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The Predictive Role of Model for End-Stage Liver Disease-Lactate and Lactate Clearance for In-Hospital Mortality Among a National Cirrhosis Cohort.

ABSTRACT: The burden of cirrhosis hospitalizations is increasing. The admission Model for End-Stage Liver Disease-lactate (MELD-lactate) was recently demonstrated to be a superior predictor of in-hospital mortality compared with MELD in limited cohorts. We identified specific classes of hospitalizations where MELD-lactate may be especially useful and evaluated the predictive role of lactate clearance. This was a retrospective cohort study of 1036 cirrhosis hospitalizations for gastrointestinal bleeding, infection, or other portal hypertension-related indications in the Veterans Health Administration where MELD-lactate was measured on admission. Performance characteristics for in-hospital mortality were compared between MELD-lactate and MELD/MELD-sodium (MELD-Na), with stratified analyses of MELD categories (≤15, >15 to <25, ≥25) and reason for admission. We also incorporated day 3 lactate levels into modeling and tested for an interaction between day 1 MELD-lactate and day 3 lactate clearance. MELD-lactate had superior discrimination for in-hospital mortality compared with MELD or MELD-Na (area under the curve [AUC] 0.789 versus 0.776 versus 0.760, respectively; P < 0.001) and superior calibration. MELD-lactate had higher discrimination among hospitalizations with MELD ≤15 (AUC 0.763 versus 0.608 for MELD, global P = 0.01) and hospitalizations for infection (AUC 0.791 versus 0.674 for MELD, global P < 0.001). We found a significant interaction between day 1 MELD-lactate and day 3 lactate clearance; heat maps were created as clinical tools to risk-stratify patients based on these clinical data. MELD-lactate had significantly superior performance in predicting in-hospital mortality among patients hospitalized for infection and/or with MELD ≤15 when compared with MELD or MELD-Na. Incorporating day 3 lactate clearance may further improve prognostication.

SUBMITTER: Mahmud N

PROVIDER: S-EPMC7880877 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description: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.DesignRetrospective observational cohort study.SettingMixed ICU of Leiden University Medical Center, The Netherlands.PatientsCritically 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.InterventionsNone.Measurements and main resultsWe 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%).ConclusionsLactate 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.

Dataset Information

The Predictive Role of Model for End-Stage Liver Disease-Lactate and Lactate Clearance for In-Hospital Mortality Among a National Cirrhosis Cohort.

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