Predictive value of TyG-BMI, AIP, and postprandial glucose excursion for sarcopenia in patients with type 2 diabetes mellitus
Objective To evaluate the predictive value of triglyceride-glucose body mass index (TyG-BMI), atherogenic index of plasma (AIP), and postprandial glucose excursion (PPGE) for sarcopenia in patients with type 2 diabetes mellitus (T2DM). Methods An observational cohort trial was conducted on 590 h...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Journal of Army Medical University
2025-08-01
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| Series: | 陆军军医大学学报 |
| Subjects: | |
| Online Access: | http://aammt.tmmu.edu.cn/html/202505021.html |
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| Summary: | Objective To evaluate the predictive value of triglyceride-glucose body mass index (TyG-BMI), atherogenic index of plasma (AIP), and postprandial glucose excursion (PPGE) for sarcopenia in patients with type 2 diabetes mellitus (T2DM). Methods An observational cohort trial was conducted on 590 hospitalized T2DM patients (322 males and 268 females) admitted to Department of Endocrinology of the First Affiliated Hospital of Chongqing Medical University between January 2023 and December 2024. General demographic data and key metabolic indicators, including fasting plasma glucose (FPG), postprandial 2-hour plasma glucose (PPG), triglyceride (TG) were collected, and then TyG-BMI, AIP, and PPGE were calculated. Based on the Asian Working Group for Sarcopenia (AWGS) 2019 criteria, they were divided into a sarcopenia group (n=140) and a non-sarcopenia group (n=450). After 1∶1 propensity score matching (PSM), 102 patients with sarcopenia were matched with 102 without. Differences in metabolic indicators FPG, PPG, TyG-BMI, AIP and PPGE were compared between the 2 groups. Spearman correlation analysis was conducted to assess correlations of these indicators with sarcopenia. Conditional logistic regression analysis was performed to identify independent risk factors, and receiver operating characteristic (ROC) curves were plotted to assess predictive performance. An external validation cohort consisting of 192 T2DM patients from Department of Endocrinology of Jiangbei Branch of First Affiliated Hospital of Army Medical University between January 2023 and December 2024 was included to validate the prediction model. Results After PSM, the baseline data of the 2 groups was balanced (P>0.05). The sarcopenia group showed higher levels of PPG, AIP, and PPGE, but lower TyG-BMI value than the non-sarcopenia group (all P=0.001). Spearman correlation analysis revealed that the TyG-BMI was negatively correlated (r=-0.404, P=0.001), whereas AIP and PPGE were positively correlated with concomitant sarcopenia (r=0.280,P=0.001;r=0.372, P=0.001) in the T2DM patients. Conditional logistic regression analysis identified AIP (OR=14.367) and PPGE (OR=1.245) as independent risk factors, while TyG-BMI (OR=0.966) as independent protective factors. ROC curve analysis revealed that the area under the curve (AUC) of the combined model of TyG-BMI, AIP and PPGE in predicting sarcopenia was 0.918, and the AUC value was 0.954 in external validation, with good sensitivity and specificity. Conclusion TyG-BMI, AIP, and PPGE are important metabolic predictors in T2DM patients with sarcopenia. Their combination has good screening value for sarcopenia, and can be applied in external prediction for T2DM patients.
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| ISSN: | 2097-0927 |