Evidence map›Paper›PMID 37563796›Full record

ArticleRenal failure2023

Association between triglyceride-glucose index and AKI in ICU patients based on MIMICIV database: a cross-sectional study.

Zihan Jin, Kai Zhang

Abstract read
In one paragraph

Article in Renal failure, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
–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

18 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Observational
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
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

2 authors.

Zihan JinTianjin University of Traditional Chinese Medicine, Tianjin, P.R. China.ORCID 0000-0003-4941-2703
Kai ZhangThe Second Hospital of Jilin University, Changchun, P.R. China.ORCID 0000-0002-4069-6319

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMethods for early prediction of the occurrence of acute kidney injury (AKI) were limited. The relationship between triglyceride glucose index (TyG) and the incidence of acute kidney injury in ICU patients is unclear. This study aims to explore the relationship between the two.

methodsBased on their TyG index, participants from the Intensive Care Medical Information Market IV (MIMIC-IV) were divided into quartiles. A logistic regression model was constructed based on the risk of acute kidney injury as the main outcome, in order to detect a potential relationship that may exist between the TyG index and acute kidney injury in ICU patients. Finally, in order to confirm the relationship existing between the TyG index and the results, a restricted cubic spline model was used.

resultsIn total, 54,263 patients were involved in our present study, of whom 48.2% were male. The occurrence of acute kidney injury was 25.1%. An independent relationship was observed between the TyG index and an increased risk of acute kidney injury through multivariate logistic regression analysis (OR, 1.28 [95% CI 1.22-1.35]

conclusionThe triglyceride glucose index is related to the risk of acute kidney injury in ICU patients. In the future, in order to further validate this finding, larger prospective studies are needed.

Indexed as

Acute Kidney InjuryBiomarkersBlood GlucoseCross-Sectional StudiesFemaleGlucoseHumansIntensive Care UnitsMaleRisk FactorsTriglyceridesBiomarkersBlood GlucoseGlucoseTriglyceridesacute kidney failureICUMIMICTriglyceride glucose index

Identifiers

PMID37563796
PMCPMC10424620

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.