PEAL Score to Predict the Mortality Risk of Cardiogenic Shock in the Emergency Department: An Observational Study

Area of Science:

• Cardiology
• Critical Care Medicine
• Health Outcomes Research

Background:

• Cardiogenic shock (CS) has a high in-hospital mortality rate (28-45%).
• Existing prediction models like CardShock and IABP-SHOCK II show modest performance due to population heterogeneity.
• Limited research exists on predictive scores for Asian populations, who often have a higher comorbidity burden.

Purpose of the Study:

• To describe the clinical characteristics of a contemporary Asian CS population.
• To identify key risk factors for mortality in this demographic.
• To develop and validate a novel predictive scoring model for CS mortality.

Main Methods:

• Retrospective observational study of 225 CS patients in Taiwan (2014-2019).
• Patients categorized into acute myocardial infarction-CS (AMI-CS) and heart failure-CS (HF-CS) subgroups.
• Development of a prediction model using hazard ratios and Youden index for cutoff points; assessed using ROC curve analysis.

Main Results:

• Identified four significant predictors of 30-day mortality: low platelet count (<200 × 10^3/μL), reduced LVEF (<40%), advanced age (>71 years), and elevated lactate (>2.7 mmol/L).
• The developed PEAL score demonstrated good predictive performance with an AUC of 0.774 for all patients.
• Subgroup analysis showed strong predictive ability for both AMI-CS (AUC 0.781) and HF-CS (AUC 0.759) populations.

Conclusions:

• The PEAL score, based on platelet counts, LVEF, age, and lactate, effectively predicts 30-day all-cause mortality in Asian CS patients.
• The model shows good performance in both AMI-CS and HF-CS subgroups.
• Initial platelet counts exhibited a significant negative correlation with 30-day mortality risk in CS patients.