Pulmonary artery elastance as a predictor of hospital mortality in heart failure cardiogenic shock

Aims: The initial bundle of cares strongly affects haemodynamics and outcomes in acute decompensated heart failure cardiogenic shock (ADHF-CS). We sought to characterize whether 24 h haemodynamic profiling provides superior prognostic information as compared with admission assessment and which haemodynamic parameters best predict in-hospital death. Methods and results: All patients with ADHF-CS and with available admission and 24 h invasive haemodynamic assessment from two academic institutions were considered for this study. The primary endpoint was in-hospital death. Regression analyses were run to identify relevant predictors of study outcome. We included 127 ADHF-CS patients [65 (inter-quartile range 52–72) years, 25.2% female]. Overall, in-hospital mortality occurred in 26.8%. Non-survivors were older, with greater CS severity. Among admission variables, age [odds ratio (OR) = 1.06; 95% confidence interval (CI): 1.02–1.11; Padj = 0.005] and CPIRAP (OR = 0.62 for 0.1 increment; 95% CI: 0.39–0.95; Padj = 0.034) were found significantly associated with in-hospital death. Among 24 h haemodynamic univariate predictors of in-hospital death, pulmonary elastance (PaE) was the strongest (area under the curve of 0.77; 95% CI: 0.68–0.86). PaE (OR = 5.98; 95% CI: 2.29–17.48; Padj < 0.001), pulmonary artery pulsatility index (PAPi, OR = 0.77; 95% CI: 0.62–0.92; Padj = 0.013) and age (OR = 1.06; 95% CI: 1.02–1.11; Padj = 0.010) were independently associated with in-hospital death. Best cut-off for PaE was 0.85 mmHg/mL and for PAPi was 2.95; cohort phenotyping based on these PaE and PAPi thresholds further increased in-hospital death risk stratification; patients with 24 h high PaE and low PAPi exhibited the highest in-hospital mortality (56.2%). Conclusions: Pulmonary artery elastance has been found to be the most powerful 24 h haemodynamic predictor of in-hospital death in patients with ADHF-CS. Age, 24 h PaE, and PAPi are independently associated with hospital mortality. PaE captures ventricular (RV) afterload mismatch and PAPi provides a metric of RV adaptation, thus their combination generates four distinct haemodynamic phenotypes, enhancing in-hospital death risk stratification.