Predictive value of triglyceride glucose index in acute kidney injury in patients with severe traumatic brain injury
Background At present, the relationship between the Triglyceride-glucose index (TyG index) and Acute kidney injury (AKI) in traumatic brain injury patients in the Intensive Care Unit (ICU) is still unclear. Currently, the relationship between TyG index and AKI occurred within 7 days in the ICU is a...
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Veröffentlicht in: | Scientific reports 2024-10, Vol.14 (1), p.24522-11, Article 24522 |
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Sprache: | eng |
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Zusammenfassung: | Background At present, the relationship between the Triglyceride-glucose index (TyG index) and Acute kidney injury (AKI) in traumatic brain injury patients in the Intensive Care Unit (ICU) is still unclear. Currently, the relationship between TyG index and AKI occurred within 7 days in the ICU is a highly researched and trending topic. Objective In this study, we conducted in-depth exploration of the relationship between the development of AKI in traumatic brain injury (TBI) patients in the ICU and changes in TyG index, as well as its relevance. Methods A cross-sectional study was conducted with a total of 492 individuals enrolled in the Medical Information Mart for Intensive Care IV(MIMIC-IV) database. Multivariate model logistic regression, smoothed curve fitting and forest plots were utilized to confirm the study objectives. The predictive power of the TyG index for outcome indicators was assessed using subject work characteristics (ROC) curves. As well as comparing the Integrated Discriminant Improvement Index and the Net Reclassification Index of the traditional forecasting model with the addition of the TyG index. Results Of all eligible subjects, 55.9% were male and the incidence of AKI was 59.3%. There was a statistically significant difference in the incidence of AKI within 7 days in the ICU between the different TyG index groups. The difference between TyG index and the risk of AKI within 7 days in the ICU remained significant after adjustment for logistic multifactorial modeling (OR = 2.07, 95% CI = 1.41–3.05, P |
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ISSN: | 2045-2322 2045-2322 |
DOI: | 10.1038/s41598-024-75887-z |