Association Between the Triglyceride-Cholesterol-Body Weight Index and Cognitive Impairment After Subarachnoid
Tao Xiong1, Guzhalinuer Tuerhong2, Hongyu Wu2
1Department of Cardiovascular Surgery, The Affiliated Hospital of Qingdao University, Qingdao University.
Background:
Poststroke cognitive impairment (PSCI) is a common sequela after subarachnoid hemorrhage (SAH), but practical biomarkers for early risk stratification remain limited. This study investigated the association between the triglyceride-cholesterol-body weight index (TCBI) and cognitive impairment after SAH and evaluated its predictive value.
Methods:
In this retrospective longitudinal cohort study, 252 patients with SAH admitted to the Affiliated Hospital of Qingdao University between March 2024 and June 2025 were initially enrolled. After excluding 24 patients lost to follow-up and 13 with recurrent cerebrovascular events, 215 patients were included in the final analysis. TCBI was calculated as triglycerides×total cholesterol×body weight/1000. Cognitive function was assessed during follow-up using the Montreal Cognitive Assessment, and PSCI was defined as a score <26 after education adjustment. Logistic regression, restricted cubic spline (RCS), receiver operating characteristic (ROC), calibration, and decision curve analyses (DCA) were performed.
Results:
Of the 252 patients with SAH initially enrolled, 215 were included in the final analysis, and 90 (41.9%) developed PSCI. Patients with PSCI were older and had a higher prevalence of hypertension and Hunt-Hess grade ≥3 (all P <0.05). TG, TC, and TCBI levels were significantly lower in the PSCI group (all P <0.001). In logistic regression analyses, TCBI remained significantly associated with PSCI in both the unadjusted model (OR=1.148, 95% CI: 1.026-1.260, P <0.001) and the adjusted model (OR=1.134, 95% CI: 1.022-1.246, P =0.035). Restricted cubic spline analysis showed no significant nonlinear association between TCBI and PSCI risk (P for nonlinear=0.087), although lower TCBI was generally associated with a higher risk of PSCI. TCBI showed the best predictive performance among the tested indicators, with an AUC of 0.744, compared with 0.602 for BW, 0.552 for TG, and 0.495 for TC. Calibration analysis showed good agreement between predicted and observed risk, while decision curve analysis demonstrated greater clinical net benefit for TCBI than for TG, TC, and BW across a wide range of threshold probabilities.
Conclusions:
Lower TCBI was independently associated with a higher risk of cognitive impairment after SAH. As a simple and low-cost index derived from routine clinical variables, TCBI may serve as a useful marker for early cognitive risk stratification in patients with SAH.
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