DOI DOI https://doi.org/10.1007/s00392-021-01843-w
Background: Cardiogenic shock (CS) can be either a manifestation of the end of life or a transient, life-threatening event requiring advanced therapy. Clinical tools guiding therapy decisions are needed. Existing scores are neither sufficiently sensitive nor specific and were built within selected cohorts, not accounting for the heterogeneity of CS. The aim of this study was to develop a novel clinical score (CSS) predicting 30-day death in unselected patients with CS.
Methods: Within a registry of 1,308 CS patients (49.1 % with acute myocardial infarction) admitted to a tertiary-care hospital between 2009 and 2019, a Cox regression model was fitted to derive the novel CSS, with 30-day all-cause mortality as outcome of interest. CSS’s predictive ability was compared to the IABP-Shock II score, the CardShock score and the STRATIFY score by their respective C-indices.
Results: Based on the Cox regression, 9 predictors were included in the CSS: age, sex, ischemic etiology, systolic blood pressure, heart rate, pH, lactate, glucose and cardiac arrest. The novel CSS had the highest C-index in the overall cohort (0.740 vs. 0.677, 0.683 and 0.659 for IABP-Shock II score, CardShock score and STRATIFY score), in patients with ischemic etiology (0.738 vs. 0.675, 0.689 and 0.641 for IABP-Shock II score, CardShock score and STRATIFY score) and in patients with non-ischemic etiology (0.734 vs. 0.677, 0.669 and 0.672 for IABP-Shock II score, CardShock score and STRATIFY score). External validation data will be acquired soon and reported in the final manuscript.
Conclusions: The novel CSS provides superior and consistent risk prediction for unselected patients with CS. It is based on readily available variables which can be obtained even in critical situations and thus has the potential to guide use of treatments in CS.
Background: Cardiogenic shock (CS) can be either a manifestation of the end of life or a transient, life-threatening event requiring advanced therapy. Clinical tools guiding therapy decisions are needed. Existing scores are neither sufficiently sensitive nor specific and were built within selected cohorts, not accounting for the heterogeneity of CS. The aim of this study was to develop a novel clinical score (CSS) predicting 30-day death in unselected patients with CS.
Methods: Within a registry of 1,308 CS patients (49.1 % with acute myocardial infarction) admitted to a tertiary-care hospital between 2009 and 2019, a Cox regression model was fitted to derive the novel CSS, with 30-day all-cause mortality as outcome of interest. CSS’s predictive ability was compared to the IABP-Shock II score, the CardShock score and the STRATIFY score by their respective C-indices.
Results: Based on the Cox regression, 9 predictors were included in the CSS: age, sex, ischemic etiology, systolic blood pressure, heart rate, pH, lactate, glucose and cardiac arrest. The novel CSS had the highest C-index in the overall cohort (0.740 vs. 0.677, 0.683 and 0.659 for IABP-Shock II score, CardShock score and STRATIFY score), in patients with ischemic etiology (0.738 vs. 0.675, 0.689 and 0.641 for IABP-Shock II score, CardShock score and STRATIFY score) and in patients with non-ischemic etiology (0.734 vs. 0.677, 0.669 and 0.672 for IABP-Shock II score, CardShock score and STRATIFY score). External validation data will be acquired soon and reported in the final manuscript.
Conclusions: The novel CSS provides superior and consistent risk prediction for unselected patients with CS. It is based on readily available variables which can be obtained even in critical situations and thus has the potential to guide use of treatments in CS.
https://dgk.org/kongress_programme/jt2021/aV1365.html