External validation of organ perfusion pressure as a prognostic marker in cardiogenic shock

The organ perfusion pressure (OPP) is a surrogate for end-organ hypoperfusion and was shown to predict outcomes in a multicenter cohort of cardiogenic shock (CS) patients. This investigation was conducted to externally validate the independent prognostic efficacy of admission OPP in predicting in-hospital mortality in CS.

This was a retrospective analysis of a Multicenter International Registry that enrolled consecutive patients admitted for CS from July 2023 to October 2024. Only patients with CS related to heart failure (HF) or acute myocardial infarction (AMI) were included. Admission OPP was calculated as the difference between mean arterial pressure and central venous pressure. The primary outcome was in-hospital all-cause death.

About 621 patients were considered (mean age 62 ± 13 years; 138 [22.2%] female): 518 (83.4%) patients presented with SCAI stage ≥ C severity. In-hospital all-cause death occurred in 247 (39.8%) individuals. As compared to survivors, nonsurvivors had significantly lower OPP (59 mmHg [IQR 49-69 mmHg] vs 70 mmHg [60-80 mmHg], P-value < .001). In univariable analysis, low OPP (<57 mmHg) was associated with significantly higher in-hospital all-cause mortality (OR 3.20 [95% CI 2.25-4.56], P-value < .001); this result was consistent across both AMI-CS and HF-CS cohorts. In a multivariable logistic regression analysis including age, diabetes, SCAI stage, Sequential Organ Failure Assessment Score, creatinine, lactates, Vasoactive Inotropic Score, OPP, central venous pressure and cardiac arrest, lower OPP significantly predicted the primary outcome (OR per mmHg decrease: 1.03 [95% CI 1.01-1.06], P-value = .020). The C-index for OPP as a predictor of in-hospital mortality was 0.691 (slope = 1.01; intercept = 0.01).

In this multicenter CS cohort, admission OPP was an independent prognostic marker of in-hospital mortality, irrespective of underlying CS etiology. Its inherent simplicity and demonstrated clinical robustness may support its integration into risk stratification and CS protocols.