• Han Chen, Shu-Rong Gong, and Rong-Guo Yu.
• Department of Critical Care Medicine, Fujian Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, No 134, Dongjie Street, Gulou District, Fuzhou, 350001, Fujian, China.
• BMC Anesthesiol. 2022 Mar 25; 22 (1): 79.

BackgroundThe present study aimed to evaluate the association between normalized lactate load, an index that incorporates the magnitude of change and the time interval of such evolution of lactate, and 28-day mortality in sepsis and non-sepsis patients. We also compared the accuracy of normalized lactate load in predicting mortality between these two populations.MethodsData were extracted from the Medical Information Mart for Intensive Care (MIMIC)-IV database. We defined lactate load as the sum of the area under the lactate concentration curve; we also defined normalized lactate load as the lactate load divided by time. The performance of maximum lactate, mean lactate and normalized lactate load in predicting 28-day mortality in sepsis and non-sepsis patients were compared by receiver-operating characteristic curves analysis.ResultsA total of 21,333 patients were included (4219 sepsis and 17,114 non-sepsis patients). Non-survivors had significantly higher normalized lactate load than survivors in sepsis and non-sepsis patients. The maximum lactate, mean lactate, and normalized lactate load AUCs were significantly greater in sepsis patients than in non-sepsis patients. Normalized lactate load had the greatest AUCs in predicting 28-day mortality in both sepsis and non-sepsis patients. Sensitivity analysis showed that the AUC of normalized lactate load increased in non-sepsis patients when more lactate measurement was obtained, but it was not improved in sepsis patients.ConclusionsNormalized lactate load has the strongest predictive power compared with maximum or mean lactate in both sepsis and non-sepsis patients. The accuracy of normalized lactate load in predicting mortality is better in sepsis patients than in non-sepsis patients.© 2022. The Author(s).

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