PG-HACKER

PG-HACKER predicts the risk of major adverse cardiac and cerebrovascular events (MACCE) in patients with diabetes following acute coronary syndrome (ACS).

Key Features:

• Competing Risks Model: Implements the Fine-Gray competing risks model to estimate incidence and subdistribution hazards for MACCE.
• Risk Factor Integration: Incorporates clinical predictors including gender, age, peripheral arterial disease, left ventricular function, previous congestive heart failure, Killip class, and optimal medical therapy.
• Point-Based Scoring System: Converts the predictive model coefficients into a point-based score for individual risk quantification.
• Cohort Data: Developed from a retrospective cohort of 1,400 consecutive patients admitted for ACS across two centers, with 783 patients experiencing at least one MACCE, 417 deaths, and 143 non-MACCE deaths.

Scientific Applications:

• Risk Stratification: Estimates individual MACCE risk in diabetic patients after ACS to stratify patients by event probability.
• Clinical Management Guidance: Identifies high-risk individuals who may warrant intensified monitoring or therapeutic intervention based on predicted MACCE risk.

Methodology:

Retrospective analysis of 1,400 consecutive ACS patients from two centers with evaluation of clinical predictors using the Fine-Gray competing risks model.