Evidence map›Paper›PMID 40074720›Full record

ArticleRenal failure2025

Utilization of lactate trajectory models for predicting acute kidney injury and mortality in patients with hyperlactatemia: insights across three independent cohorts.

Yipeng Fang, Ying Zhang, Xuejun Shen, Aizhen Dou, Hui Xie, Yunfei Zhang, Keliang Xie

Abstract readMulticenter Study
In one paragraph

Article in Renal failure, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

  1. Review
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  3. Article
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  5. Review
  6. Review
  7. Article
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  9. Article
  10. The new insights of lactate in various kidney diseases.Expert reviews in molecular medicine · 2025
    Review
  11. Article
  12. Article
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4 · The record

Corrections and comments

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.

Yipeng FangDepartment of Critical Care Medicine, Tianjin Medical University General Hospital, Tianjin, China.ORCID 0000-0001-6051-5274
Ying ZhangDepartment of Critical Care Medicine, Tianjin Medical University General Hospital, Tianjin, China.
Xuejun ShenDepartment of Cardiology, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong Province, China.
Aizhen DouDepartment of Critical Care Medicine, Tianjin Medical University General Hospital, Tianjin, China.
Hui XieFirth Clinical College, XinXiang Medical University, Xinxiang, Henan, China.
Yunfei ZhangEditorial Department of Journal, Tianjin Hospital, Tianjin, China.
Keliang XieDepartment of Critical Care Medicine, Tianjin Medical University General Hospital, Tianjin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aims to investigate the association between lactate trajectories and the risk of acute kidney injury (AKI) and hospital mortality in patients with hyperlactatemia. We conducted a multicenter retrospective study using data from three independent cohorts. By the lactate levels during the first 48 h of ICU admission, patients were classified into distinct lactate trajectories using group-based trajectory modeling (GBTM) method. The primary outcomes were AKI incidence and hospital mortality. Logistic regression analysis assessed the association between lactate trajectories and clinical outcomes, with adjusting potential confounders. Patients were divided into three trajectories: mild hyperlactatemia with rapid recovery (Traj-1), severe hyperlactatemia with gradual recovery (Traj-2), and severe hyperlactatemia with persistence (Traj-3). Traj-3 was an independent risk factor of both hospital mortality (all

Indexed as

Acute Kidney InjuryHyperlactatemiaLactic AcidAgedFemaleHospital MortalityHumansIncidenceIntensive Care UnitsLogistic ModelsMaleMiddle AgedPrognosisRetrospective StudiesRisk AssessmentRisk FactorsLactic Acidacute kidney injurygroup-based trajectory modelinghyperlactatemiaLactatemortalitytrajectory

Identifiers

PMID40074720
PMCPMC11905305

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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.