared to waitlist control groups or non-personalized behavioral counseling. Significant effects emerged in high-genetic risk subgroups within personalized behavioral counseling, using behavior change techniques such as problem-solving, feedback on behavior, self-monitoring, and environmental changes. The most promising results emerged from complex interventions integrating genetic risk communication into multiple sessions and combining numerous additional behavioral change techniques, such as social reward, cues/prompts, self-reward. Complex personalized interventions combining multiple behavior change techniques and prompting experiential genetic risk awareness show promise for improving weight, nutrition, and exercise-related outcomes.

Humans↗
PubMed2026

Incidence and risk factors for malignancy in patients with incidental solitary pulmonary nodules: a systematic review and meta-analysis.

BACKGROUND: The increasing use of chest imaging has led to a higher detection rate of incidental solitary pulmonary nodules (SPNs), often causing patient anxiety. Determining the malignancy rate and associated risk factors is crucial for developing appropriate follow-up strategies to prevent overdiagnosis, overtreatment, or missed diagnoses. This meta-analysis aims to investigate the malignancy rate and risk factors in patients with incidental SPNs. METHODS: A systematic search of PubMed, Embase, Web of Science, and the Cochrane Library was conducted up to June 30, 2025. Data on malignancy rates and potential risk factors were extracted from eligible studies. All pooled analyses were performed using a random-effects model. RESULTS: Fifty-four studies involving 19,985 patients were included. The pooled malignancy rate for incidental SPNs was 56.7% (95% CI: 51.5-62.0), with significant between-study heterogeneity (I2 = 98.5%, p&#x2009;<&#x2009;0.001). The pooled effect size showed a minimal change after adjustment for potential publication bias using the non-parametric Trim-and-Fill method (54.7%; 95%CI: 50.9-58.8). Risk factor analysis identified that older age, history of cancer, cigarette smoker, larger nodule diameter, spiculation, upper lobe location, lobulation, pleural indentation, vascular convergence, solid nodules, family history of cancer, and irregular or ill-defined margins were significantly associated with an increased risk of malignancy. Conversely, male sex, presence of calcification, and clear borders were significantly associated with a reduced risk of malignancy. CONCLUSION: This meta-analysis provides a comprehensive assessment of malignancy rates and risk factors in incidental SPNs. The high pooled malignancy rate should be interpreted considering the significant heterogeneity and the inclusion of a high proportion of retrospective studies and populations from high-risk regions. Nonetheless, these findings offer essential evidence for clinical risk stratification, supporting optimized follow-up and informed decision-making.

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

Review of regulatory requirements for benefit-risk assessment for medical devices: uncovering existing methodologies.

INTRODUCTION: A positive benefit-risk profile is a prerequisite for the market approval of medical devices. However, regulations are often criticized for providing limited information on benefit-risk assessment (BRA) despite growing expectations for quantitative methods. A clearer understanding of regulatory requirements, existing methodologies, and unresolved issues is needed. AREAS COVERED: Relevant regulatory documents referencing BRA for medical devices were systematically identified, with a primary focus on the European regulation followed by screening to extract BRA&#x2011;related requirements and any explicitly or implicitly described methods. The findings were analyzed and consolidated by BRA context, type, objective, methodological description, and implementation, thereby establishing a basis for the BRA methodological landscape. EXPERT OPINION: BRA is not a single concept, but a set of context&#x2011;dependent assessments across lifecycle of a medical device. BRA within clinical evaluation framed into BRAs of risk management holds a pivotal role and is supported by the most detailed methodological guidance, although BRAs in other contexts are important. A structured overview of existing BRA requirements clarifies their treatment across regulatory documents. By differentiating BRA contexts, types, objectives, and required methodological detail, the analysis supports a more transparent understanding of BRA and helps identify priorities for methodological refinement and interface clarification.

Risk Assessment↗
PubMed2026

Effects of Moderate-Frequency Resistance Training on Cardiometabolic Risk Factors in Adults With Overweight or Obesity: A Systematic Review and Meta-Analysis.

BACKGROUND: Resistance training (RT) effectively manages cardiometabolic risk factors in adults, but the specific effects of moderate-frequency RT (2-3 sessions/week) in adults with overweight or obesity are understudied. OBJECTIVE: This study aimed to evaluate moderate-frequency RT's effects on cardiometabolic risk factors in this population and quantify effect sizes. DATA SOURCES: PubMed, Web of Science, EMBASE, and Cochrane Library searched up to July 2025. ELIGIBILITY: English randomized controlled trials (RCTs) comparing RT (&#x2265;&#x2009;7&#x2009;weeks) to nonexercise control; nonathletic adults &#x2265;&#x2009;18&#x2009;years with BMI&#x2009;&#x2265;&#x2009;25&#x2009;kg/m2. PARTICIPANTS: 454 participants across 12 RCTs (mean age 58.93&#x2009;&#xb1;&#x2009;12.87&#x2009;years; mean BMI 31.2&#x2009;&#xb1;&#x2009;3.5&#x2009;kg/m2; ~50% female). RESULTS: RT significantly reduced diastolic blood pressure (MD&#x2009;=&#x2009;-1.53&#x2009;mmHg; 95% CI: -2.16 to -0.91; p&#x2009;<&#x2009;0.01), LDL-C (MD&#x2009;=&#x2009;-0.25&#x2009;mmol/L; 95% CI: -0.41 to -0.08; p&#x2009;<&#x2009;0.01), and triglycerides (MD&#x2009;=&#x2009;-0.17&#x2009;mmol/L; 95% CI: -0.30 to -0.04; p&#x2009;=&#x2009;0.01). No significant effects on systolic blood pressure, mean arterial pressure, waist circumference, glycemic markers, total cholesterol, or HDL-C. Subgroup analyses showed larger LDL-C/triglyceride improvements with concurrent dietary control. CONCLUSION: Moderate-frequency RT inconsistently improves cardiometabolic risk factors, benefiting diastolic blood pressure, LDL-C, and triglycerides but not glycemic or other parameters. Combining with dietary control may enhance benefits, supporting RT as a complementary strategy in multimodal lifestyle interventions. TRIAL REGISTRATION PROSPERO: CRD42022343167.

Humans↗
PubMed2028

Parental son preference in childhood and sex differences in the risk of cardiovascular disease in middle-aged and older adults.

INTRODUCTION: Sex differences in cardiovascular disease (CVD) risk are examined through biological and clinical factors, with less attention to early-life social exposures. This study examined associations of childhood parental son preference with CVD risk, sex differences, and mediation by modifiable risk factors. METHODS: This cohort analysis included China Health and Retirement Longitudinal Study participants aged &#x2265;45 years without baseline CVD. Parental son preference was assessed retrospectively in 2014; incident CVD was self-reported physician-diagnosed heart disease or stroke through 2020. Sampling-weighted, community-clustered Cox models estimated adjusted hazard ratios (aHRs) and 95% CIs. Sex was prespecified as an effect modifier; mediation by 13 risk factors used inverse-odds-ratio weighting. Data were collected from 2011 to 2020 and analyzed from 2025 to 2026. RESULTS: Among 8,079 participants (mean age, 57.5 years; 4,216 women [52.2%]), 1,820 (22.5%) reported parental son preference. Son preference was associated with higher CVD risk overall (aHR 1.23 [95% CI 1.04, 1.46]) and among women (aHR 1.25 [95% CI 1.03, 1.53]); among men, the estimate was 1.16 (95% CI 0.87, 1.56), with limited heterogeneity by sex (ratio of aHRs 1.06 [95% CI 0.72, 1.58]). Among women, risk was concentrated in the highest paternal (aHR 1.47 [95% CI 1.14, 1.90]) and maternal (aHR 1.50 [95% CI 1.12, 1.99]) preference categories. Modifiable risk factors mediated 5.8% (95% CI 1.9%, 9.7%) of the association among women, mainly through socioeconomic and psychosocial factors. CVD risk was highest with both son preference and high risk-factor burden overall (aHR 1.97 [95% CI 1.43, 2.73]) and among women (aHR 2.23 [95% CI 1.61, 3.10]). CONCLUSIONS: Parental son preference was associated with higher incident CVD risk, with the largest estimates in the highest paternal or maternal categories among women. Modifiable risk factors explained a modest proportion, supporting life-course cardiovascular prevention that considers sex-differentiated childhood environments alongside risk-factor modification.

cardiovascular disease↗
PubMed2026

Predictive Models for Hypoglycemia Risk in Haemodialysis Patients With Diabetic Kidney Disease: Systematic Review and Meta-Analysis.

AIM: To provide evidence for selecting and developing reliable clinical assessment tools for hypoglycemia in diabetic kidney disease patients during haemodialysis. DESIGN: Review. METHODS: Systematic searches were performed in 9 Chinese and English databases to collect literature regarding the development of hypoglycemia risk prediction models in haemodialysis patients with diabetic kidney disease. Two reviewers independently performed literature screening, data extraction, risk-of-bias assessment, and applicability evaluation. The Prediction Model Risk of Bias Assessment Tool was used to assess the risk of bias and applicability of the included studies. Meta-analysis was conducted using R software. DATA SOURCES: CNKI, Wanfang, VIP, CBM, PubMed, Cochrane Library, EMbase, Web of Science, and CINAHL. The search period covered from the establishment date of each database to December 2025. RESULTS: Six studies, comprising six prediction models, were included. Two studies performed internal validation, and three conducted external validation. All models reported the area under the curve, ranging from 0.813 to 0.866, and calibration measures. Four studies were rated as having a high risk of bias, while all six demonstrated good overall applicability. The meta-analysis showed that the pooled AUC value of the six studies was 0.846 (95% CI: 0.823-0.867). CONCLUSION: Research on hypoglycemia risk prediction models in haemodialysis patients with diabetic kidney disease remains in the developmental stage. Although the included prediction models exhibited satisfactory apparent discriminatory ability and clinical applicability, most of the original studies suffered from a high risk of bias and lacked adequate validation. The true predictive performance and clinical application value of these models remain to be further verified. Accordingly, routine and unconditional clinical application is not recommended at this stage. Future studies should include more high-quality, multicenter external validation and develop models with high generalizability, favourable clinical applicability, and robust predictive performance to facilitate early identification of hypoglycemia risk in this population. IMPACT: This study systematically evaluated the hypoglycemia risk prediction models for diabetic kidney disease patients during haemodialysis, and the research on hypoglycemia risk prediction models for maintenance haemodialysis patients during dialysis is still in the development stage. This study provides a reference for clinical medical staff to select or develop hypoglycemia risk prediction and assessment tools for diabetic kidney disease patients during haemodialysis. REPORTING METHOD: This study was conducted in accordance with the relevant guidelines of the EQUATOR Network and followed the TRIPOD-SRMA Checklist. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution. TRIAL REGISTRATION: PROSPERO: CRD420251243352.

Humans↗
PubMed2026

Clustering patterns of behavioral and metabolic risk factors for noncommunicable diseases in Iran: findings from a national STEPS survey.

BACKGROUND: Noncommunicable diseases (NCDs) are the leading cause of mortality in Iran, driven by behavioral and metabolic risk factors that frequently co-occur. OBJECTIVE: To identify patterns of co-occurring behavioral and metabolic NCD risk factors among Iranian adults and characterize their demographic and socioeconomic correlates. METHODS: This cross-sectional study analyzed data from 16,618 adults aged &#x2265;25&#x2009;years who participated in Iran's 2021 nationally representative STEPS survey. Thirteen behavioral and metabolic variables, including physical activity, nutrition score, smoking frequency, alcohol intake, salt intake, body mass index, blood pressure, fasting plasma glucose, and lipid markers, were entered into a K-means clustering analysis. Clusters were characterized by their risk profiles and demographic/socioeconomic attributes. Multinomial logistic regression examined associations between cluster membership and sociodemographic factors. RESULTS: Five distinct behavioral-metabolic clusters emerged. The smokers-drinkers (SD) cluster (3.1%) comprised mostly older, less-educated men with high smoking and alcohol use. The healthy-low-risk (HLR) cluster (40.3%) showed favorable profiles and included younger, more educated individuals. The physically active (PA) cluster (6.6%) was characterized mainly by younger men with markedly high physical activity levels. The dyslipidemic (DLP) cluster (26.0%) exhibited high dyslipidemia and overweight prevalence, while the hypertensive-diabetic (HTD) cluster (24.0%) had the highest obesity, hypertension, and diabetes rates, common among older urban adults. CONCLUSION: Behavioral and metabolic NCD risk factors in Iran formed five distinct co-occurrence patterns. Nearly half of adults belonged to metabolically high-risk clusters, highlighting the need for targeted prevention strategies that combine lifestyle interventions with screening and management of obesity, hypertension, diabetes, and dyslipidemia.

Humans↗
PubMed2026

Risk factors of venous thromboembolism in ICU patients: a systematic review and meta-analysis.

OBJECTIVE: This study aimed to identify risk factors associated with the development of VTE in patients admitted to the intensive care unit (ICU). METHODS: A systematic literature search was conducted via PubMed, Embase, Web of Science, and Cochrane databases up to 25 April 2025, to identify studies examining the association between risk factors and the occurrence of venous thromboembolism (VTE) in ICU patients. Data were pooled using odds ratios (ORs) and 95% confidence intervals (CIs). RESULTS: A total of 2465 relevant studies were identified through the systematic search, of which 30 were included in the meta-analysis. The pooled data showed that the following were significant risk factors for venous thromboembolism (VTE) in ICU patients: central venous catheterization (OR = 2.67, 95% CI: 1.67-4.28; I2 = 28%), invasive mechanical ventilation (OR = 2.08, 95% CI: 1.46-2.96; I2 = 0%), advanced age (OR = 2.06, 95% CI: 1.28-3.31; I2 = 86%), length of ICU stay (OR = 4.24, 95% CI: 1.43-12.57; I2 = 98%), malignancy (OR = 2.30, 95% CI: 1.03-5.12; I2 = 67%), elevated D-dimer levels (OR = 2.46, 95% CI: 1.37-4.40; I2 = 34%), and a history of VTE (OR = 2.84, 95% CI: 1.45-5.55; I2 = 51%). According to the GRADE assessment, the quality of evidence was rated as moderate for invasive mechanical ventilation, low for central venous catheterization and D-dimer levels, and very low for the remaining factors. CONCLUSION: Invasive mechanical ventilation, central venous catheterization, and elevated D-dimer levels are associated with VTE risk, supported by relatively high-quality evidence. These findings may help identify ICU patients at higher risk of VTE, inform the development of risk assessment models for patient stratification, and ultimately contribute to improved prognosis through optimal screening and management strategies.

Humans↗
PubMed2026

Risk stratification in aortic stenosis: exercise haemodynamics to refine risk in early cardiac damage stages.

AIMS: To describe exercise haemodynamics across cardiac damage stages and evaluate the incremental prognostic impact of cardiac damage stage and exercise-induced pulmonary hypertension (exPHT) in patients with symptomatic moderate aortic stenosis (AS) and asymptomatic severe AS. METHODS AND RESULTS: A total of 436 consecutive patients with &#x2265; moderate AS (74 &#xb1; 10 years, 32% women, 56% severe AS) underwent cardiopulmonary exercise testing with echocardiography. The primary endpoint was heart failure (HF) death and HF hospitalizations. Cardiac damage stage was 0 in 93 patients, 1 (LV damage) in 135, 2 (LA/mitral damage) in 135, and 3-4 (pulmonary vasculature/tricuspid or RV damage) in 73. Higher stages were associated with worse exercise capacity and haemodynamics. Over a median follow-up of 37 months, 65 patients met the primary endpoint. After adjustment for age, AS severity, and aortic valve replacement, cardiac damage stage and exPHT were independently associated with HF outcomes [HR per stage increase 1.51 (1.26-1.82); P < 0.001; exPHT HR 2.36 (1.10-5.07); P = 0.03]. exPHT improved risk stratification in early-stage disease (stages 1-2), conferring an approximately five-fold higher risk of HF events in patients with exPHT [HR 4.45 (1.58-12.59); P < 0.01]. CONCLUSION: In patients with &#x2265; moderate AS and discordant symptoms, cardiac damage stage and exPHT independently refined HF risk stratification. ExPHT provides incremental prognostic value in early damage stages (1-2), representing over half of the cohort, supporting a stepwise approach of routine damage staging with selective with exPHT assessment with exercise echocardiography in this subgroup to guide more personalized management and potentially optimize AVR timing.

Humans↗
PubMed2026

Artificial Intelligence for Diagnosis, Risk Stratification, and Prognosis of Neuroblastoma - A Systematic Review and Meta-Analysis.

PURPOSE: To synthesizes evidence on artificial intelligence (AI) performance in neuroblastoma (NB) diagnosis, risk stratification, prognosis, and genomic characterization. MATERIALS AND METHODS: A systematic review and meta-analysis was conducted following PRISMA 2020 guidelines (PROSPERO: CRD42024539475) across five databases. Meta-analyses used random-effects models with logit-transformed Area Under the Curve (AUCs) and cluster-robust standard errors. AI models were classified as Machine Learning Models (MLM) or Hybrid Nomograms (HN) based on their construction methodology. RESULTS: Of 3,742 articles identified, 53 were included. MLMs demonstrated higher point estimates than radiologists in differential diagnosis (AUC: 0.87 vs. 0.83), though this difference was not statistically significant and carried substantial uncertainty. HNs achieved stronger performance in risk stratification (AUC: 0.87). AI-derived nomograms (AUC: 0.9) and gene signatures (AUC: 0.8) outperformed conventional prognostic markers descriptively. Chemotherapy response prediction remained below clinical utility thresholds across all model types. Only 33.9% of models reported calibration and 24.5% underwent external validation. CONCLUSIONS: AI demonstrates proof-of-concept across multiple NB clinical domains. However, clinical adoption remains premature given persistent gaps in external validation, calibration, dataset size, and pediatric-specific model development. Future studies should test these models prospectively in multicenter pediatric cohorts, ideally through COG or SIOPEN, using shared definitions for diagnosis, risk group, treatment response, and survival outcomes.

Humans↗
PubMed2026

Factors Impacting Overall Survival Post-Relapse in High-Risk Neuroblastoma: Children's Oncology Group Outcomes From 2000 to 2019.

PURPOSE: Prior studies of features impacting post-relapse survival in high-risk neuroblastoma (HRNB) evaluated patient cohorts that did not receive contemporary high-risk or relapse therapies. We describe overall survival (OS) after first progression or first relapse of HRNB in a modern cohort. METHODS: Patients with HRNB enrolled on COG ANBL00B1(NCT00904241) between 2000 and 2019, who had relapsed or progressive disease were eligible. Clinical and molecular risk factors at diagnosis, therapy era, clinical trial enrollment, and clinical features at relapse, including site of and time to relapse, were evaluated. OS post-relapse was compared between groups using log-rank tests and Cox models. RESULTS: Among 4253 eligible HRNB patients, 1616 had relapse or progression as a first event. Five-year OS post-relapse was 19.1&#xa0;&#xb1;&#xa0;1.1%. The risk group with the lowest post-relapse survival was observed in patients with INSS Stage 4 or 4S disease <&#xa0;18 months of age at diagnosis with MYCN amplified (MYCN-A) tumors. The other significant most unfavorable factors at diagnosis included diagnosis 2000-2004, tumor MYCN-A, 1p loss of heterozygosity (LOH), and elevated LDH or ferritin. Unfavorable factors at relapse included the time to relapse <&#xa0;36 months from diagnosis, and combined local and metastatic disease at relapse. Multivariable analysis indicated that those with tumors harboring 1p LOH, age &#x2264;&#xa0;5 years at diagnosis, or earlier treatment therapy era (2000-2004) had a higher risk of post-relapse death. CONCLUSIONS: While the 5-year OS rate was low in this cohort, there are subsets of patients with relapsed HRNB who demonstrate long-term survival. TRIALS REGISTRATION: ClinicalTrials.gov identifier: NCT00904241.

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&#xa0;=&#xa0;5), support vector machines (n&#xa0;=&#xa0;4), k-nearest neighbor (n&#xa0;=&#xa0;3), decision trees (n&#xa0;=&#xa0;3), random forests (n&#xa0;=&#xa0;5), neural networks (n&#xa0;=&#xa0;2), linear discriminant analysis (n&#xa0;=&#xa0;1), and pre-trained CNNs (n&#xa0;=&#xa0;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&#xa0;=&#xa0;12 to n&#xa0;=&#xa0;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

Clinical and psychological characteristics of adolescents at risk of mood disorders compared with adolescents with suicidal behavior.

Suicide is one of the leading causes of death among adolescents, yet little is understood about the biopsychosocial factors related to suicidality. The demographic, clinical, and biological characteristics of adolescents with and without psychiatric histories may help inform mechanistic approaches to treatment of mood disorders and suicidality. The 'characterizing the inflammatory profile and suicidal behavior in adolescents' and 'RAD arm of the Texas Resilience Against Depression' studies aimed to characterize the clinical and biological profiles of youth with suicidal behavior and youth at risk for mood disorders, compared to healthy adolescents (n&#xa0;=&#xa0;75 in each group). Here, we report the descriptive baseline clinical and psychological characteristics of adolescents at risk of mood disorders and those with suicidal behavior. The adolescents with suicidal behavior reported 3.53 lifetime suicidal events on average, predominantly reported moderate to very severe depression (34.7%, 24%, to 9.3%), moderate to severe anxiety (58.6%), low optimism (91.9%), and mild (39.2%) to moderate (28.4%) degree of hopelessness. The at-risk adolescents predominantly reported no depression (60%) or anxiety (68.9%), moderate optimism (50%), and a positive outlook (85.7%). Healthy adolescents predominantly reported no depression (88.3%) or anxiety (93.2%), moderate optimism (59%), and a positive outlook (87%). The adolescents with suicidal behavior and those at risk of mood disorders exhibited significantly higher irritability and borderline personality disorder features (uncorrected p&#xa0;=&#xa0;0.02 to p&#xa0;<&#xa0;0.001) and lower resilience compared to healthy adolescents. Ongoing investigations using the longitudinal clinical and biological data will help identify the immune biosignatures of suicidality in youth.

Humans↗