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Comparing Clinical and Cytokine Profiling of Genital Inflammation as Predictors of HIV Acquisition in Women.

BACKGROUND: Inflammation in the female genital tract is a key risk factor for HIV acquisition, but it remains unclear whether clinical or immunological measures best predict risk. We aimed to compare HIV acquisition among women with clinically and/or immunologically defined inflammation. SETTING: HIV-uninfected women enrolled in the CAPRISA 004 tenofovir gel randomized controlled trial in South Africa were followed for up to 34 months. METHODS: We analyzed data from 889 women, with cytokine measurements available for 774 participants. Clinical genital abnormalities were assessed at scheduled visits, and 9 cytokines were measured in cervicovaginal lavage samples. HIV incidence was compared across categories of clinical and immunological inflammation using time varying Cox proportional hazards models, adjusting for relevant covariates. RESULTS: Immunological inflammation, defined as ≥9 elevated cytokines, was present in 18% (140/774) of women. Among specific clinical signs, abnormal genital discharge (adjusted hazard ratio: 2.67, 95% confidence interval [CI]: 1.14 to 6.23, P = 0.024) and cervicitis (adjusted hazard ratio: 10.34, 95% CI: 2.46 to 43.65, P = 0.001) were significantly associated with increased HIV acquisition. Women with both clinical and immunological inflammation had the highest risk of HIV acquisition, with adjusted hazard ratios of 2.08 (95% CI: 1.10 to 3.91, P = 0.022) and 2.46 (95% CI: 1.21 to 5.03, P = 0.013), respectively. CONCLUSIONS: Clinical and immunological definitions of inflammation were each independently associated with increased HIV acquisition risk and combined, they reflected greater susceptibility. These findings highlight the important role of genital inflammation in women's HIV susceptibility, suggesting that clinical signs may provide practical early indicators of risk even as cytokine profiles provide more sensitive measures of underlying inflammation.

Humans

Rates, Timing, and Predictors of Retreatment Across Risk-Cohorts in Retinopathy of Prematurity: Intravitreal Bevacizumab Injection Versus Laser.

OBJECTIVE: To characterize rates, timing, and predictors of retinopathy of prematurity (ROP) retreatment among infants treated with primary laser or intravitreal bevacizumab injection. DESIGN: Retrospective consecutive, comparative clinical study. PARTICIPANTS: Infants who underwent initial treatment for treatment-warranted ROP (TW-ROP) with either intravitreal bevacizumab or laser photocoagulation between 2017 and 2023. METHODS: Patients were stratified into two treatment groups: primary laser group vs primary bevacizumab group. MAIN OUTCOME MEASURES: Retreatment within the first 3 months (0-90 days) was assessed and classified as early (&#x2264;30 days) or late (31-90 days). RESULTS: Two hundred and thirty eight eyes of 122 infants were treated for ROP; of those, 181 (76.1%) eyes of 93 (76.2%) patients were included. There were 116 (64.1%) eyes in the bevacizumab group, and 65 (35.9%) eyes in the laser group. Thirty-three (18.2%) eyes-all micro- or nano-premature (<27 weeks GA and/or <800 grams)-required retreatment for TW-ROP. Sixteen (8.8%) required early retreatment at a median postmenstrual age (PMA) of 40.4 weeks (IQR, 38.44-43.3). There were differences in the proportion of early retreated infants (21.5% for laser vs 1.7% for injection, P < .001). Seventeen (9.4%) eyes required late retreatment. The median PMA at late retreatment was 45.6 weeks (IQR, 43.7-47.4). Infants in the bevacizumab group had lower odds of retreatment within three months than those with laser (OR, 0.23; 95% CI, 0.06-0.82). Similarly, patients in the bevacizumab group had lower odds of requiring early retreatment compared to those with laser (OR, 0.08; 95% CI, 0.04-0.18). Within eyes with retreatment, infants in the bevacizumab group had a later PMA at retreatment than those in the laser group (B = 6.81; 95% CI: 4.68-8.93). AROP was associated with earlier PMA at retreatment (B = -7.72; 95% CI, -9.36 to -6.10). CONCLUSION: In this study, early retreatment was low (8.8%), with most eyes initially treated with laser (21.5%) rather than bevacizumab (1.7%). Aggressive ROP was associated with earlier retreatment, highlighting its role as a marker of more severe disease. Compared to laser, bevacizumab was associated with lower overall and early retreatment, and delayed need for additional intervention when necessary. All retreatments occurred in micro- or nano-premature infants, suggesting that medium-to-low risk infants may require less strict post-treatment monitoring.

Humans

Postoperative chemoradiotherapy in Wilms tumor with concurrent lung and lymph node metastasis.

BACKGROUND: An effective treatment strategy is essential for metastatic Wilms tumor (WT) management. To improve prognostic accuracy, this study examined metastatic patterns and key prognostic factors. METHODS: Children diagnosed with WT from 2010 to 2021 were identified from the SEER database. All patients underwent chemotherapy and surgical resection. Metastatic patterns, metastasis-related predictors, and prognostic factors were evaluated. RESULTS: Of the 1040 patients analyzed, 226 (21.7%) experienced lung metastasis, 31 (3.0%) liver metastasis, 6 (0.6%) bone metastasis, and 220 (21.2%) regional lymph node metastasis. Distant metastasis was associated with a higher incidence of lymph node metastasis (OR = 1.506, 95% CI 1.346-1.685, p < 0.001). Age 3-17 years (OR = 1.933, 95% CI 1.406-2.680, p < 0.001), left-sided (OR = 1.383, 95% CI 1.016-1.890, p = 0.040), bilateral (OR = 2.303, 95% CI 1.215-4.243, p = 0.009), and tumor size &#x2265;135 mm (OR = 2.020, 95% CI 1.481-2.749, p < 0.001) were identified as predictors of metastasis. Both lymph node (p < 0.001) and lung metastasis (p < 0.001) were high-risk factors for WT. Radiotherapy provided long-term survival benefits for the metastatic population (p = 0.027), while postoperative chemotherapy showed better outcomes than preoperative or other strategies (p < 0.001). Further analysis demonstrated that the concurrent lung and lymph node metastasis group benefited more from postoperative chemoradiotherapy, with HRs of 0.226 (p = 0.028) for overall survival and 0.255 (p = 0.048) for cancer-specific survival. CONCLUSION: WT with concurrent lung and lymph node metastasis represents a distinct and aggressive metastatic phenotype associated with a significantly poor prognosis. Postoperative chemoradiotherapy may provide superior survival benefits for this high-risk population.

Humans

Effects of Family-Based Intervention for Childhood Obesity on Parental and Offspring Outcomes: A Systematic Review and Meta-Analysis.

BACKGROUND AND OBJECTIVES: Childhood obesity is a global public health issue with strong familial and intergenerational transmission. However, existing syntheses often overlook the active role of parents and fail to assess outcomes beyond the child. This systematic review and meta-analysis specifically investigate the effects of family-based interventions, which position parents as active co-agents of change, on health outcomes for both children with obesity and their parents. METHODS: A systematic review and meta-analysis were conducted. Six databases were searched for randomized controlled trials (RCTs) targeting children with obesity and at least one family member. Primary outcomes were children's BMI z-score and parental BMI; secondary outcomes included other adiposity measures and dietary behaviors. Outcomes for both children and parents were synthesized. Subgroup analyses were conducted based on intervention characteristics. Risk of bias was assessed using RoB 2, and evidence certainty was evaluated using GRADE. RESULTS: Twenty RCTs with 1740 participants were included in the meta-analysis. The interventions demonstrated a significant reduction in children's BMI z-score. Additional benefits were observed for long-term BMI z-score and percentage of total body fat. The most effective interventions commonly integrate health education, behavioral strategies, and motivational support. Subgroup analyses indicated that interventions positioning parents as active co-participants, rather than mere supporters, yielded larger effects. However, no significant effects were found on parental BMI. CONCLUSION: This study demonstrates that family-based interventions can confer significant benefits for children with obesity. Their success hinges on strategically framing parents as active co-agents and integrating motivational strategies.

Humans

Effectiveness of psychosocial and lifestyle interventions in promoting behaviour change and improving cognitive outcomes in older people with memory concerns: A systematic review.

BACKGROUND: Older adults with mild cognitive impairment or subjective cognitive decline have a greater dementia risk, particularly those from minority ethnic and socioeconomically disadvantaged backgrounds. Psychosocial and lifestyle interventions targeting modifiable risk factors offer hope for reducing risk, yet behavioural mechanisms remain unclear. This systematic review examines these mechanisms and associated outcomes. METHOD: We searched PubMed, Embase (Ovid), PsycINFO (Ovid), Web of Science, and Scopus for randomised control trials testing interventions that aimed to improve lifestyle and cognition in older adults with memory concerns. We explored behavioural mechanisms using the COM-B model and synthesised intervention effectiveness, overall and within underserved groups. We prioritised lower risk of bias studies. RESULTS: 26 studies described 23 randomised controlled trials (14 multidomain, 9 single domain interventions). Certainty of evidence that behaviour change was associated with cognition was low. Moderate-certainty evidence indicated that interventions providing a socially supportive environment and combining nutritional education and counselling for 6&#x202f;+&#x202f;months improved diet. Physical activity improved primarily in interventions incorporating education, structured training, and enablement strategies (e.g., tailored programmes, providing tools). Interventions simultaneously targeting capability, opportunity and motivation showed greater overall effectiveness. Few studies recorded ethnicity (13%) or sociodemographic status (9%), and none explored their impact. CONCLUSIONS: Non-pharmacological interventions can help this population improve their lifestyles if they feel capable, equipped and motivated, highlighting the value of careful design and implementation. There is scarce evidence on how these interventions work for underserved populations. Future research should explore this to inform tailored interventions and develop equitable dementia prevention strategies.

Humans

Reinforcement learning-based dynamic ensemble for missense variant effect prediction and tiered prioritization of VUS.

BACKGROUND: Accurate classification of missense variants remains a challenging task despite major advances in genomics. Numerous computational models have been developed to assist in variant classification, but often require repeated integration and benchmarking efforts. Ensemble methods have been proposed to overcome the limitations of single predictors, but mostly rely on fixed, predefined weights that constrain their ability to capture interactions among predictive signals. METHODS: We present GenixRL, a dynamic ensemble framework that reformulates model fusion as a reinforcement learning optimization problem. GenixRL uses a Q-learning agent to learn a policy that dynamically weights the probabilistic outputs of complementary predictors, including BayesDel (addAF and noAF), ClinPred, and MetaRNN. Replacing static weighting with policy learning allows GenixRL to adaptively identify optimal weightings and substantially improve classification accuracy. RESULTS: In benchmark evaluation against 25 state-of-the-art predictors, GenixRL achieved an AUROC of 0.9644 on an independent ClinVar dataset. On saturation genome editing assays for BRCA1 and BRCA2, GenixRL achieved the best performance and ranked highest on 14 of 17 clinically significant genes in a zero-shot evaluation. Applied to uncertain and conflicting ClinVar variants, GenixRL enabled tiered, evidence-based prioritization of hundreds of thousands of variants as likely pathogenic or pathogenic with high confidence, supported by orthogonal population evidence from gnomAD. CONCLUSION: GenixRL advances pathogenicity prediction for missense variants and provides an adaptive ensemble that sorts variants of uncertain significance into tiered candidates for expert curation and functional validation.

Mutation, Missense

Risk Factors for Long-Term Health-Related Quality-of-Life and Mental Health Outcomes in Traumatic Brain Injury: A Systematic Review and Meta-Analysis.

Traumatic brain injury (TBI) often leads to long-term disability, including persistent mental health issues and lower health-related quality of life (HRQoL). Early interventions can improve recovery, but because resources limit routine monitoring of all patients, trauma care remains largely symptom-driven. The combination of long-term disability and limited capacity for routine follow-up highlights the need for risk-stratified follow-up care and reliable evidence on early prognostic factors. However, the existing literature is sparse and methodologically heterogeneous, limiting the clinical applicability of findings. We therefore conducted a systematic review and meta-analysis to identify early risk factors for poorer long-term mental health and HRQoL outcomes. A systematic search of seven electronic databases identified studies of adult patients with TBI, with outcomes assessed at least 6 months postdischarge. Two authors independently screened the studies, assessed the risk of bias, and extracted the data. We pooled effect estimates using a random-effects meta-analysis and calculated 95% prediction intervals. A narrative synthesis was applied when meta-analysis was not feasible. The review was registered with PROSPERO (CRD42024576912) and reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Of the 8,104 articles screened, 64 studies met the inclusion criteria (n = 334,672). Most studies (58%) had a low risk of bias. Female sex, socioeconomic disadvantage, psychiatric history, assaultive-related injuries, and previous TBI were consistently associated with worse long-term outcomes. Across meta-analyses, assault-related injuries more than doubled the odds of post-traumatic stress disorder (odds ratio [OR] = 2.72; 95% confidence interval [CI]: 2.01-3.66, I2 = 0%). Higher odds were also observed among females (OR = 1.33; 95% CI: 1.11-1.59, I2 = 0%), individuals with prior TBI (OR = 1.56; 95% CI: 1.07-2.27, I2 = 0%), and those with psychiatric history (OR = 2.38; 95% CI: 1.83-3.10, I2 = 48%). We found that female sex (OR = 1.72; 95% CI: 1.38-2.16, I2 = 58%), prior TBI (OR = 1.52; 95% CI: 1.25-1.85, I2 = 0%), and psychiatric history (OR = 3.25; 95%CI: 1.86-5.69, I2 = 98%) were associated with higher odds of depression. Furthermore, higher pooled anxiety scores were observed in females and in individuals with a psychiatric history. The study identified several readily available factors present before or at discharge that are associated with poor long-term HRQoL and mental health outcomes. Leveraging these factors in follow-up protocols, prediction modeling, and clinical decision support systems may facilitate risk-stratified postdischarge care for TBI patients.

Humans

Development and validation of a comprehensive prognostic model for 28-day ICU mortality in non-traumatic subarachnoid hemorrhage: an analysis based on the MIMIC-IV database.

BACKGROUND: Due to the complex pathophysiology of non-traumatic subarachnoid hemorrhage (SAH), accurate risk prediction remains a challenge. Our aim is to develop and validate a comprehensive prognostic model that integrates demographic characteristics, vital signs, laboratory parameters, and more, to provide clinical decision-making support in real-world practice. METHODS: We conducted a retrospective cohort study of 785 Non-traumatic subarachnoid hemorrhage patients. The cohort was randomly divided into a training set (n&#xa0;=&#xa0;549) and a validation set (n&#xa0;=&#xa0;236). Feature selection was performed using LASSO regression, followed by backward stepwise Cox regression for optimization. A nomogram was constructed based on independent predictive factors, and model performance was assessed using discrimination, calibration, and decision curve analysis. To prevent immortal-time bias, all predictors were anchored to a fixed early (first-24-hour) measurement window, treatment variables were modelled as binary indicators rather than cumulative exposures, and a five-model sensitivity analysis with baseline-severity adjustment was performed. RESULTS: The development of our model followed a systematic approach: first, 15 potential predictive factors were selected via LASSO regression, which were then refined to 12 independent predictors using backward stepwise Cox regression. The final predictive factors included: Ventilation, AHT, Nimodipine 60&#xa0;mg, Age, SAPS.II, Input amount, Calcium total, Platelet count, White blood cells, Anion gap, pH, and Chloride. The integrated model demonstrated excellent predictive ability for 7-day, 14-day, and 21-day mortality in both the training set (AUC: 0.972, 0.934, 0.898) and the validation set (AUC: 0.968, 0.948, 0.911). Calibration curves and decision curve analysis confirmed the model's reliability and clinical utility across different time points. We constructed a nomogram for individualized risk prediction. Univariate Kaplan-Meier survival analysis demonstrated significant stratification of survival outcomes by each predictor, while restricted cubic spline analysis revealed non-linear relationships between continuous variables and mortality risk. Random survival forest analysis identified the top three predictive factors (Nimodipine 60&#xa0;mg, Ventilation, AHT) and compared them with our full 12-variable model, confirming superior performance of the integrated model at all time points. At the 28-day primary endpoint, the model achieved a time-dependent AUC of 0.898 (training) and 0.904 (validation); after restricting predictors to the early baseline window, the leakage-controlled model retained good discrimination (validation C-index 0.803). CONCLUSIONS: Our ICU 28-day mortality prognosis model demonstrated robust performance in predicting ICU 28-day mortality in non-traumatic subarachnoid hemorrhage. The model, through the nomogram, provides individualized risk assessment, aiding clinical decision-making and patient stratification.

Humans

Meta-PseU: A meta-classifier for robust prediction of RNA pseudouridine modification sites from long sequences.

BACKGROUND AND OBJECTIVES: Pseudouridine (&#x3a8;) represents one of the most abundant and conserved RNA modifications. &#x3a8; provides an additional hydrogen-bond donor that enhances RNA structural stability and modulates translation. It participates in diverse biological processes, including RNA-protein interactions, splicing, translational control, and stress responses. Aberrant pseudouridylation is implicated in cancer, neurodegenerative disorders, and autoimmune diseases. Despite its biological importance, experimental identification of &#x3a8; sites remains time-consuming and costly, limiting the feasibility of transcriptome-wide profiling. Computational approaches have therefore become essential complements to experimental techniques. However, state-of-the-art machine-learning and deep-learning predictors often suffer from limited generalizability due to small training datasets. To overcome these issues, we aim at constructing new long-sequence datasets and developing a novel &#x3a8; site predictor. METHODS: New long-sequence datasets were constructed as benchmarks for RNA &#x3a8;-site prediction. The &#x3a8; modification sites in RMBase 3.0 were mapped to the reference genomes across three species of human, mouse, and yeast, and the RNA sequences with a length of 201 were generated by extending the upstream and downstream from the mapped, central sites. To eliminate sequence redundancy, the sequences were clustered using CD-HIT with a 70% sequence identity threshold. We developed Meta-PseU, a logistic regression-based meta-classifier that considered 118 machine learning and deep learning classifiers. The datasets and programs are freely accessible at https://github.com/kuratahiroyuki/MetaPseU. RESULTS: By optimizing model configuration, we proposed the Meta-PseU model stacking 32 machine learning and deep learning classifiers out of 118 classifiers. Meta-PseU substantially improved model generalizability, overcoming a key limitation of existing approaches. It greatly outperformed state-of-the-art predictors and achieved increasing accuracy with increasing sequence length. CONCLUSIONS: Long-sequence datasets were newly constructed as benchmarks for RNA &#x3a8;-site prediction. Meta-PseU offers a new framework for robust &#x3a8;-site identification by using long sequences.

Pseudouridine

Executive function in alcohol use disorder with low psychiatric comorbidity: Comparison with a non-clinical sample and predictive value for treatment outcome.

BACKGROUND: Executive functions (EF) encompass abilities such as planning, decision-making, and inhibitory control, critical for learning, establishing and maintaining behavioral change. The association between alcohol use disorder (AUD) and impairments in EF are well established. However, prior research is dominated by studies on convenience samples including individuals with severe AUD with high levels of psychiatric comorbidity, which limits generalizability. The present study therefore aimed to investigate the degree of impairment and predictive ability of EF, on alcohol consumption, among individuals with moderate AUD with low levels of psychiatric comorbidity. METHODS: Adults with moderate AUD (n&#x2009;=&#x2009;147) were recruited at three specialized addiction outpatient clinics in Stockholm, to a randomized controlled trial investigating the efficacy of two psychological treatments. Participants underwent neuropsychological testing before treatment. Eight tests from the CANTAB&#xae; battery were administered at baseline, assessing mental flexibility, sustained attention, visuospatial working memory, response inhibition, and delay discounting. Assessments of alcohol use and related symptoms were conducted at baseline, the 12- and 26-weeks follow-up. A non-clinical reference sample (n&#x2009;=&#x2009;72) completed corresponding CANTAB&#xae; tests. The two groups were compared regarding EF using descriptive statistics and t-tests, and the predictive value of EF for reduction in alcohol consumption, was investigated using multiple regression models. RESULTS: Individuals with AUD did not perform worse on any of the tests on executive function (CANTAB&#xae;) as compared to the non-clinical reference sample. Measures of EF were not significant predictors for reduction in alcohol use for the 12-week, or the 26-week follow-up. CONCLUSIONS: EFs were not impaired and were not a clinically relevant predictor of treatment outcomes in this population with AUD. Future research on EF as a predictor in AUD treatment, needs to corroborate the present findings, and include other populations, e.g., with different socio-economic backgrounds and by including other methodologies for measuring EF.

Humans

Vesicoureteral reflux and anorectal malformations.

BACKGROUND: Renal and urinary tract anomalies are frequently associated with anorectal malformations (ARMs) and may adversely affect long-term renal outcomes, if not detected early. However, reliable clinical predictors for significant urologic abnormalities across different ARM phenotypes remain poorly defined. OBJECTIVE: To determine the prevalence and grade distribution of vesicoureteric reflux (VUR) in neonates with ARMs, and to explore its association with renal and urinary tract anomalies, the complexity of the ARM phenotype, and other factors are associated with high-grade VUR. METHODS: In this retrospective cross-sectional study, medical records of 64 neonates diagnosed with ARMs and managed at a tertiary children's hospital between 2018 and 2025 were reviewed. All patients underwent renal and urinary tract ultrasonography. Voiding cystourethrography (VCUG) was performed for all neonates according to our institutional protocol, regardless of ultrasound findings or ARM phenotype. Demographic characteristics, ARM phenotype (less-complex vs. complex), urologic findings, urinary tract infection (UTI) history, and associated anomalies were analyzed. Multivariable logistic regression models were used to identify independent predictors of complex ARM phenotype and high-grade VUR. RESULTS: The cohort consisted of 64 neonates (75% male) with a mean gestational age of 37.36 &#xb1; 1.83 weeks and a mean birth weight of 2940 &#xb1; 601 g. Renal and urinary tract anomalies were common, with hydronephrosis observed in 48.4%, VUR of any grade in 39.1% and hydroureter in 35.9%,of patients. High-grade VUR was identified in 21.9% of patients, and a documented history of UTI was present in 18.8% of the entire cohort. In multivariable analyses, birth weight, presence of VUR, and UTI history were not independently associated with complex ARM phenotype. Additionally, no demographic or clinical variables reliably predicted high-grade VUR. The predictive performance of the regression model for high-grade VUR was limited (AUC = 0.60). CONCLUSION: Renal and urinary tract anomalies are highly prevalent among neonates with ARMs, with VUR representing a prominent finding. The lack of robust clinical predictors for complex ARM phenotype or high-grade VUR underscores the limitations of selective screening strategies and supports the role of comprehensive urologic evaluation in neonates with ARM, regardless of anatomic subtype.

Humans

Beyond predictive performance: A systematic review and critical methodological appraisal of AI/ML and conventional modelling strategies in breast, colorectal, and pancreatic Cancer.

BACKGROUND: Predictive modelling for cancer risk, treatment-related complications, and survival is central to precision oncology. Conventional logistic regression (LR) and Cox proportional hazards (CoxPH) regression remain widely used but are limited when modelling nonlinear interactions, high-dimensional imaging features, and multimodal clinical-metabolic predictors. Artificial intelligence (AI) and machine learning (ML) methods offer expanded capability through automated feature extraction, ensemble learning, and flexible survival modelling, but the evidence on when AI/ML adds value over conventional models across cancer sites and predictive tasks remains fragmented. OBJECTIVE: To systematically evaluate the methodological performance, validation strategies, and translational limitations of AI/ML models compared with conventional statistical models in published predictive-modelling studies for breast, colorectal, or pancreatic cancer. METHODS: PubMed, Scopus, and Web of Science were searched for studies published between January 2019 and March 2025. Two reviewers independently conducted title-and-abstract screening, full-text eligibility assessment, and PROBAST risk-of-bias assessment. Sixty-five studies (n&#xa0;=&#xa0;907,567 participants) were narratively synthesised by cancer site, predictive task, model family, comparator, validation strategy, predictor modality, and calibration or explainability reporting. RESULTS: The 65 studies comprised breast cancer (n&#xa0;=&#xa0;35), colorectal cancer (n&#xa0;=&#xa0;21), and pancreatic cancer (n&#xa0;=&#xa0;9). AI/ML superiority over LR and CoxPH was task- and data-dependent. CNN- and U-Net-based models predominated in imaging and body-composition tasks, tree-based ensembles consistently outperformed LR for tabular perioperative complication prediction, and CoxPH remained competitive, and in the largest pancreatic risk study, superior to XGBoost (C-index 0.802 vs 0.723) in well-structured datasets. PROBAST analysis-domain risk was moderate in 54 of 65 studies (83%), driven by limited external validation, sparse calibration reporting (11/65), and few decision-curve analyses (7/65). CONCLUSION: AI/ML adds the most methodological value in imaging-derived feature extraction and nonlinear perioperative prediction, while conventional regression remains preferable in large, structured datasets with linear predictors. Clinical translation requires standardised body-composition definitions, external validation, calibration assessment, decision-curve analysis, and explainability, in line with TRIPOD+AI and CLAIM standards.

Humans

Application of causal discovery of factors driving dissolved oxygen in estuarine environments.

Dissolved oxygen (DO) concentrations in estuarine bottom waters are a manifestation of multiple, interacting physical and biogeochemical processes, yet identifying their independent contributions remains challenging. Here, we analyze monthly water quality monitoring data from eight stations across Long Island Sound from 1994 to 2022 using a causal discovery framework (PCMCI+) and transformation of forcing variables. Our goal is to identify and isolate variables that causally influence bottom DO and improve predictive models by minimizing overfitting and multicollinearity. PCMCI+ reveals surface-layer temperature as the most important and consistent negative driver of bottom DO, followed by stratification. Wind events exhibit only brief relief by advection and mixing, while river discharge shows no direct causal link to DO, making it less influential than previously thought. Biogeochemical variables, including chlorophyll-a (Chl-a), nitrate and nitrite, and particulate carbon, influence DO through both contemporaneous and time-lagged pathways, often with signs that shift depending on the process. The derived models were evaluated by comparing skill scores, mean squared error, and Akaike Information Criterion. Both model types perform well, with coefficient of determination values exceeding 0.90 at multiple stations using only 3-5 predictors. Our analysis reveals that the best causal predictors are surface-layer temperature, stratification, Chl-a, and particle carbon. This approach provides a scalable framework for improving prediction models and understanding the mechanistic links that control the seasonal variability of DO in estuarine systems.

Estuaries

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

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

Humans

Factors associated with additional intervention requirement following ESWL in pediatric patients with urolithiasis.

OBJECTIVE: To identify predictors of additional intervention following extracorporeal shock wave lithotripsy (ESWL) in pediatric patients and to develop a clinically applicable predictive model. MATERIALS AND METHODS: This retrospective cohort study included 647 pediatric patients who underwent ESWL between 2015 and 2025. Demographic, clinical, and radiological variables were analyzed. Univariable and multivariable logistic regression analyses were performed to identify independent predictors of additional intervention. Model performance was evaluated using receiver operating characteristic curve analysis. RESULTS: Additional intervention was required in 65 patients (10.0%). On multivariable analysis, stone size 10-20 mm (OR: 3.04, p = 0.003), moderate (OR: 2.16, p = 0.049) and severe hydronephrosis (OR: 6.05, p < 0.001), and multiple stones (OR: 3.52, p = 0.030) were identified as independent risk factors. Increasing age (OR: 0.84, p = 0.026), history of urolithiasis (OR: 0.41, p = 0.006), and lower calyx location (OR: 0.14, p = 0.034) were associated with a reduced risk. The model demonstrated good discriminative performance (AUC: 0.794), with a sensitivity of 72% and specificity of 75%. Internal validation using bootstrap resampling demonstrated stable model performance, yielding a corrected AUC of 0.732. CONCLUSION: Stone burden, hydronephrosis severity, and stone multiplicity are key determinants of additional intervention after ESWL in pediatric patients. The proposed model shows good predictive performance and may support individualized risk stratification and clinical decision-making.

Humans

Status of dementia care among healthcare practitioners in Nigerian tertiary hospitals: a cross-sectional study.

BACKGROUND/OBJECTIVES: Dementia is an escalating public health concern globally. This study evaluated the knowledge, attitudes, practices, and perceived barriers to dementia care among healthcare practitioners in Nigerian tertiary hospitals, aiming to identify practitioner-related sociodemographic predictors and systemic barriers affecting dementia care delivery. METHODS: We collected data from May 2024 to May 2025 for this cross-sectional study in 12 purposively selected tertiary hospitals across Nigeria's six geopolitical zones. Participants included physicians, nurses, pharmacists, and other professionals involved in geriatric psychiatric care. Using multistage and convenience sampling, 394 respondents were recruited (response rate: 99.5%). Data were collected via a validated Dementia Care Practice Questionnaire (Cronbach's &#x3b1; = 0.84) and analyzed with SPSS v22. Descriptive statistics, Chi-square tests, and odds ratios (ORs) identified associations (significance: p &#x2264; 0.05). RESULTS: Of 394 respondents, 51.5% were aged &#x2265;40 years, and 54.8% were female. While 62.9% demonstrated adequate knowledge, negative perceptions (51.3%) and attitudes (56.9%) were common. Despite this, 71.3% reported engagement in dementia care, and 75.6% demonstrated appropriate professional help-seeking behaviour when confronted with dementia care challenges. Practitioner-reported barriers included limited training opportunities, geographical barriers affecting patient access to dementia services, and inadequate staffing. Predictors of desirable care practices among healthcare practitioners included age &#x2265;40 years, female gender, Christian affiliation, and &#x2265;5 years of professional experience. CONCLUSION: Although many healthcare practitioners are involved in dementia care, gaps in perceptions, attitudes, and structural support persist. Interventions should focus on targeted training, system strengthening, and policy reform to improve dementia care outcomes.

Barriers to care

Longitudinal functional trajectory and surgical outcomes after intracranial meningioma resection: implications for surgical decision-making in older patients.

OBJECTIVE: As the population ages, meningiomas are increasingly encountered in older patients, yet longitudinal functional outcomes following surgery across age groups remain incompletely characterized. This study evaluated age-related differences in clinical and tumor characteristics, functional trajectory, and surgical outcomes. METHODS: This was a retrospective cohort study of 396 consecutive patients who underwent surgery for intracranial meningiomas at a single academic center between January 2023 and September 2025. Patients were stratified into 5 age groups (< 65, 65-69, 70-74, 75-79, and &#x2265; 80 years). Neurological deficits and Karnofsky Performance Status (KPS) were assessed preoperatively, at discharge, and at last follow-up. Logistic regression analyses identified predictors of prolonged length of stay (LOS) (> 5 days) and poor functional outcome at discharge (KPS < 80). RESULTS: Older patients presented with greater comorbidity burden, larger tumors, and lower preoperative KPS (all p < 0.05), while gross-total resection was achieved at comparable rates across all age groups (p = 0.504). A clinically meaningful inflection point was observed around age 75 years, with KPS < 80 at discharge rising from 7.4% and 9.7% in the < 65-year and 70- to 74-year subgroups and to 36.2% and 57.1% in the 75- to 79-year and &#x2265; 80-year subgroups (p < 0.001), and median LOS increased from 4 days in the younger groups to 9 and 7 days in the 75- to 79-year and &#x2265; 80-year groups (p < 0.001). However, recovery rates among patients who experienced functional decline at discharge were comparable across age strata. On multivariable analysis, independent predictors of prolonged LOS were age &#x2265; 75 years (OR 2.31, p = 0.019), diabetes mellitus (OR 2.85, p = 0.004), posterior fossa location (OR 2.1, p = 0.008), tumor diameter (OR 1.33, p < 0.001), postoperative edema (OR 2.58, p = 0.015), and neurosurgical complications (OR 3.18, p = 0.002). Independent predictors of poor functional outcome at discharge were age &#x2265; 75 years (OR 5.84, p < 0.001), lower preoperative KPS (OR 2.8, p < 0.001), posterior fossa location (OR 3.72, p = 0.003), neurosurgical complications (OR 3.56, p = 0.008), and recurrent meningioma (OR 2.89, p = 0.025). Among 70 endoscopic endonasal approach patients, higher preoperative deficit burden and subtotal resection rates were observed compared to open craniotomy, though overall functional outcomes were comparable. CONCLUSIONS: Surgical risk in meningioma resection increases from age 75 years onwards, yet recovery capacity following initial functional decline remains similar across all age groups. Preoperative functional status, tumor location, comorbidity burden, and recurrence history should guide surgical decision-making rather than age alone.

Humans

Characterizing Caregiver-Child Interactions Through a Transactional Lens: A Baseline Analysis of a Caregiver-Implemented Intervention.

PURPOSE: This study was motivated by the transactional model of development and examined the reciprocal influences that children and caregivers have on caregiver-child interactions (CCXs) prior to a caregiver-implemented intervention. We tested whether child communication characteristics were associated with caregiver strategy use and whether these strategies, in turn, influenced children's communication to understand how caregivers and children mutually shaped the language learning environment. METHOD: Caregiver-child dyads (N = 105) were participants in a randomized controlled trial. CCXs were collected when children were approximately 30 months of age, transcribed, and coded for four caregiver language facilitation strategies and child communication variables. RESULTS: Least Absolute Shrinkage and Selection Operator regression and postselection inference indicated that child communication characteristics in CCXs were associated with both the frequency and type of strategies caregivers used. Children's overall communication acts were significantly associated with caregiver use of vocabulary strategies, whereas children's vocabulary diversity was significantly associated with caregiver use of sentence strategies. Mixed-effects logistic regression demonstrated that all four caregiver strategies significantly increased the likelihood of spontaneous lexical overlap in subsequent child turns. CONCLUSIONS: Prior to the intervention, caregivers and children reciprocally shaped the language environment. This supports a transactional perspective and warrants further consideration of reciprocal influences when assessing the impact of caregiver-implemented interventions. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.32995796.

Humans