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- Title
Triglyceride-glucose index predicts postoperative delirium in elderly patients with type 2 diabetes mellitus: a retrospective cohort study.
- Authors
Sun, Miao; Liu, Min; Zhang, Faqiang; Sang, Lijuan; Song, Yuxiang; Li, Peng; Liu, Siyuan; Yang, Huikai; Ma, Libin; Cao, Jiangbei; Mi, Weidong; Ma, Yulong
- Abstract
Background: Postoperative delirium (POD) is more prevalent among elderly patients with type 2 diabetes mellitus (T2DM). Insulin resistance (IR) can be assessed using the triglyceride-glucose (TyG) index, a novel biomarker. This study aims to investigate the predictive potential of the TyG index for POD in elderly patients with T2DM. Materials and methods: Elderly patients (≥ 65) with T2DM who underwent non-neurosurgery and non-cardiac surgery were enrolled. Univariate and multivariate logistic regression analyses were conducted to assess the association between the TyG index and POD. Additionally, subgroup analyses were performed to compare the sex-specific differences in the predictive ability of the TyG index for POD. Results: A total of 4566 patients were included in this retrospective cohort. The receiver operating characteristic (ROC) curve analysis determined the optimal cut-off value for the TyG index to be 8.678. In the univariate model, a TyG index > 8.678 exhibited an odds ratio (OR) of 1.668 (95% CI: 1.210–2.324, P = 0.002) for predicting POD. In the multivariate regression models, the ORs were 1.590 (95% CI: 1.133–2.252, P < 0.008), 1.661 (95% CI: 1.199–2.325, P < 0.003), and 1.603 (95% CI: 1.137–2.283, P = 0.008) for different models. Subgroup analyses demonstrated that the predictive ability of the TyG index was more pronounced in females compared to males. Conclusion: The TyG index shows promise as a novel biomarker for predicting the occurrence of POD in elderly surgical patients with T2DM.
- Subjects
TYPE 2 diabetes; OLDER patients; GLYCOSYLATED hemoglobin; COHORT analysis; RECEIVER operating characteristic curves; LOGISTIC regression analysis
- Publication
Lipids in Health & Disease, 2024, Vol 23, Issue 1, p1
- ISSN
1476-511X
- Publication type
Article
- DOI
10.1186/s12944-024-02084-2