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Updated: Oct 8, 2025

A Data-Driven Approach to Quantifying Immune States in Sepsis
Published on: February 7, 2025
Assessment of Metabolic Dysfunction in Sepsis in a Retrospective Single-Centre Cohort
Julien Goutay1, Juliette Perche2, Aurelia Toussaint1
1Division of Intensive Care, University Lille, CHU Lille, Inserm, Institut Pasteur de Lille, U1167, Lille 59000, France.
Objective:
Our primary aim was to assess selected metabolic dysfunction parameters, both independently and as a complement to the SOFA score, as predictors of short-term mortality in patients with infection admitted to the intensive care unit (ICU).
Methods:
We retrospectively enrolled all consecutive adult patients admitted to the eight ICUs of Lille University Hospital, between January 2015 and September 2016, with suspected or confirmed infection. We selected seven routinely measured biological and clinical parameters of metabolic dysfunction (maximal arterial lactatemia, minimal and maximal temperature, minimal and maximal glycaemia, cholesterolemia, and triglyceridemia), in addition to age and the Charlson's comorbidity score. All parameters and SOFA scores were recorded within 24 h of admission.
Results:
We included 956 patients with infection, among which 295 (30.9%) died within 90 days. Among the seven metabolic parameters investigated, only maximal lactatemia was associated with higher risk of 90-day hospital mortality in SOFA-adjusted analyses (SOFA-adjusted OR, 1.17; 95%CI, 1.10 to 1.25; p < 0.001). Age and the Charlson's comorbidity score were also statistically associated with a poor prognosis in SOFA-adjusted analyses. We were thus able to develop a metabolic failure, age, and comorbidity assessment (MACA) score based on scales of lactatemia, age, and the Charlson's score, intended for use in combination with the SOFA score.
Conclusions:
The maximal lactatemia level within 24 h of ICU admission is the best predictor of short-term mortality among seven measures of metabolic dysfunction. Our combined "SOFA + MACA" score could facilitate early detection of patients likely to develop severe infections. Its accuracy requires further evaluation.

