# Remnant cholesterol: a risk stratification aid for coronary artery stenosis severity in patients with type 2 diabetes

## TL;DR

This study shows that remnant cholesterol levels can help predict the severity of coronary artery blockage in type 2 diabetes patients.

## Contribution

The study demonstrates remnant cholesterol's incremental diagnostic value beyond traditional risk factors for coronary artery stenosis in type 2 diabetes.

## Key findings

- Higher remnant cholesterol levels correlate with more severe coronary artery stenosis in type 2 diabetes patients.
- Remnant cholesterol is an independent risk factor for coronary artery stenosis severity (OR = 2.849).
- Adding remnant cholesterol to baseline models improves diagnostic accuracy (AUC increased to 0.790).

## Abstract

To investigate the association between remnant cholesterol (RC) levels and the degree of coronary artery stenosis in patients with type 2 diabetes, and to assess its incremental value in risk stratification.

A retrospective study was conducted on 155 patients with type 2 diabetes diagnosed and treated in the Department of Cardiology at Zhaotong Third People’s Hospital from January 2023 to December 2024. Based on coronary angiography Gensini scores, patients were divided into a mild stenosis group (Gensini < 22 points) and a moderate-to-severe stenosis group (Gensini ≥ 22 points). Clinical characteristics were compared between the two groups. Spearman’s correlation analysis assessed the relationship between RC and Gensini scores. Logistic regression analyzed the association between RC and coronary artery stenosis severity. ROC curves evaluated the diagnostic capability of RC, while NRI and IDI measures assessed its incremental diagnostic value.

The RC in the moderate-to-severe stenosis group was higher than that in the mild stenosis group (P < 0.05). RC showed a positive correlation with the Gensini score (P < 0.05). Multivariate logistic regression analysis indicated that RC was an independent risk factor for the severity of coronary artery stenosis (OR = 2.849, 95% CI: 1.313–6.181, P = 0.008). The AUC for RC in independently identifying coronary artery stenosis was 0.603 (95% CI: 0.514–0.691). Adding RC to the baseline model increased the AUC to 0.790 (95% CI: 0.719–0.860), with statistically significant continuous NRI (0.324, P = 0.039) and IDI (0.032, P = 0.026).

Levels of RC in patients with type 2 diabetes are independently associated with the degree of coronary artery stenosis. Beyond traditional risk factors, RC demonstrates clear incremental value and can serve as an auxiliary indicator for stratifying the risk of coronary artery stenosis.