The Added Value of Lactate and Lactate Clearance in Prediction of In-Hospital Mortality in Critically Ill Patients With Sepsis.
Autor: | Baysan M; Department of Intensive Care, Leiden University Medical Center, Leiden, The Netherlands.; Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands.; Center for Clinical Transfusion Research, Sanquin Research, Leiden, The Netherlands., Baroni GD; Department of Intensive Care, Leiden University Medical Center, Leiden, The Netherlands.; Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands., van Boekel AM; Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands.; Department of Internal Medicine, Leiden University Medical Center, Leiden, The Netherlands., Steyerberg EW; Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands., Arbous MS; Department of Intensive Care, Leiden University Medical Center, Leiden, The Netherlands.; Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands., van der Bom JG; Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands.; Center for Clinical Transfusion Research, Sanquin Research, Leiden, The Netherlands. |
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Jazyk: | angličtina |
Zdroj: | Critical care explorations [Crit Care Explor] 2020 Mar 24; Vol. 2 (3), pp. e0087. Date of Electronic Publication: 2020 Mar 24 (Print Publication: 2020). |
DOI: | 10.1097/CCE.0000000000000087 |
Abstrakt: | We investigated the added predictive value of lactate and lactate clearance to the Acute Physiology and Chronic Health Evaluation IV model for predicting in-hospital mortality in critically ill patients with sepsis. Design: Retrospective observational cohort study. Setting: Mixed ICU of Leiden University Medical Center, The Netherlands. Patients: Critically ill patients adult patients with sepsis who have been admitted to the ICU of Leiden University Medical Center, The Netherlands, from 2006 to January 2018. Interventions: None. Measurements and Main Results: We fitted a baseline model with the Acute Physiology and Chronic Health Evaluation IV predictors and added 13 prespecified combinations of lactate and lactate clearance at 0, 6 and 24 hours after admission to create a set of extended models to compare with the baseline Acute Physiology and Chronic Health Evaluation IV model. Among 603 ICU admissions, 451 patients met the inclusion criteria. A total of 160 patients died in-hospital, of which 106 died in the ICU. Their lactate and lactate clearance measurements were higher at all time points than those of survivors. The Akaike Information Criterion score improved in 10 of 13 prespecified extended models, with best performance for models that included lactate at 24 hours, alone or in combination with lactate at admission or lactate clearance at 24 hours. We compared the observed and predicted probabilities of in-hospital mortality of the baseline Acute Physiology and Chronic Health Evaluation IV model with the best model in our data, lactate at 24 hours added to the Acute Physiology and Chronic Health Evaluation IV model. This resulted in an increase in specificity of 29.9% (95% CI, 18.9-40.9%). Conclusions: Lactate measurements at 24 hours after admission add predictive value to the prediction of mortality with Acute Physiology and Chronic Health Evaluation IV among ICU patients with sepsis. External validation is needed to develop extended prediction models. (Copyright © 2020 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of the Society of Critical Care Medicine.) |
Databáze: | MEDLINE |
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