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Herz · 2026

Correlation of carotid intima-media thickness and lipid indices with SYNTAX score in coronary artery disease: a cross-sectional study.

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Johny Dilip, Belur Hosmane Giridhar, Kodangala Subramanyam, Chakraborty Anirban, Ojha Aditya

Аннотация

BACKGROUND: Carotid intima-media thickness (CIMT) is a widely used noninvasive marker of subclinical atherosclerosis, yet its relationship with angiographic coronary disease complexity, quantified with the SYNTAX score, remains incompletely characterized. This study evaluated the correlations between CIMT, low-density lipoprotein cholesterol (LDL-C), the Atherogenic Index of Plasma (AIP), and SYNTAX score in patients with angiographically confirmed coronary artery disease (CAD) in coastal South India.

METHODS: A total of 115 consecutive patients with proven CAD undergoing elective coronary angiography (≥ 50% stenosis) were enrolled. B‑mode ultrasonography was used to measure CIMT bilaterally. Lipid profiles were obtained from fasting samples, and AIP was computed as log(TG/HDL-C). Pearson correlations, ANOVA, and multivariate logistic regression were used for analysis.

RESULTS: Mean CIMT was positively correlated with both SYNTAX score (r = 0.192, p = 0.039) and LDL‑C (r = 0.207, p = 0.026). SYNTAX scores increased progressively across single-, double-, and triple-vessel disease groups (F = 25.50, p < 0.001). There was no significant association between AIP and either CIMT or SYNTAX score. Inter-rater agreement for SYNTAX score categorization was excellent (Cohen's κ = 0.880, 95% confidence interval [CI]: 0.799-0.960, p < 0.001). On multivariate analysis, only age independently predicted high-complexity CAD (OR = 1.661, 95% CI: 1.077-2.561, p = 0.022).

CONCLUSION: The SYNTAX score increased significantly with increasing vessel involvement, and CIMT was modestly correlated with SYNTAX score and LDL‑C. Age was the sole independent predictor of high-complexity CAD. These preliminary findings suggest that CIMT may have potential as a supplementary marker of coronary complexity, but this requires confirmation in larger, prospective studies before any clinical application can be recommended.

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

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