ArticleLipids in health and disease2026
The total cholesterol to high-density lipoprotein cholesterol ratio predicts post-stroke depression: linear association and individualized risk nomogram.
Article in Lipids in health and disease, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundPost-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.
methodsThe 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.
resultsThirty-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.
conclusionsAdmission 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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