Serum Lactate Could Predict Mortality in Patients With Spontaneous Subarachnoid Hemorrhage in the Emergency Department

Background: Serum lactate is a useful biomarker for prediction of mortality in critically ill patients. The purpose of this study was to identify if serum lactate could be used as a biomarker for predicting mortality in patients with subarachnoid hemorrhage (SAH) in the emergency department.Methods:...

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Bibliographic Details
Main Authors: Chang Hwan Oh, Jong Won Kim, Geon Ha Kim, Kyeong Ryong Lee, Dae Young Hong, Sang O Park, Kwang Je Baek, Sin Young Kim
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-09-01
Series:Frontiers in Neurology
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Online Access:https://www.frontiersin.org/article/10.3389/fneur.2020.00975/full
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Summary:Background: Serum lactate is a useful biomarker for prediction of mortality in critically ill patients. The purpose of this study was to identify if serum lactate could be used as a biomarker for predicting mortality in patients with subarachnoid hemorrhage (SAH) in the emergency department.Methods: This retrospective study enrolled 189 patients. Baseline demographic data and clinical characteristics of patients were obtained from medical record review. Multiple logistic regression analysis was performed to determine predictor variables significantly associated with mortality. Receiver operating characteristic (ROC) curve analysis was used to evaluate the performance of variables for mortality prediction in SAH.Results: Using multivariate logistic regression analysis, age [OR 1.05; 95% confidence interval (CI) 1.00–1.10; p = 0.037], Hunt and Hess scale score (OR 3.29; 95% CI 1.62–6.70; p = 0.001), serum lactate level (OR 1.33; 95% CI 1.03–1.74; p = 0.032), and serum glucose level (OR 1.01; 95% CI 1.00–1.02; p = 0.049) predicted overall mortality in SAH. The area under the ROC curve (AUC) value for the use of serum lactate level to predict mortality in SAH was 0.815 (95% CI 0.753–0.868) (p < 0.001).Conclusion: Serum lactate may be a useful biomarker for the early prediction of mortality in SAH patients in the emergency department.
ISSN:1664-2295