ACEF score and lactate: lifeline predictors in endocarditis valve procedures: insights from a single-center study

• Published in: Clinical research in cardiology 2024-11
• Main Authors: Dinges, Christian, Kremser, Iris, Gansterer, Katja, Rodemund, Niklas, Steindl, Johannes, Hammerer, Matthias, Seitelberger, Rainald, Hoppe, Uta C, Rezar, Richard, Boxhammer, Elke
• Format: Article
• Language: English
• ISSN: 1861-0684; 1861-0692; 1861-0692
• DOI: 10.1007/s00392-024-02573-5

This study aimed to assess the prognostic value of routinely collected laboratory parameters, specifically lactate, troponin-T, and CK-MB, in predicting mortality in patients with surgically treated endocarditis. Additionally, the study evaluated the effectiveness of two mortality scores, EuroSCORE II and ACEF II Score, in this clinical context. We retrospectively analyzed data from 130 patients diagnosed with endocarditis who underwent surgery at a single tertiary center over nine years. The study utilized preoperative mortality scores and laboratory parameters collected within the first 24 h post-surgery. Statistical analyses included AUROC curves, Kaplan-Meier survival analyses, and correlation analyses to determine predictive values and associations with patient outcomes. Among the 130 patients, 28 (21.5%) died within one year post-surgery. Elevated postoperative lactate levels were significantly associated with increased short- and long-term mortality, with AUROC values indicating strong predictive capability. The ACEF II Score also demonstrated significant predictive value for mortality at various time points, outperforming EuroSCORE II. Higher lactate levels and ACEF II Scores correlated with increased hazard ratios for mortality. Kaplan-Meier analyses revealed significant survival differences based on lactate and ACEF II Score thresholds. Postoperative lactate levels and the ACEF II Score are robust predictors of mortality in patients undergoing cardiac surgery for endocarditis. Integrating these parameters into clinical practice can enhance risk stratification and guide therapeutic decisions, improving patient outcomes through personalized care. Further studies are needed to validate these findings across diverse populations and explore additional biomarkers for refined predictive accuracy.