Association between non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) and the characteristics of carotid artery plaques: a retrospective study and machine learning model construction

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Background Low-echo plaques are closely related to stroke. Non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) is a novel lipid metabolism indicator. This study aims to evaluate the predictive value of NHHR for identifying vulnerable plaques.Methods This study retrospectively collected data from 3,339 patients with carotid plaque. We used multivariable logistic regression and restricted cubic spline (RCS) method to evaluate the association between NHHR and high-risk plaques. The feature variables were determined through Boruta feature selection, and verified using the Shapley Additive Interpretation (SHAP) method. We constructed 9 machine learning model to further explore the ability of NHHR to predict high-risk plaques.Results The results of the multivariable logistic regression analysis showed a significant positive association between NHHR and high-risk plaques: In the three-category model (low/medium-high/high-risk plaques), patients with high NHHR had a 57.3% increased risk of developing high-risk plaques compared to those with low NHHR (OR = 1.573, 95% CI: 1.266–1.955; p < 0.001); while in the binary model (non-high-risk/high-risk plaques), the risk of developing high-risk plaques in the high NHHR group increased by 80.2% (OR = 1.802, 95% CI: 1.369–2.378; p < 0.001). RCS also revealed that NHHR was significantly and linearly associated with high-risk plaques. In machine learning, NHHR could be used as a new non-invasive screening indicator for plaque risk (RF model: AUC = 0.68).Conclusions Higher NHHR is significantly associated with high-risk carotid plaques. NHHR has strong potential as a convenient and non-invasive auxiliary screening indicator, especially suitable for scenarios where ultrasound examination is not accessible or requires frequent monitoring.

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