Research Article: Serial lactate–procalcitonin interaction identifies a high-risk phenotype in 24-h conditional survivors of post-cardiac arrest syndrome: a CART-based analysis
Abstract:
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.
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.
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, p =?0.003). Lactate burden (AUC) demonstrated superior prognostic performance compared to baseline T0 measurements (Bootstrap-validated DeLong test, p =?0.019). CART analysis identified a high-risk phenotype (T0 lactate >5?mmol/L AND T24 PCT?>?5.5?ng/mL) associated with a 92% mortality risk (PPV: 91.8%). The CART model showed excellent calibration (Brier score: 0.14) and comparable discrimination to logistic regression (Logistic Regression Brier score: 0.12 vs. CART Brier score: 0.14; AUC: 0.830 vs. 0.842, p =?0.412).
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.
Introduction:
Cardiac arrest (CA), characterized by the abrupt cessation of systemic circulation, remains a leading cause of mortality and morbidity worldwide ( 1 , 2 ). Despite significant advancements in cardiopulmonary resuscitation (CPR) techniques and post-resuscitation care bundles, survival rates remain approximately 10% for out-of-hospital cardiac arrest (OHCA) and 15–20% for in-hospital cardiac arrest (IHCA) ( 3 , 4 ). Even after successful CPR and the return of spontaneous circulation (ROSC), patients admitted to the…
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