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Carotid plaque measures predict coronary heart disease in CKD patients

Carotid plaque measures predict coronary heart disease in CKD patients
Photo by Navy Medicine / Unsplash
Key Takeaway
Interpret carotid plaque measures as associations, not proven predictors, in CKD patients.

This retrospective analysis examined 377 patients with chronic kidney disease, most in stage 2, to assess whether carotid plaque measures predict coronary heart disease. Researchers used propensity score matching to create comparable groups of 114 patients each, comparing those with CHD to those without. The study evaluated carotid plaque number and maximum plaque length as predictors.

Carotid plaque number showed a significant association with CHD, with an odds ratio of 2.074 (95% CI: 1.243–3.460, p = 0.005). Maximum plaque length also showed a positive association with an OR of 1.165 (95% CI: 1.073–1.265), though the exact p-value was not reported. No absolute numbers were provided for these outcomes.

Safety and tolerability data were not reported in this analysis. The study's key limitation is its observational, retrospective design, which prevents causal inference despite the use of propensity score matching to control for confounders. Other limitations, funding sources, and conflicts of interest were not reported.

For clinical practice, this analysis suggests carotid plaque measures may have predictive value for CHD in CKD patients, but the retrospective nature means these findings should be interpreted cautiously as associations rather than proven predictors. The study provides no guidance on how these measures might be integrated into clinical decision-making.

Study Details

Study typeCohort
EvidenceLevel 3
PublishedApr 2026
View Original Abstract ↓
BackgroundChronic 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.MethodsIn 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.ResultsA 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 
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