ArticleFrontiers in nutrition2025
Triglyceride-glucose-body mass index predicts early-onset acute kidney injury in critically ill patients: a retrospective analysis using the MIMIC-IV database.
Article in Frontiers in nutrition, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Acute kidney injury (AKI) is a common and serious complication in critically ill patients, with metabolic dysfunction playing a crucial role in its pathogenesis. The triglyceride-glucose-body mass index (TyG-BMI) has emerged as a novel marker of insulin resistance and metabolic health. However, the relationship between TyG-BMI and early-onset AKI in critically ill patients remains unclear. The aim of this study was to evaluate the association between TyG-BMI and early-onset AKI in critically ill patients, and identify optimal cutoff thresholds for risk stratification. Methods: This retrospective study analyzed 4,024 critically ill adults from the MIMIC-IV database. Patients were stratified according to TyG-BMI quartiles. Cox proportional hazards models, restricted cubic splines (RCS), and receiver operating characteristic (ROC) analyses were employed to examine associations between TyG-BMI and early-onset AKI. Optimal cutoff values were determined using the Youden index, while net reclassification improvement (NRI) assessed incremental predictive value. Results: Early-onset AKI developed in 2,535 patients (63.0%). Multivariable-adjusted hazard ratios increased across TyG-BMI quartiles, with the highest quartile showing significantly increased risk compared to the lowest (HR 1.40, 95% CI: 1.25-1.58). Risk increased approximately linearly when TyG-BMI exceeded 261.84. The optimal cutoff value was 252.50 (sensitivity 0.604, specificity 0.648). Adding TyG-BMI to traditional risk models improved prediction (NRI = 0.141, 95% CI: 0.024-0.207). Associations were stronger among males, younger patients, those with preserved eGFR, and patients with diabetes or sepsis. Conclusion: Triglyceride-glucose-body mass index independently predicts early-onset AKI in critically ill patients. The threshold of 252.50 offers a reliable reference for risk stratification in ICU settings.
Indexed as
Identifiers
What Socratic holds
Registered trials
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.