Lactate indices as predictors of in-hospital mortality or 90-day survival after admission to an intensive care unit in unselected critically ill patients

• Published in: PloS one 2020-03, Vol.15 (3), p.e0229135-e0229135
• Main Authors: Hayashi, Yusuke, Endoh, Hiroshi, Kamimura, Natuo, Tamakawa, Taro, Nitta, Masakazu
• Format: Article
• Language: English
• Subjects: Biology and Life Sciences; Comorbidity; Computer and Information Sciences; Confidence intervals; Critical care; Hospital patients; Hospitals; Intensive care; Lactates; Lactic acid; Mechanical ventilation; Medicine; Medicine and Health Sciences; Mortality; Normal distribution; Patient outcomes; Patients; Physical Sciences; Physiology; Regression analysis; Regression coefficients; Regression models; Renal replacement therapy; Research and Analysis Methods; Sepsis; Statistical analysis; Structured Query Language-SQL; Studies; Survival; Taiwan; University faculty; Ventilation; Ventilators
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0229135

We performed an exclusive study to investigate the associations between a total of 23 lactate-related indices during the first 24h in an intensive care unit (ICU) and in-hospital mortality. Nine static and 14 dynamic lactate indices, including changes in lactate concentrations (Δ Lac) and slope (linear regression coefficient), were calculated from individual critically ill patient data extracted from the Multiparameter Intelligent Monitoring for Intensive Care (MIMIC) III database. Data from a total of 781 ICU patients were extracted, consisted of 523 survivors and 258 non-survivors. The in-hospital mortality rate for this cohort was 33.0%. A multivariate logistic regression model identified maximal lactate concentration at 24h after ICU admission (max lactate at T24) as a significant predictor of in-hospital mortality (odds ratio = 1.431, 95% confidence interval [CI] = 1.278-1.604, p