Evidence mapPaperPMID 41339400Full record

ArticleScientific reports2025

Early arterial lactate trajectories and mortality risk in critically ill heart failure: a two-cohort trajectory analysis.

Peng-Fei Wang, Cheng-Jian Guan, Qian Chen, Huan Ma, Bing Xiao, Ya-Li Chen

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Article in Scientific reports, 2025. 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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1 · What the graph read from it

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1 citing paper in PubMed.

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5 · Who and what money

Authors and funding

6 authors.

Peng-Fei Wang *Department of Cardiology, The Second Hospital of Hebei Medical University, No.215 Heping West Road, Xinhua District, Shijiazhuang, 050000, People's Republic of China.
Cheng-Jian Guan *Department of Cardiology, The Second Hospital of Hebei Medical University, No.215 Heping West Road, Xinhua District, Shijiazhuang, 050000, People's Republic of China.
Qian ChenDepartment of Physiology, Hebei Medical University, No.361 Zhong Shan East Road, Shijiazhuang, 050017, People's Republic of China.
Huan MaCollege of Integrated Traditional Chinese and Western Medicine, Hebei University of Traditional Chinese Medicine, No.3 Xing Yuan Road, Shijiazhuang, 050000, People's Republic of China.
Bing XiaoDepartment of Cardiology, The Second Hospital of Hebei Medical University, No.215 Heping West Road, Xinhua District, Shijiazhuang, 050000, People's Republic of China. xiaobing@hebmu.edu.cn.
Ya-Li ChenDepartment of Cardiology, The Second Hospital of Hebei Medical University, No.215 Heping West Road, Xinhua District, Shijiazhuang, 050000, People's Republic of China. 26804795@hebmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lactate is widely used as a biomarker of tissue hypoperfusion and illness severity in critically ill patients with heart failure (HF). While static lactate levels have prognostic value, dynamic changes in lactate over time may offer deeper insights into metabolic stress and clinical outcomes. However, the prognostic utility of lactate trajectories remains poorly defined in HF populations. We conducted a retrospective cohort study using the MIMIC-IV (n = 5,261) and MIMIC-III (n = 906) databases to identify distinct early arterial lactate trajectories in ICU-admitted HF patients. Latent class mixed model were used to categorize 72-hour lactate patterns, and association with in-hospital, 28-day, and 1-year mortality were assessed using multivariable logistic and Cox regression models. External validation was performed in the MIMIC-III cohort. Three distinct lactate trajectory classes were identified: low-stable (Class 1, 86.4%), early rise with delayed decline (Class 2, 4.1%), and early decline followed by re-elevation (Class 3, 9.6%). Compared with Class 1, Class 2 had higher in-hospital mortality (OR 6.88, 95% CI 4.86-9.74), 28-day mortality (HR 3.88, 95% CI 3.17-4.75), and 1-year mortality (HR 3.16, 95% CI 2.65-3.78; all P < 0.001). Class 3 also showed higher risks versus Class 1 (OR 3.03, 95% CI 2.32-3.98; 28-day HR 2.20, 95% CI 1.83-2.66; 1-year HR 1.83, 95% CI 1.56-2.15; all P < 0.001). Risks showed a consistent gradient (Class 2 > Class 3 > Class 1) across cohorts. Findings were consistent in the validation cohort. Sensitivity and subgroup analyses confirmed the robustness of these associations. Early arterial lactate trajectories were independently associated with both mortality in critically ill patients with HF. Trajectory-based profiling provides more nuanced prognostic insight than initial lactate values alone and may inform early risk stratification and ICU decision-making.

Indexed as

Heart FailureLactic AcidAgedBiomarkersCritical IllnessFemaleHospital MortalityHumansIntensive Care UnitsMaleMiddle AgedPrognosisRetrospective StudiesRisk FactorsBiomarkersLactic AcidCritical careHeart failureLactate trajectoryLatent class mixed modelMIMIC-IV databaseMortality

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PMID41339400
PMCPMC12675593

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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.