OBJECTIVE: To explore the relationship between the C-reactive protein-triglyceride-glucose index (CTI) and the risk of type 2 diabetes mellitus (T2DM) in women with prior gestational diabetes mellitus (GDM). METHODS: Logistic regression and restricted cubic spline (RCS) analyses were used to explore the relationship between CTI and the risk of T2DM. Subgroup and interaction analyses were conducted to examine the sensitivity of CTI to T2DM risk and its interaction with confounding factors, respectively. Machine learning algorithms were employed to rank variable importance in T2DM. The receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were employed to investigate the clinical value of CTI. RESULTS: CTI showed a significant positive linear association with T2DM, influenced by hyperlipidemia and BMI. CTI was related to T2DM risk among individuals with low-density lipoprotein cholesterol (LDL-C) >130 mg/dL. CTI ranked as the top predictor of T2DM risk. The area under the curve (AUC) of CTI was 0.767 in predicting T2DM. CTI provided a clinical net benefit for predicting T2DM when the threshold probability ranged from 0.18 to 0.64. CONCLUSION: CTI is associated with future T2DM in women with prior GDM, showing a continuous dose-response relationship. Elevated LDL-C may enhance CTI's predictive power.
Qiu-feng et al. (Thu,) studied this question.
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