Integration of two-dimensional echocardiography: A novel risk indicator for ST-segment elevation myocardial infarction.

Aims: We aim to integrate the parameters of two-dimensional (2D) echocardiography and identify the high-risk population for all-cause mortality in patients with acute ST-segment elevation myocardial infarction (STEMI) undergoing percutaneous coronary intervention (PCI).

Methods: The study involved a retrospective cohort population with STEMI who were admitted to Yongchuan Hospital of Chongqing Medical University between January 2016 and January 2019. Baseline data were collected, including 2D echocardiography parameters and left ventricular ejection fraction (LVEF).

Association between TyG index and long-term prognosis of patients with ST-segment elevated myocardial infarction undergoing percutaneous coronary intervention: a retrospective cohort study.

Objective: To assess the association between the serum triglyceride-glucose product index (TyG index) and the risk for all-cause mortality in patients with ST-segment elevated myocardial infarction (STEMI).

Design: Retrospective.

Setting And Participants: This retrospective study included 896 patients with STEMI who underwent percutaneous coronary intervention (PCI) at a comprehensive university-affiliated hospital between January 2016 and January 2019.

Impact of left atrial diameter on all-cause mortality of patients with STEMI undergoing primary percutaneous coronary intervention.

Objectives: To evaluating the predictive significance of the left atrial diameter in acute ST elevation myocardial infarction (STEMI) patients undergoing primary percutaneous coronary intervention (PCI).

Methods: The STEMI population came from 2 retrospective cohorts with 1097 patients, cohorts A (YongChuan Hospital) and cohorts B (Taizhou First People's Hospital). Within 3 days (cohort A) or 5 days (cohort B) post-PCI, patients underwent ultrasound evaluations.

Machine learning-based in-hospital mortality risk prediction tool for intensive care unit patients with heart failure.

Objective: Risk stratification of patients with congestive heart failure (HF) is vital in clinical practice. The aim of this study was to construct a machine learning model to predict the in-hospital all-cause mortality for intensive care unit (ICU) patients with HF.

Methods: eXtreme Gradient Boosting algorithm (XGBoost) was used to construct a new prediction model () from the Medical Information Mart for Intensive Care IV database (MIMIC-IV) (training set).

Impact of the De Ritis Ratio on the Prognosis of Patients with Stable Coronary Artery Disease Undergoing Percutaneous Coronary Intervention.

BACKGROUND The aim of this study was to emphasize the impact of the aspartate aminotransferase-to-alanine aminotransferase ratio (De Ritis ratio) on the prognosis of patients with stable coronary artery disease (SCAD) undergoing percutaneous coronary intervention (PCI). MATERIAL AND METHODS Patients with SCAD who underwent elective PCI at Shinonoi General Hospital were included. SCAD was defined as epicardial coronary artery diameter stenosis ≥90% or epicardial coronary artery diameter stenosis ≥75% accompanied by symptoms or stress-induced myocardial ischemia.