Lipoprotein(a) as an Independent Biomarker of Coronary Complexity: Prevalence, Clinical Correlates, and Diagnostic Utility in a North Indian Acute Coronary Syndrome Cohort

脂蛋白(a)作为冠状动脉复杂性的独立生物标志物:在北印度急性冠状动脉综合征队列中的患病率、临床相关性和诊断效用

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Abstract

Background Despite extensive research on coronary artery disease (CAD), many underlying reasons remain unexplored. Geographic variations warrant focused studies tailored to specific populations. This study was conducted to assess the role of lipoprotein(a) (Lp(a)) in complex CAD among the North Indian cohort with acute coronary syndrome (ACS). Methods This retrospective study included 688 ACS patients confirmed by ECG, cardiac biomarkers, and coronary angiography. They were grouped by Lp(a) levels (≤50 mg/dL and >50 mg/dL) to assess their association with SYNTAX score >22. Multivariate logistic regression evaluated the odds ratio of Lp(a) > 50 mg/dL, and sensitivity and specificity were analysed for different Lp(a) cut-off values. Results In the present study, 207 (30.1%) of participants had elevated Lp(a) levels exceeding 50 mg/dL. Comorbidities and baseline blood parameters were evenly distributed between groups. A SYNTAX score > 22 was observed in 35.7% (n = 74/207) of individuals with Lp(a) > 50 mg/dL, compared to 26.6% (n = 128/481) in those with Lp(a) ≤ 50 mg/dL. On univariate logistic regression, elevated Lp(a) was significantly associated with a high SYNTAX score (OR=1.53; 95% CI:1.08-2.17). This association remained statistically significant after adjustment for traditional cardiovascular risk factors (OR = 1.54; 95% CI: 1.07-2.21; p = 0.02). Sensitivity and specificity analysis identified the >50 mg/dL threshold as the optimal cut-off, yielding a sensitivity and specificity of 63.37% and 75.14%. Conclusion Lp(a) > 50 mg/dL was significantly associated with complex CAD, independent of traditional cardiovascular risk. This cut-off demonstrated good diagnostic performance, with a sensitivity of 63.37%, specificity of 75.14%, and overall accuracy of 71.91%, supporting its role as an independent biomarker for anatomical CAD complexity.

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