SEARCH · Search PubMed

Results for “Predictors”

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.

SourceResearch connectionFrom yearThrough year

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

50 recordsLinked to original sources

PubMed2026

Peripheral immune markers and choroid plexus volumes as predictors of change in depressive symptoms: Insights from the EMBARC study.

Changes in choroid plexus (ChP) volume and peripheral inflammation have been associated with Major Depressive Disorder (MDD), yet their individual and combined impact on depressive symptoms is unclear. This study investigated whether baseline immune markers and ChP volumes predict changes in depressive symptoms during the 8-week treatment period among Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study participants who received either sertraline or placebo. Adults (n = 222) with MDD with peripheral blood samples were included. Circulating chemokines and cytokines were examined using a 40-plex assay. Depressive symptoms were assessed over 8 weeks using the Hamilton Depression Rating Scale (HAMD-17). Principal component analysis (PCA) was used for dimension reduction. Mixed-effects models were used to examine whether immune profiles and ChP volumes, and their interaction predicted HAMD-17, adjusting for demographic/clinical covariates and baseline depression severity. PCA identified three immune profiles. One profile, characterized by higher levels of cytokines and chemokines including IL-6, TNF-α, and IL-1β, was associated with greater depression severity, higher BMI, age, and CRP at baseline. Higher levels of these immune markers were associated with less improvement in depressive symptoms at 8 weeks (estimate = 1.211, p = 0.018) in models adjusting for right and left ChP volume (right ChP model: estimate = 1.034, p = 0.005; left ChP model: estimate = 0.993, p = 0.007). Interactions between immune markers and ChP volumes were not significant. Future investigations are warranted to examine the relationships between immune markers and ChP volume beyond structural changes in the context of depression symptoms.

Adult↗

PubMed2026

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↗

PubMed2026

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 (≤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↗

PubMed2026

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 ≥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↗

PubMed2026

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↗

PubMed2026

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 = 549) and a validation set (n = 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 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 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↗

PubMed2026

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

BACKGROUND AND OBJECTIVES: Pseudouridine (Ψ) represents one of the most abundant and conserved RNA modifications. Ψ 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 Ψ 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 Ψ site predictor. METHODS: New long-sequence datasets were constructed as benchmarks for RNA Ψ-site prediction. The Ψ 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 Ψ-site prediction. Meta-PseU offers a new framework for robust Ψ-site identification by using long sequences.

Pseudouridine↗

PubMed2026

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 ± 1.83 weeks and a mean birth weight of 2940 ± 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↗

PubMed2026

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 = 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 = 35), colorectal cancer (n = 21), and pancreatic cancer (n = 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↗

PubMed2025

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↗

PubMed2026

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↗

PubMed2026

Lower urinary tract evaluation in children with cerebral palsy: A crossectional study.

INTRODUCTION: Cerebral palsy (CP) is a chronic, non-progressive motor disorder affecting voluntary movement and posture. Lower urinary tract (LUT) dysfunction is highly prevalent in children with CP. This study aims to evaluate LUT function in children with CP. MATERIAL AND METHODS: This cross-sectional study was conducted at a tertiary care hospital. Patients aged 5-18 years with established CP diagnosis were included. Evaluation included clinical history, physical examination, urinary ultrasonography with post-void residual (PVR) measurement, and urodynamic studies when indicated. Patients were categorized into three groups; group-1 (LUT dysfunction), group-2 (symptomatic), and group-3 (asymptomatic) for analysis. RESULTS: The study included 97 children with CP (41 girls, 56 boys; median age 8 years). Of the patients, 61.8% were ambulatory (GMFCS I-III) and 38.2% were non-ambulatory (GMFCS IV-V). At least one LUT symptom was detected in 75.3% of patients. Incontinence was the most common symptom at 69.1%. Incontinence prevalence was significantly higher in non-ambulatory patients (81.1% vs 61.7%, p = 0.044). Invasive urodynamics was performed in 19 patients, and LUT dysfunction was diagnosed in 89.5% of them (19.3% of the entire population). Prematurity rate was significantly higher in patients with LUT dysfunction (94.1% vs 64.8%, p = 0.017). Binary logistic regression analysis identified elevated PVR as the strongest independent risk factor for LUT dysfunction (OR = 108, p < 0.001). Abnormal urinary frequency (OR = 14.9, p = 0.022) and quadriplegia (OR = 10.3, p = 0.016) were other independent risk factors. ROC analysis determined the optimal cut-off value for PVR as 19 mL (sensitivity 58.82%, specificity 94.92%). In the intergroup analysis, multinomial logistic regression identified elevated PVR as the strongest predictor (Group-1 vs Group-2: OR = 101; Group-1 vs Group-3: OR = 24, both p < 0.003). Lower gestational age was also an independent risk factor in both comparisons (OR = 1.25-1.26, p < 0.020). DISCUSSION: This study demonstrates LUT dysfunction affects 19.3% of children with CP, strongly correlating with motor impairment severity. Elevated PVR emerged as the strongest independent predictor (OR = 108), offering a practical non-invasive screening tool. Our proposed urodynamic criteria achieved 94.7% diagnostic yield, enabling selective evaluation. Limitations include single-center design and cross-sectional methodology without longitudinal follow-up. These findings support integrating systematic urological assessment into standard CP care for early intervention. CONCLUSION: LUT dysfunction prevalence is high in children with CP, and symptom frequency increases with higher GMFCS levels. Elevated PVR is the strongest predictor, with a clinically applicable cut-off value of 19 mL. Particularly in quadriplegic, non-ambulatory, and premature patients, close follow-up and urodynamic evaluation when necessary should be performed with a multidisciplinary approach.

Humans↗

PubMed2026

Heterogeneity in Teriflunomide Treatment Arms: A Systematic Review and Meta‑Regression of Randomised Multiple Sclerosis Trials.

BACKGROUND: Teriflunomide is widely used as an active comparator in Phase 3 randomised trials for relapsing multiple sclerosis (RMS). Temporal changes in disease activity within teriflunomide-treated cohorts have not been systematically examined. OBJECTIVES: To assess temporal trends in relapse and disability outcomes across teriflunomide arms of Phase 3 multiple sclerosis (MS) trials and identify predictors of between-trial heterogeneity. METHODS: We performed a systematic review and meta-analysis of Phase 3 randomised controlled trials including a teriflunomide arm. PubMed, Scopus, and ClinicalTrials.gov were searched up to October 2025. Annualised relapse rate (ARR) and 12- and 24-week confirmed disability worsening (CDW) were extracted together with baseline characteristics. Risk of bias was assessed using the Cochrane Risk of Bias 2 tool. Random-effects meta-analyses, meta-regression, and sensitivity analyses were performed. RESULTS: Twelve teriflunomide cohorts from eight trials involving 4,900 adults with RMS were included. ARR ranged from 0.11 to 0.37 with substantial heterogeneity (I2 = 94%). Trial start year was inversely associated with ARR and explained a large proportion of between-study variability in exploratory meta-regression analyses. Confirmed disability worsening outcomes also showed substantial heterogeneity with a weaker trend toward lower event rates in more recent trials. CONCLUSION: Teriflunomide-treated trial populations have shifted toward lower relapse activity over time, and trial start year was the principal predictor of between-trial heterogeneity in ARR in exploratory analyses. These findings most plausibly reflect evolving recruitment and diagnostic practices rather than changes in drug efficacy. Accounting for these temporal dynamics is essential when interpreting outcomes from RMS trial using teriflunomide as comparator.

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

Does impulsivity predict treatment outcomes in PTSD with borderline personality disorder features? Results from a randomized clinical trial.

BACKGROUND: Trauma-focused psychotherapies are first-line treatments for posttraumatic stress disorder (PTSD). However, a substantial proportion of clients do not respond adequately or drop out of therapy prematurely. This has sparked interest in identifying individual-level predictors of treatment outcomes, including improvement in PTSD severity and dropout. Impulsivity may be a predictor because it may interfere with key therapeutic processes, such as cognitive restructuring and emotional processing. Consequently, we present a hypothesis-driven secondary analysis of a 15-month randomized clinical trial comparing Dialectical Behavior Therapy for PTSD (DBT-PTSD) and Cognitive Processing Therapy (CPT) in women with childhood abuse-related PTSD and borderline personality disorder features to test whether impulsivity, assessed at baseline, predicts PTSD improvement and dropout. We further explore whether the dimensions of impulsivity (non-planning, attentional impulsivity, and motor impulsivity) differentially affect the outcomes in DBT-PTSD vs. CPT. METHODS: A total of 193 cis women with PTSD related to childhood abuse and borderline personality disorder features were assessed using the Clinician-Administered PTSD Scale (CAPS) and the Barratt Impulsiveness Scale (BIS-10). Separate probit models and general linear models were applied to predict dropout and pre-to-post changes in PTSD severity (ΔCAPS) from total impulsivity and subscale scores, i.e. non-planning, attentional and motor impulsivity. RESULTS: Overall, dropout rates were higher for participants with higher baseline impulsivity scores (p = 0.049), particularly for those with higher non-planning impulsivity (p = 0.012). In participants randomized to CPT improvement in PTSD symptom severity (ΔCAPS) was negatively related to baseline total impulsivity (p = 0.021). In participants randomized to DBT-PTSD this relation was not significant. CONCLUSIONS: The results suggest that impulsivity may predict treatment outcomes. Specifically, patients with elevated impulsivity may be less likely to respond adequately to CPT. If replicated, these findings have implications for personalization of treatment.

Humans↗

PubMed2026

Could the preoperative urethral curve be used to predict immediate urinary continence following Retzius-sparing robot-assisted radical prostatectomy? A retrospective multi-center study.

PURPOSE: Immediate urinary continence (UC) recovery following Retzius-sparing robot-assisted radical prostatectomy (RS-RARP) remains highly variable, highlighting the need for reliable preoperative prediction. We aimed to develop and validate models to identify patients likely to achieve immediate UC recovery following RS-RARP. MATERIALS AND METHODS: A total of 580 prostate cancer patients who underwent RS-RARP from four medical centers were assigned to a training set (n=348), an internal validation set (n=103) and an external validation set (n=129). Independent predictors were identified through univariate analysis and LASSO regression. A nomogram was constructed using multivariate logistic regression. Its performance was evaluated with receiver operating characteristic (ROC) curve, calibration curves, and decision curve analysis. RESULTS: Immediate UC recovery was observed in 84.5% (294/348) of patients in the training cohort, 80.6% (83/103) in the internal validation cohort, and 81.4% (105/129) in the external validation cohort, respectively. Multivariate analysis identified membranous urethral length (MUL) (OR=1.23, P=0.029) and urethral curvature (OR=2.84, P<0.001) as independent predictors, while prostate volume (PV) (OR=0.84, P <0.001) as a protective factor. The nomogram integrating MUL, PV, and urethral curvature demonstrated superior predictive accuracy, with an AUC of 0.87 (95% CI, 0.83-0.91) in the training cohort. The bootstrap-corrected calibration slope was 0.96, and the Brier score was 0.08. Calibration curves and decision curve analysis confirmed the predictive accuracy and clinical utility of the nomogram. CONCLUSIONS: Our study introduces a novel quantitative method for assessing urethral curvature. The mpMRI-based model, integrating urethral curvature and prostate spatial configuration, offers enhanced predictive accuracy for postoperative immediate UC recovery.

Humans↗

PubMed2026

Clinical Utility of Ultra-Widefield Swept-Source OCT for Intraocular Tumors: Comparison With Ultrasonography, SD-OCT, and MRI.

PURPOSE: To evaluate the clinical performance of ultra-widefield swept-source optical coherence tomography (UWF-OCT) in the assessment of choroidal tumors and to compare it with ultrasonography (US), spectral-domain (SD)-OCT, and magnetic resonance imaging (MRI). DESIGN: Retrospective diagnostic comparison. SUBJECTS: Thirty-nine eyes from 39 patients diagnosed with choroidal tumors at a single tertiary referral center. METHODS: This retrospective diagnostic comparison evaluated patients diagnosed with choroidal tumors at a single tertiary referral center between January 2023 and August 2025. All patients underwent UWF-OCT imaging at diagnosis. Tumor measurements obtained with UWF-OCT were compared with US, SD-OCT, and MRI. Comparative analysis among imaging modalities and predictors affecting UWF-OCT applicability was performed. MAIN OUTCOME MEASURES: Tumor thickness (mm) and largest basal diameter (LBD, mm) measurements, and complete measurability rate across different tumor size categories. RESULTS: Thirty-nine eyes from 39 patients (mean age 59.2 ± 16.9 years) were analyzed, including 27 choroidal melanomas (69.2%), 5 metastatic tumors (12.8%), 4 hemangiomas (10.3%), 2 osteomas (5.1%), and 1 (2.6%) indeterminate choroidal melanocytic lesion. UWF-OCT successfully measured both tumor thickness and largest basal diameter (LBD) in 100% (31/31) of small and medium choroidal tumors, substantially outperforming SD-OCT (complete measurement achieved in 63.6% of small tumors, and 0% of medium or large tumors). UWF-OCT measurements were systematically smaller than ultrasonography (thickness: -32.3%, P < .01; LBD: -11.1%, P < .01) and MRI (thickness: -29.2%, P < .01). Mushroom-shaped tumor morphology was the strongest negative predictor of UWF-OCT quality (OR = 0.015, 95% CI 0.001-0.196, P < .01). UWF-OCT's complete measurability was limited in large tumors (12.5%, 1/8). CONCLUSIONS: UWF-OCT provides precise, noninvasive, single-scan assessment of small-to-medium choroidal tumors with detailed structural visualization. It may be particularly useful for dome-shaped tumors, while multimodal imaging with US and MRI remains optimal for complex morphologies. Overall, UWF-OCT represents a valuable tool for diagnosis and treatment planning, with potential utility for longitudinal follow-up in choroidal tumor management.

Humans↗

PubMed2026

Cine-derived mitral annular relaxation velocity for detection of preclinical left ventricular diastolic dysfunction.

OBJECTIVES: Imaging diastolic dysfunction in pre-clinical heart failure (HF) is challenging. We evaluated a novel cardiac MRI (CMR) biomarker, CMR e-prime (CMR-MARV), in patients at risk of HF. METHODS: In this substudy of the PARABLE trial (NCT04687111), 236 patients (71.6 ± 7.7 years, 61.6% male) fulfilling trial-defined ALVDD citeria underwent CMR with measurement of mitral annular relaxation velocity (CMR-MARV) at four mitral annular anchor points. Diastolic strain rates from FT were also assessed. Twenty-five age- and sex-matched controls were included (73.8 ± 3.1 years, 52% male). Group differences were tested with t-tests, diagnostic accuracy with ROC analysis, and predictors of diastolic dysfunction with adjusted logistic regression. RESULTS: Compared with controls, patients had significantly higher indexed maximal left atrial volume (LAVimax), LV end-diastolic and end-systolic volumes, and LV mass (all p < 0.001). Of FT variables, only peak diastolic longitudinal velocity differed between groups (p < 0.001). In multivariate models, CMR-MARV correlated with radial, circumferential, and longitudinal diastolic strain rates, radial and longitudinal diastolic velocities (all p < 0.001), echocardiographic e' (r = 0.20, p = 0.007), LV mass (r = -0.18, p = 0.008), LAVimax (r = -0.18, p = 0.008), and NT-proBNP (r = -0.30, p < 0.0001). LAVimax and CMR-MARV were strongly independently associated with ALVDD (AUC 0.89 and 0.76, respectively; p < 0.0001). A combined model (LAVimax + CMR-MARV) achieved excellent discrimination (AUC 0.91, 95% CI 0.86-0.97, p < 0.0001). Independent predictors included LAVimax, CMR-MARV, and peak diastolic longitudinal velocity (all p < 0.001). CONCLUSION: CMR-MARV provides a simple cine-derived measure of longitudinal relaxation that correlates with established structural and biochemical markers of diastolic burden. Within an at-risk population, it offers incremental functional information beyond conventional parameters and may support multiparametric CMR phenotyping of preclinical diastolic dysfunction.

Aged↗