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Lactate indices as predictors of in-hospital mortality or 90-day survival after admission to an intensive care unit in unselected critically ill patients

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  • Yusuke Hayashi
  • Hiroshi Endoh
  • Natuo Kamimura
  • Taro Tamakawa
  • Masakazu Nitta

Abstract

Background: We performed an exclusive study to investigate the associations between a total of 23 lactate-related indices during the first 24h in an intensive care unit (ICU) and in-hospital mortality. Methods: Nine static and 14 dynamic lactate indices, including changes in lactate concentrations (Δ Lac) and slope (linear regression coefficient), were calculated from individual critically ill patient data extracted from the Multiparameter Intelligent Monitoring for Intensive Care (MIMIC) III database. Results: Data from a total of 781 ICU patients were extracted, consisted of 523 survivors and 258 non-survivors. The in-hospital mortality rate for this cohort was 33.0%. A multivariate logistic regression model identified maximal lactate concentration at 24h after ICU admission (max lactate at T24) as a significant predictor of in-hospital mortality (odds ratio = 1.431, 95% confidence interval [CI] = 1.278–1.604, p

Suggested Citation

  • Yusuke Hayashi & Hiroshi Endoh & Natuo Kamimura & Taro Tamakawa & Masakazu Nitta, 2020. "Lactate indices as predictors of in-hospital mortality or 90-day survival after admission to an intensive care unit in unselected critically ill patients," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-14, March.
    • Handle: RePEc:plo:pone00:0229135
    DOI: 10.1371/journal.pone.0229135
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