Evidence map›Paper›PMID 41606597›Full record

ArticleBMC medical informatics and decision making2026

Lactate trajectories and outcomes in critically ill patients with septic shock: a retrospective analysis of the MIMIC-IV database.

Yuanji Ma, Lingyao Du, Hong Tang

Abstract read
In one paragraph

Article in BMC medical informatics and decision making, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Yuanji MaCenter of Infectious Diseases, West China Hospital of Sichuan University, No. 37 GuoXue Alley, Wuhou District, Chengdu, 610041, China.
Lingyao DuCenter of Infectious Diseases, West China Hospital of Sichuan University, No. 37 GuoXue Alley, Wuhou District, Chengdu, 610041, China. n.sync@163.com.
Hong TangCenter of Infectious Diseases, West China Hospital of Sichuan University, No. 37 GuoXue Alley, Wuhou District, Chengdu, 610041, China. htang6198@hotmail.com.

Funding

the 1.3.5 project for disciplines of excellence, West China Hospital, Sichuan University ZYGD23030
6 · The paper itself

Abstract

backgroundStatic measurements of lactate concentrations are insufficient to fully capture the metabolic dynamics that occur during disease progression. We aimed to investigate the lactate trajectories and their association with 7-day and 28-day all-cause mortality in critically ill patients with septic shock.

methodsCritically ill patients with septic shock were obtained from the MIMIC-IV database (v3.1). Latent growth mixture models (LGMM) and smoothed curve fitting were used to investigate lactate trajectories. Multinomial logistic regression models were employed to examine the associations between the characteristics of membership identified by the least absolute shrinkage and selection operator (LASSO) regression and lactate trajectories. Cox regression models were used to investigate the association between lactate trajectories and all-cause mortality.

resultsA total of 2,211 patients with 18,518 lactate measurements collected over the three days following ICU admission were included. The 7-day and 28-day all-cause mortality rates were 26.5% and 35.5%, respectively. Three distinct lactate trajectories were identified: Class 1, “Moderate level with improvement”; Class 2, “High level with improvement”; and Class 3, “High level with deterioration”. In addition to elevated baseline lactate levels, vasopressor use at ICU admission was independently associated with a significantly higher probability of belonging to Class 3. After adjustment for confounding variables, patients in Classes 2–3 exhibited significantly higher 7-day and 28-day mortality risks compared to those in Class 1 (all adjusted HRs (95% CIs) > 1, P < 0.001; all P for trend < 0.001). Integrating the SOFA score with lactate trajectories could significantly enhance the accuracy of the SOFA score in evaluating patient prognosis. The sensitivity analysis confirmed the lactate trajectories and their association with mortality.

conclusionsSignificant heterogeneity in lactate trajectories was observed over the three days following ICU admission among critically ill patients with septic shock. Lactate trajectories were closely associated with patient outcomes and could potentially serve as a dynamic metabolic marker for actionable risk stratification in this population.

Indexed as

Critical IllnessLactic AcidShock, SepticAgedDatabases, FactualFemaleHumansIntensive Care UnitsMaleMiddle AgedRetrospective StudiesLactic AcidIntensive careLactate trajectoryOutcomeRisk factorSeptic shock

Identifiers

PMID41606597
PMCPMC12922257

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.