Rapid Classification and Treatment Algorithm of Cardiogenic Shock Complicating Acute Coronary Syndromes: The SAVE ACS...

Area of Science:

• Cardiology
• Critical Care Medicine
• Health Outcomes Research

Background:

• Acute coronary syndromes (ACS) are a leading cause of mortality.
• Identifying early predictors of mortality in ACS is crucial for timely intervention.
• Cardiogenic shock (CS) complicates ACS and requires rapid risk stratification.

Purpose of the Study:

• To identify independent "frontline" predictors of 30-day mortality in ACS patients.
• To develop a rapid classification system for CS in ACS.
• To propose a management pathway for CS in ACS.

Main Methods:

• Analysis of 11,439 ACS patients treated between 2011-2019.
• Forward conditional logistic regression to identify mortality predictors.
• Validation using a separate cohort of 431 ACS patients (2020).

Main Results:

• Key predictors of 30-day mortality included age, intubation, LV systolic impairment, serum lactate, base excess, and systolic blood pressure.
• The developed SAVE (SBP, Arterial blood gas, and left Ventricular Ejection fraction) ACS classification demonstrated excellent discrimination (AUC 0.879).
• The SAVE classification showed good discrimination for 30-day (AUC 0.814) and long-term mortality, validated in an independent cohort (AUC 0.815).

Conclusions:

• A rapid method for classifying CS in ACS using frontline parameters has been developed.
• The SAVE ACS classification can facilitate future randomized trials on mechanical circulatory support for CS.
• This classification system aids in stratifying CS risk and guiding management in ACS patients.