Abstract
BACKGROUND: Chronic kidney disease (CKD) is an established risk factor for coronary heart disease (CHD). Current CHD diagnostics-coronary angiography or CTA-require contrast agents that may worsen renal function or induce contrast-induced nephropathy. A non-contrast, non-invasive, and relatively accurate method is urgently needed to predict CHD in CKD patients. METHODS: In this retrospective analysis (2020.04-2024.10), patients with CKD were classified into stable CHD or non-CHD groups based on coronary CTA. Carotid ultrasound parameters were collected. Propensity score matching (PSM) controlled for confounders. Logistic regression identified CHD risk factors, and ROC analysis evaluated predictive performance. RESULTS: A total of 377 patients with renal insufficiency were enrolled, most of whom were in CKD stage 2. Among them, 144 patients had stable CHD. After matching, 114 patients per group were analyzed. Carotid plaque number (OR = 2.074, 95% CI: 1.243-3.460, p = 0.005) and maximum plaque length (OR = 1.165, 95% CI: 1.073-1.265, p < 0.001) were significant predictors. AUC values were 0.593 (p = 0.032) for plaque number, 0.696 (p < 0.001) for plaque length, and 0.716 (p < 0.001) for the combined model, with optimal cutoffs of 2.50 plaques and 8.75 mm. CONCLUSION: Carotid plaque number and length are useful predictors of CHD in CKD patients, especially in the early stage. Carotid ultrasound may serve as a non-invasive tool for early detection and improved long-term outcomes in this high-risk population.