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The total cholesterol to high-density lipoprotein cholesterol ratio predicts post-stroke depression: linear
Xiangqi Kong1, Haobo Wang1, Xinyue Yuan1
1Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, 030032, China.
Background:
Post-stroke depression (PSD) is a common, impactful complication of stroke, yet clinically applicable early prediction tools remain limited. The ratio of total cholesterol to high-density lipoprotein cholesterol (TC/HDL) integrates atherogenic burden and neuroprotective reserve, making it a promising candidate for PSD risk stratification. However, its association with 90-day PSD and utility in predictive models remain unestablished.
Methods:
The primary endpoint was PSD at 90 days after stroke. Multivariable logistic regression assessed TC/HDL-PSD association, and restricted cubic spline (RCS) analysis tested non-linearity. A nomogram was constructed and internally validated, with its performance assessed using decision curve, calibration curves, and receiver operating characteristic analysis.
Results:
Thirty-five point seven percent of patients developed PSD. TC/HDL was an independent predictor of PSD (OR = 1.2726, P = 0.0028), with a linear relationship (no nonlinearity; P = 0.879). The highest TC/HDL quartile correlated with a 136.26% increased PSD risk (OR = 2.3626, P = 0.0190). The nomogram, incorporating TC/HDL, NIHSS, MoCA, sex, and neutrophil count, demonstrated good discrimination and calibration.
Conclusions:
Admission TC/HDL is an independent prognostic marker of 90-day PSD, with a linear dose-response relationship. The internally validated nomogram may assist in risk estimation. However, its clinical applicability remains to be established and requires external validation. Given that TC/HDL is a simple, widely available and low-cost biomarker, these findings may support early risk stratification and preventive psychological care in routine stroke management, particularly in resource-limited clinical settings.
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