Purpose: We co mpared the use of lactate level for predicting 28-day mortality in non-elderly (<65 years) and elderly (≥65 years) sepsis patients who were admitted to an intensive care unit (ICU). A multivariate logistic regression model was established to predict 28-day mortality for each group.Methods: This retrospective study used the Medical Information Mart for Intensive Care Ⅲ, a publicly available database of ICUs. Eligible sepsis patients were at least 18 years-old, hospitalized for at least 24 h, and had lactate levels measured in the ICU. Univariate logistic regression analysis and step-wise multivariable logistic regression models were used to identify factors associated with 28-day mortality.Results: The 28-day mortality was 30.9% among the 2482 patients, and was significantly greater in elderly than non-elderly patients. Within each age group, the lactate level was greater for nonsurvivors than survivors. Among non-survivors, the lactate level was significantly higher for the nonelderly than the elderly. Adjusted logistic regression analysis showed that non-elderly patients with lactate levels of 2.0-4.0 mmol/L and above 4.0 mmol/L had greater risk of death than those with normal lactate levels. For all patients, the stepwise logistic regression model had an area under the receiver operating curve (AUROC) of 0.752; for non-elderly patients, the model had an AUROC of 0.793; for elderly patients, the model had an AUROC of 0.711. The Hosmer-Lemeshow test indicated acceptable goodness-of-fit for each group (P=0.206, P=0.646, and P= 0.482, respectively).Conclusion: In our population of sepsis patients, the lactate level was about 0.9 mmol/L lower in elderly non-survivors than non-elderly survivors. A plasma lactate level above 2.0 mmol/L was an independent risk factor for death at 28-days among non-elderly patients. Our logistic regression models effectively predicted 28-day mortality of sepsis patients in different age groups.No funding was obtained for this study.
Availability of data and materialsThe datasets analyzed during the current study are available in https://github.com/MIT-LCP/mimiccode/tree/master/concepts.