Association between iron intake and risk of all-cause mortality in patients with nonalcoholic fatty liver disease: a retrospective study of NHANES

Preoperative Platelet Count Predicts In-Hospital Mortality in Patients Supported With Venoarterial Extracorporeal Membrane Oxygenation: A Single-Center Retrospective Cohort Study.

Handgrip strength as an independent predictor of mortality in chronic kidney disease patients undergoing hemodialysis: A prospective cohort.

Cardiovascular-kidney-metabolic syndrome (CKM) is closely associated with obesity, diabetes, chronic kidney disease (CKD), and cardiovascular disease (CVD). Although the dietary inflammatory index (DII) reflects the inflammatory potential of diet, the relationship between CKM and DII, as well as the potential mediators, remains unclear. This prospective cohort study included adults with complete dietary data from the National Health and Nutrition Examination Survey (NHANES) 2003-2018. DII was ascertained using the 24-hour recall method. Cox models and cubic spline analyses assessed mortality risk, while the mediating role of insulin resistance-related indicators was further investigated by causal mediation analysis. As of December 31, 2019, a total of 2,505 (13.4%) all-cause deaths and 777 (4.1%) cardiovascular deaths were documented in 18,746 adults over a median follow-up of approximately 8years. Highest DII tertile showed increased all-cause mortality (HR=1.24, 95%CI:1.11-1.37) and cardiovascular mortality (HR =1.22, 95%CI:1.01-1.48) versus lowest tertile. RCS analysis showed that mortality risk increased linearly with increasing DII (all-cause mortality: P for overall: <0.001; cardiovascular mortality: P for overall: <0.135). The time-dependent curves show the long-term predictive performance of DII. In addition, TyG-WC and TyG-WHtR mediated 4.69% and 4.18% of all-cause mortality and 13.13% and 13.96% of cardiovascular mortality (both P<0.05) in DII and CKM patients, respectively. Elevated DII was strongly associated with an elevated risk of death in patients with CKM. In addition, the TyG index and its combined indicator of abdominal obesity partially mediated the association between DII and mortality risk in CKM.

To identify factors and preexisting conditions that are associated with overall cancer mortality, lung cancer mortality, and gastrointestinal cancer mortality in patients after acute myocardial infarction (AMI). In total 10,718 AMI patients aged 25 to 74years were evaluated. All cases of AMI that occurred in the study region of the population-based Myocardial Infarction Registry Augsburg during the period from 2000 to 2017 were analyzed. Median follow-up time was 6.6years (IQR 2.8-11.2). Multivariable Cox regression models were calculated for overall cancer mortality (ICD-10: C00-D48), lung cancer mortality (C34), and gastrointestinal cancer mortality (C15-C25). During the study period, 633 patients died from cancer, including 155 deaths from lung cancer and 212 deaths from gastrointestinal cancer. Higher age, current smoking and diabetes were associated with an increased cancer mortality risk in patients after AMI, whereas female sex, never smoking and platelet aggregation inhibitor intake were inversely related to overall cancer mortality. Higher lung cancer mortality in patients after AMI was linked with advanced age and current smoking. For gastrointestinal cancer death in patients after AMI age, diabetes and current smoking were associated with higher risk, whereas female sex, never smoking, platelet aggregation inhibitor and statin intake were inversely associated. Factors already known for preventing cardiovascular disease were inversely associated with cancer mortality after AMI. These findings support the importance of comprehensive patient education regarding a healthy lifestyle following AMI. Overall, physicians targeting secondary prevention after AMI can also highlight the positive effects of these measures on cancer mortality.

In hepatocellular carcinoma (HCC) with cirrhosis, portal hypertension worsens outcomes. Esophagogastroduodenoscopy (EGD), the current screening method for esophageal varices (EVs), is invasive and may delay therapy. We aimed to develop and externally validate non-invasive models to detect EVs and predict hepatic decompensation (bleeding, ascites or hepatic encephalopathy), a major cause of mortality in patients with HCC, using routine contrast-enhanced CT and clinical data. This multicenter retrospective study included 489 patients with unresectable HCC treated with atezolizumab-bevacizumab (AtezoBev) from five French centers, divided into a development cohort (n = 279) and an external validation cohort (n = 210). Arterial-phase contrast-enhanced CTs were processed through a Deep Learning pipeline using a foundation model (HepatoSageCT). Logistic and Cox models generated clinical models and combined models integrating the HepatoSageCT scores with key clinical variables for EVs and hepatic decompensation. Performance was assessed using AUROC, sensitivity, specificity, C-index and cause-specific hazard ratios. Portosystemic shunts (PSS) at imaging identified EVs with an AUROC of 0.78, increasing to 0.84 when combined with HepatoSageCT. A decision algorithm incorporating PSS and HepatoSageCT missed 4.2% of varices needing treatment, compared to 8.4% when using only PSS, while missing 0% of large EVs. HepatoSageCT predicted hepatic decompensation in the validation cohort (C-index: 0.73, hazard ratio: 3.17) with significant stratification (p <0.001), comparable to a composite score of ascites, splenomegaly and HepatoSageCT risk (C-index: 0.73, hazard ratio: 3.48). Patients stratified at higher risk of decompensation by HepatoSageCT also exhibited significantly lower overall survival (p <0.001). HepatoSageCT scores, supplemented with clinical data, enable accurate non-invasive detection of EV in AtezoBev-treated unresectable HCC and stratify patients according to their risk of hepatic decompensation. This approach may reduce unnecessary endoscopies and improve prognostic assessment. The present study demonstrates that foundation models applied to routine CT imaging, when combined with routinely collected features such as the presence of portosystemic shunts, can accurately predict the presence of esophageal varices and the risk of first or further hepatic decompensation in patients with AtezoBev-treated unresectable hepatocellular carcinoma. These findings are particularly relevant for hepatologists and oncologists, as they highlight a promising non-invasive tool for timely risk assessment in a time-sensitive patient population. While prospective validation is warranted, this approach could support more personalized management and care of patients with unresectable hepatocellular carcinoma.

Cardiovascular disease, particularly ischemic heart disease (IHD), is a major cause of morbidity and mortality in patients with type 2 diabetes mellitus (T2DM). Accurate risk prediction is essential, yet the influence of linear versus non-linear feature selection and survival modelling on performance and feature interpretability remains insufficiently explored. We analysed 12,281 patients with T2DM from a university hospital EHR, followed for up to 15years. The outcome was incident IHD, defined by ICD-10 codes. After variance thresholding and multicollinearity filtering, 263 predictors were retained. Features were selected using univariate Cox regression, Random Survival Forest (RSF), and their consensus. Seven survival models (Cox, Ridge Cox, Weibull, RSF, Gradient-Boosted Survival [GBS], Survival SVM, XGBoost) were trained using five-fold cross-validation. Performance was assessed using the concordance index (C-index) and Integrated Brier Score (IBS). Feature importance stability, Spearman rank correlations, and top-20 feature contributions were compared across models. RSF, Weibull, GBS, and SSVM achieved the highest discrimination (C-index up to 0.78) with comparable calibration, whereas XGBoost consistently performed poorest (C-index 0.66-0.68). Linear models produced stable, diffuse feature importance profiles, while non-linear models concentrated importance on a narrower set of dominant predictors. Across all approaches, cardiovascular comorbidities (I10, I50, I15, I11) remained the most influential predictors. Linear models ensured stability and interpretability, whereas non-linear methods enhanced discrimination and calibration but increased variability. Combining linear and non-linear feature selection provided complementary insights for EHR-based risk prediction of IHD in T2DM.

Treatment outcome and its predictors among patients with status epilepticus in Africa: A systematic review and meta-analysis.

Malnutrition and mortality in patients≥75 years with chronic heart failure.

Association between different biomarkers and mortality in moderate or asymptomatic severe aortic stenosis: A systematic review.

Health Insurance Payor Type as a Predictor of Clinical Presentation and Mortality in Patients Undergoing Urgent or Emergent TEVAR for Type B Aortic Dissection: Insights from Society for Vascular Surgery Vascular Quality Initiative Database.

Combined Impact of Cannabinoids and Cocaine on Outcomes of Trauma Patients.

Optimal delivery of enteral protein in the critically ill: A systematic review and meta-analysis of randomised controlled trials.

Forecasting complications: The role of inflammatory indices in acute peripheral vascular pathologies.

Path forward: Cryoablation for colorectal liver metastases.

Inflammatory biomarkers partially explain the association between dietary index for gut microbiota and all-cause and cardiovascular mortality in patients with cardiovascular disease: A prospective cohort study and machine learning model

VEXUS protocol as a prognostic tool in acute heart failure: A systematic review and Bayesian meta-analysis.

Background: Bedside ultrasound is increasingly utilized to assess muscle mass in critically ill patients, providing a noninvasive and real-time tool for early risk stratification. Muscle wasting is known to be associated with adverse outcomes in septic shock, but its prognostic value using ultrasound in this population remains underexplored. This study aimed to investigate the association between changes in rectus femoris cross-sectional area (CSA), assessed by bedside ultrasound, and 28-day mortality in patients with septic shock. Methods: This prospective observational study enrolled adult patients (≥18 years) with septic shock admitted to the intensive care unit (ICU), diagnosed according to Sepsis-3 criteria. Ultrasound assessments of rectus femoris CSA were performed at baseline (day 0), day 4, and day 7 using a linear transducer. The primary outcome was 28-day mortality. Percentage change in CSA was calculated, and its association with mortality was evaluated using multivariable logistic regression and receiver operating characteristic (ROC) analysis. Results: A total of 116 patients were included. The 28-day mortality rate was 20.7%. Rectus femoris CSA decreased significantly over time, with a median reduction of -0.35 cm² (IQR: -0.62 to -0.21) by day 7. The percentage decrease in CSA was significantly greater in non-survivors at both day 4 (-10.0% vs -8.5%, P = .041) and day 7 (-15.4% vs -13.5%, P = .044). In multivariable analysis, percentage CSA loss at day 7 was independently associated with 28-day mortality (OR 0.94, 95% CI 0.88-0.99, P = .036). ROC analysis yielded an area under the curve (AUC) of 0.65 (95% CI 0.52-0.78) for %CSA reduction at day 7, with a -15.28% cut-off showing 66.7% sensitivity and 61.9% specificity. Conclusions: Serial ultrasound assessment of rectus femoris CSA is a feasible and reproducible method for monitoring muscle wasting in septic shock. While the predictive performance was modest, serial ultrasound measurements may serve as a valuable adjunct in early mortality risk stratification in critically ill patients.

Risk Factors Associated with Mortality for Nosocomial and Community-Acquired Spontaneous Bacterial Peritonitis in Patients with Liver Cirrhosis.

Systematic Review of Emergency Severity Index (ESI) triage tool's utility in predicting mortality and critical care unit admission in Emergency Departments.