Serial lactate-procalcitonin interaction identifies a high-risk phenotype in 24-h conditional survivors of post-cardiac arrest syndrome: a CART-based analysis.

Objective: To investigate the time-dependent interplay between early metabolic failure and delayed systemic inflammatory response in 24-h conditional survivors of post-cardiac arrest syndrome (PCAS). We aimed to develop a non-linear risk stratification tool using Classification and Regression Tree (CART) analysis based on serial lactate and procalcitonin (PCT) kinetics. Materials and methods: This retrospective cohort study included 158 24-h conditional survivors of PCAS. Arterial lactate levels were monitored at admission (T0), 6 h, 12 h, 24 h, and 48 h, while PCT levels were recorded at T0 and T24. Missing data were handled using multiple imputation by chained equations (MICE). The primary endpoint was in-hospital mortality. A landmark analysis was performed at 24 h to address immortal time bias. Results: The in-hospital mortality rate was 70.9%. Non-survivors exhibited significantly higher rates of non-shockable rhythms, longer CPR durations, and higher APACHE II scores. In the multivariable logistic regression model adjusted for Targeted Temperature Management (TTM), persistent hyperlactatemia at 48 h (T48) remained a significant independent predictor of mortality (OR: 1.92; 95% CI: 1.22-3.01, Conclusion: In 24-h conditional survivors of PCAS, persistent metabolic debt at 48 h is a potent independent biochemical indicator of poor outcome. Integrating serial lactate and PCT kinetics through non-linear CART analysis identifies a high-risk "metabolic-inflammatory failure" phenotype. This model may facilitate early clinical decision-making and guide the escalation to advanced circulatory or extracorporeal support strategies in high-risk patients.