Prognostic value of the lactate-albumin ratio and development of a nomogram-based prediction model in patients with acute myocardial infarction–associated cardiogenic shock

Cardiogenic shock (CS) is a serious complication of acute myocardial infarction (AMI), associated with in-hospital mortality rates of more than 40%. There is a lack of accuracy and clinical applicability in the existing risk scores, emphasizing the need for improved prognostic models using novel biomarkers. This study aimed to evaluate the prognostic role of the lactate-to-albumin ratio (LAR) in AMI-CS patients and to construct a nomogram-based model incorporating LAR with conventional clinical indicators. This prospective study enrolled 129 AMI-CS patients admitted to the cardiac care unit of Renmin Hospital (November 2022–December 2024). Patients were divided into survivor (n = 106) and in-hospital mortality (n = 23) groups. Clinical and laboratory data were compared using univariate analysis. Variables with prognostic potential were initially screened using Least Absolute Shrinkage and Selection Operator regression before entering multivariable logistic analysis. A nomogram was constructed using independent predictors and evaluated using receiver operating characteristic–area under the curve (AUC), calibration analysis, Hosmer–Lemeshow testing, and decision curve analysis. LAR, cold and clammy skin, aspartate aminotransferase, C-reactive protein, and left ventricular ejection fraction < 40% emerged as independent predictors of in-hospital mortality. The median (interquartile range) for LAR was significantly higher in the in-hospital mortality group versus the survival group (2.82 [0.93–4.2] vs 0.59 [0.42–1.54]), P = .002. The best cutoff value for LAR was 1.997, with 65% sensitivity and 82% specificity. LAR had an AUC of 0.767, outperforming blood lactate (0.749), and showed strong prognostic value (odds ratio: 1.495, 95% confidence interval: 1.174–1.904, P = .001). The nomogram-based model achieved an AUC of 0.928, outperforming CardShock (0.782), Acute Physiology and Chronic Health Evaluation II (0.727), and blood lactate (0.749). The model demonstrated excellent calibration (mean absolute error: 0.04), and goodness-of-fit was confirmed (Hosmer–Lemeshow P = .648). Decision curve analysis indicated superior clinical usefulness. LAR is a meaningful indicator for early mortality risk in AMI-CS. The proposed nomogram may support faster decision-making and bedside risk evaluation.