ST Elevation Myocardial Infarction Complicated by Cardiogenic Shock: Systematic Review of Survival Predictors

John King Khoo1, Benjamin Peter Trewin2, Audrey Adji3

  • 1Department of Cardiology, Liverpool Hospital, Sydney, Australia.

Insights

Predictors of mortality in patients with cardiogenic shock complicating ST-elevation myocardial infarction (STEMI-CS) were identified. Key factors include unsuccessful revascularization, reduced ejection fraction, and renal impairment, crucial for improving survival outcomes.

Area of Science:

  • Cardiology
  • Critical Care Medicine

Background:

  • Cardiogenic shock following acute myocardial infarction (MI) significantly reduces survival rates.
  • Improving risk stratification and management requires characterizing predictors of morbidity and mortality.
  • The complex interplay of factors influencing survival in STEMI-CS remains understudied.

Purpose of the Study:

  • To identify key predictors of short-term survival in patients with ST-elevation myocardial infarction complicated by cardiogenic shock (STEMI-CS).
  • To synthesize evidence from observational studies on factors associated with mortality in STEMI-CS.

Main Methods:

  • A systematic literature search was conducted across Embase, MEDLINE, and CINAHL databases.
  • Original studies evaluating predictors of 30-day or in-hospital survival in STEMI-CS were included.
  • Vote counting methodology was employed to identify significant predictors of mortality or survival.

Main Results:

  • Twenty-four observational studies comprising 14,735 patients were analyzed.
  • Key independent predictors of mortality identified include unsuccessful revascularization, reduced left ventricular ejection fraction, and renal impairment.
  • Significant clinical and statistical heterogeneity was noted across the included studies.

Conclusions:

  • Several variables independently increase mortality risk in STEMI-CS populations.
  • Further prospective research is needed to validate multivariate scoring systems incorporating these prognostic domains.
  • Enhanced understanding of these predictors can guide improved risk stratification and patient management.
Abstract