Association Between Four Non-Insulin-Based Insulin Resistance Indices and the Risk of Post-Stroke Depression

Research suggests that insulin resistance (IR) is associated with acute ischemic stroke (AIS) and depression. The use of insulin-based IR assessments is complicated. Therefore, we explored the relationship between four non-insulin-based IR indices and post-stroke depression (PSD).

A total of 638 consecutive AIS patients were enrolled in this prospective cohort study. Clinical data were collected to compute indices such as the triglyceride glucose (TyG) index, triglyceride glucose-body mass index (TyG-BMI), insulin resistance metabolic score (METS-IR), and triglyceride/high-density lipoprotein cholesterol ratio (TG/HDL-C). One month post-stroke, neuropsychological assessments were conducted using the 17-item Hamilton Depression Scale. Binary logistic regression analysis was performed to explore the relationship between the four non-insulin-based IR indices and PSD.

Ultimately, 381 patients completed the 1-month follow-up, including 112 (29.4%) with PSD. The PSD group exhibited significantly higher levels of the four IR indices compared to the non-PSD group. Logistic regression analysis demonstrated that these indicators were independently associated with PSD occurrence, both before and after adjusting for potential confounders (all P < 0.001). Tertile analyses indicated that the highest tertile group had a greater risk of PSD occurrence than the lowest tertile group for four IR indicators, even after adjusting for potential confounders (all P < 0.05). Restricted cubic spline analysis revealed a linear dose-response relationship between the four IR indices and PSD. In the subgroup analysis, only the TyG index showed a significant interaction with diabetes (P for interaction = 0.014). The area under curve values for the TyG index, TyG-BMI, METS-IR, and TG/HDL-C were 0.700, 0.721, 0.711, and 0.690, respectively.

High TyG index, TyG-BMI, METS-IR, and TG/HDL-C at baseline were independent risk factors for PSD in AIS. Each of these indicators exhibits predictive value for PSD occurrence, aiding in the early identification of high-risk groups.