Bhavya Khattri, Jigar Haria, Vinod Singh
Background Stroke carries substantial mortality and disability, making early prognostic risk stratification important. The Preadmission Comorbidities, Level of Consciousness, Age, and Neurological Deficit (PLAN) score provides a validated bedside approach to estimating adverse prognostic risk in acute ischemic stroke (AIS). The triglyceride-glucose (TyG) index is a simple, inexpensive marker derived from routinely available fasting triglyceride and glucose measurements and may reflect underlying metabolic dysfunction. However, its relationship with prognostic risk assessed by PLAN, and whether this association differs according to diabetes status, remains insufficiently characterized. Objectives This study aims (1) to assess the bivariate correlation between the TyG index and selected biochemical parameters in patients with AIS and (2) to examine the association between the TyG index and the PLAN prognostic score according to diabetes status. Materials and methods This cross-sectional study included 71 consecutive adults with AIS admitted to a tertiary care hospital in India between October 2024 and March 2026. Demographic, clinical, and laboratory data were collected using a structured pro forma. The TyG index was calculated as ln (fasting triglycerides (TG) (mg/dL) × fasting glucose (mg/dL)/2). The PLAN score was assessed during the initial clinical evaluation. Pearson or Spearman correlation analysis was performed based on the data distribution. Results The mean age of participants was 60.96 ± 12.20 years, with 39 (54.9%) males. Hypertension was the most frequent comorbidity (78.9%), followed by smoking (43.7%) and diabetes mellitus (35.2%). The mean TyG index and PLAN score were 9.36 ± 0.60 and 12.99 ± 4.19, respectively. The TyG index demonstrated significant positive correlations with fasting TG (ρ = 0.720), fasting glucose (ρ = 0.881), total cholesterol (ρ = 0.557), LDL-C (r = 0.504), and HbA1c (ρ = 0.348). In contrast, significant negative correlations were observed with hemoglobin (r = -0.242), HDL-C (ρ = -0.458), and serum albumin (ρ = -0.256) (all p < 0.05). A significant positive correlation was observed between the TyG index and PLAN score (r = 0.529, p < 0.0001), which remained significant after adjustment for clinical confounders (partial r = 0.540, 95% CI: 0.342-0.693; p < 0.0001). The association was also significant among diabetic (r = 0.608, p = 0.001) and non-diabetic patients (r = 0.520, p = 0.0002), with no significant TyG index × diabetes interaction (p = 0.306). Conclusions The TyG index showed significant associations with several metabolic and biochemical parameters and demonstrated a moderate positive association with PLAN prognostic risk among patients with AIS. This association persisted after adjustment for major clinical characteristics and was observed in both diabetic and non-diabetic patients, without evidence of effect modification by diabetes status. These findings suggest that the readily available TyG index may provide useful information regarding metabolic risk and its relationship with prognostic risk in AIS. However, the cross-sectional design precludes establishing causality or determining whether the TyG index independently predicts subsequent clinical outcomes. Larger prospective multicenter studies incorporating longitudinal outcomes and comprehensive adjustment for confounding are warranted.