Dynamic changes in lactate levels within the first 24 hours in septic patients as a prognostic indicator: A retrospective cohort study utilizing latent class growth analysis

Authors

  • Shifeng Li Department of Intensive Care Medicine, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
  • Tao You Department of Hematopathology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
  • Meili Liu Department of Intensive Care Medicine, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
  • Yan Hao Department of Intensive Care Medicine, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
  • Xinyue Li Department of Intensive Care Medicine, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
  • Zhiyang Wang Department of Intensive Care Medicine, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
  • Fang Huang Department of Intensive Care Medicine, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
  • Jun Wang Department of Intensive Care Medicine, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China https://orcid.org/0000-0001-8708-3096

DOI:

https://doi.org/10.17305/bb.2023.9259

Keywords:

Latent class growth analysis (LCGA), the Medical Information Mart for Intensive Care-IV database (MIMIC IV), lactate, intensive care unit (ICU), mortality

Abstract

Elevated lactate levels are common in sepsis patients. This study aimed to assess the effect of dynamic changes in lactate levels within the first 24 hours following admission on patient prognosis. We extracted data from the Medical Information Mart for Intensive Care (MIMIC)-IV database and classified patients using latent class growth analysis (LCGA). This analysis classified sepsis patients into different groups based on dynamic changes in lactate levels during the initial 24 hours post-admission, dividing this time frame into four periods (0–3 h, 3–6 h, 6–12 h, and 12–24 h). The highest lactate level recorded in each period was then used for patient classification. We subsequently compared the baseline characteristics and outcomes between these different groups. Our study encompassed 7,830 patients, whom LCGA successfully divided into two classes: class 1 (steady lactate class) and class 2 (increasing lactate class). Class 2 demonstrated a worse clinical status at baseline, as indicated by vital signs, disease severity scores, and laboratory results. Importantly, class 2 also had a significantly higher 28-day mortality rate than class 1 (55.6% vs 13.5%, P < 0.001). In conclusion, LCGA effectively categorized sepsis patients into two distinct groups based on their dynamic changes in lactate levels during the first 24 hours post-admission. This methodology has potential utility in clinical practice for managing sepsis patients.

Dynamic changes in lactate levels within the first 24 hours in septic patients as a prognostic indicator: A retrospective cohort study utilizing latent class growth analysis

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Published

03-11-2023

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Section

Translational and Clinical Research

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How to Cite

1.
Dynamic changes in lactate levels within the first 24 hours in septic patients as a prognostic indicator: A retrospective cohort study utilizing latent class growth analysis. Biomol Biomed [Internet]. 2023 Nov. 3 [cited 2024 Feb. 26];23(6):1118–1124. Available from: https://www.bjbms.org/ojs/index.php/bjbms/article/view/9259