Aliment Pharmacol Ther. 2023 Sep 9. doi: 10.1111/apt.17695. Online ahead of print.
BACKGROUND: Point-of-care echocardiography (POC-Echo) is an essential intensive care hemodynamic monitoring tool.
AIMS: To assess POC-Echo parameters [i.e., cardiac index (CI), systemic vascular resistance index (SVRI) and cirrhotic cardiomyopathy (CCM) markers] and serum biomarkers in predicting circulatory failure (need for vasopressors) and mortality in patients with acute-on-chronic liver failure (ACLF) having sepsis-induced hypotension.
METHODS: We performed serial POC-Echo within 6 hours (h) of presentation and subsequently at 24, 48 and 72 h in patients with ACLF and sepsis-induced hypotension admitted to our liver intensive care unit. Clinical data, POC-Echo data and serum biomarkers were collected prospectively.
RESULTS: We enrolled 120 patients [59% men, aged 49 ± 12 years, 56% alcohol-related disease and median MELDNa of 30 (27-32)], of whom 68 (56.6%) had circulatory failure, with overall mortality of 60%. CCM was present in 52.5%. The predictors of circulatory failure were CI (aHR -1.5; p = 0.021), N-terminal brain natriuretic peptide (aHR -1.1; p = 0.007) and CCM markers; e' septal mitral velocity (aHR -0.5; p = 0.039) and E/e' ratio (aHR -1.2; p = 0.045). Reduction in CI by 20% and SVRI by 15% at 72 h predicted mortality with a sensitivity of 84% and 72%, and specificity 76% and 65%, respectively (p < 0.001). The MELD-CCM model and CLIF-CCM model were computed as MELDNa + 1.815 × E/e' (septal) + 0.402 × e' (septal) and CLIF-C ACLF + 1.815 × E/e' (septal) + 0.402 × e' (septal), respectively, based on multivariable logistic regression. Both scores outperformed MELDNa (z-score = -2.073, p = 0.038) and CLIF-C ACLF score (z score = -2.683, p-value = 0.007), respectively, in predicting 90-day mortality.
CONCLUSION: POC-Echo measurements such as CCM markers (E/e' and e' velocity) and change in CI reliably predict circulatory failure and mortality in ACLF with severe sepsis. CCM markers significantly enhanced the CLIF-C ACLF and MELDNa predictive performance.