Evidence map›Paper›PMID 40589821›Full record

ArticleFrontiers in public health2025

Lactate trajectories and outcomes in patients with sepsis in the intensive care unit: group-based trajectory modeling.

Yu Wei, Jinqiang Zhuang, Jiaqi Li, Zixuan Wang, Jing Wang, Xiaojie Zhang, Junling Leng

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Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

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0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Yu WeiEmergency Department, The Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, China.
Jinqiang ZhuangEmergency Department, The Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, China.
Jiaqi LiEmergency Department, The Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, China.
Zixuan WangSchool of Nursing and·School of Public Health, Yangzhou University, Yangzhou, China.
Jing WangSchool of Nursing and·School of Public Health, Yangzhou University, Yangzhou, China.
Xiaojie ZhangSchool of Nursing and·School of Public Health, Yangzhou University, Yangzhou, China.
Junling LengEmergency Department, The Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Sepsis is highly heterogeneous. Therefore, identifying biomarkers that can stratify patients with sepsis into more homogeneous cohorts to develop individualized treatment and care measures for patients and carry out early intervention to reduce the risk of death and improve the prognosis of patients has become a current research hotspot. Methods: Using the MIMIC-IV database, we analyzed data from 1,575 adult patients with sepsis. Serum lactate levels were measured once daily for 5 consecutive days after admission. The GBTM model was used to stratify the risk of sepsis and explore the relationships between different lactate trajectories and 28-day mortality in septic patients. Results: We report a new method for identifying subphenotypes of sepsis patients based on lactate trajectories. Through group-based trajectory modeling, we identified and validated five groups of sepsis patients with different lactate trajectories, namely, "Low-stable group," "low-slowly declining group," "high-rapidly decline group," "Moderate-slow declining group," and "high-slow decline group." The relationships between sepsis patients with different lactate trajectories and 28-day mortality were explored. Among them, patients with a "Low-stable group" had the lowest in-hospital 28-day mortality. Patients with a "high-slow decline group" had the highest 28-day mortality. Conclusion: In this study, different subtypes of sepsis were successfully identified by analyzing lactate trajectories. Combined with the dynamic changes in lactate levels, the GBTM model was used to stratify patients according to their risk of sepsis. This model provides a theoretical basis for clinicians to evaluate the prognosis of patients using the lactate change trajectory.

Indexed as

Intensive Care UnitsLactic AcidSepsisAdultAgedBiomarkersFemaleHospital MortalityHumansMaleMiddle AgedPrognosisBiomarkersLactic Acidgroup-based trajectory modelinglactatesepsissubphenotypesurvival analysis

Identifiers

PMID40589821
PMCPMC12206821

What Socratic holds

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LicenceCC BY
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Registered trials

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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 Socratic graph.