Rhythm disturbance is the most frequent cardiovascular abnormality of the operative period, and new onset atrial fibrillation carries lasting stroke and mortality risk. We tested whether the autonomic profile of a short intraoperative observation window predicts significant arrhythmia in the minutes that follow. Secondary analysis of the VitalDB Arrhythmia Database, with anesthesiologist adjudicated annotations from 482 surgical cases. A 300 s index window was taken at the start of each annotated segment, with the following 300 s as the outcome window. Cases free of significant arrhythmia during the index window were eligible. The endpoint was incident significant arrhythmia, a composite of atrial and ventricular tachyarrhythmias, atrioventricular block and sinus node dysfunction. Logistic regression, random forest and gradient boosting were compared by repeated stratified cross validation. Of 482 cases, 299 were eligible and 109 (36.5
Stroke-heart syndrome (SHS) significantly affects prognosis in patients with acute ischemic stroke (AIS). Risk stratification tools for in-hospital major adverse cardiovascular events (MACEs) remain limited. This study aimed to develop and validate a nomogram for time-point-specific prediction of in-hospital MACEs in AIS patients using routinely available clinical variables. A total of 871 AIS patients admitted to a tertiary hospital in Urumqi (2020–2023) formed the derivation cohort, and 373 patients (2023–2024) the validation cohort. LASSO-Cox and multivariate Cox regression were used to select predictors and construct a nomogram for predicting MACEs at 3 days, 7 days, and during hospitalization. Discrimination (area under the receiver operating characteristic curve [AUC]), calibration, and decision curve analysis were assessed. X-tile-derived total risk scores defined three risk strata, validated by Kaplan-Meier curves. In the derivation cohort, 124 of 871 patients (14.2
Heart failure (HF) with pulmonary hypertension (PH) is clinically heterogeneous, and conventional classifications based on left ventricular ejection fraction may inadequately capture this heterogeneity. We applied finite mixture model (FMM) clustering to phenotype this population. From the Chang Gung Research Database (2007–2018), we identified 944 patients hospitalized for acute HF with PH (mean pulmonary artery pressure > 20 mmHg on right heart catheterization). FMM clustering was applied to mixed clinical, echocardiographic, laboratory, and hemodynamic variables, and HF hospitalization and cardiovascular (CV) death were compared across phenogroups. Six phenogroups emerged: 2 HF with preserved ejection fraction (HFpEF) phenotypes (phenogroup 1, PH-dominant; phenogroup 2, atrial fibrillation–dominant), a coronary-predominant mixed-ejection-fraction phenotype (phenogroup 3), and 3 HF with reduced ejection fraction (HFrEF) phenotypes (phenogroups 4–6). The HFrEF phenogroups showed survival comparable to HFpEF but higher HF hospitalization, and phenogroup 3 had the highest CV mortality and HF hospitalization (all-cause mortality, 65.4
Pulmonary hypertension (PH) is a progressive condition that may impair daily functioning and increase care needs. However, data on care dependency in patients with PH remain limited. This study aimed to determine the level of care dependency in patients with PH and to identify factors associated with greater dependency. This descriptive, correlational, cross-sectional study included 85 adults with Pulmonary Arterial Hypertension (PAH) or Chronic Thromboembolic Pulmonary Hypertension (CTEPH) followed at PH outpatient clinic between March 2023 and April 2024. Data were collected using the Individual Identification Form, Care Dependency Scale (CDS), and Pulmonary Arterial Hypertension Symptom Scale (PAHSS). Group comparisons, correlation analyses, and hierarchical multiple linear regression were performed. The mean age was 54.47 ± 16.76 years, and 83.5
Proton pump inhibitors (PPIs) are widely used, often without appropriate indication, and have been linked to several adverse outcomes, including possible cardiovascular effects. Whether PPI use is associated with higher predicted cardiovascular risk using validated risk scores remains unclear. This cross-sectional study used 2011–2018 NHANES data and included 4,036 adults without prior cardiovascular disease (CVD) and with complete Atherosclerotic Cardiovascular Disease (ASCVD) and Predicting Risk of Cardiovascular Disease EVENTS (PREVENT) score components. Survey-weighted multivariable linear regression estimated mean differences and 95
