Predictive Value of Monocyte to High-Density Lipoprotein Cholesterol Ratio for Target Lesion Revascularization in Patients With Drug-Eluting Stent Implantation.

Abstract

Background: Severe in-stent restenosis (ISR) following the implantation of drug-eluting stent (DES) can lead to recurrent angina pectoris or even acute myocardial infarction, thereby necessitating target lesion revascularization (TLR). Prior studies have confirmed the correlation between the monocyte to high-density lipoprotein cholesterol ratio (MHR) and ISR after DES implantation. The potential of MHR to predict TLR following DES implantation remains an area of ongoing research and may have significant clinical implications.

Methods: A retrospective analysis was conducted on a consecutive series of 474 patients undergoing DES implantation and follow-up coronary angiography between December 1, 2014 and December 1, 2022. The patients were categorized into two distinct groups according to their exposure to TLR. To assess the predictive performance of the MHR with respect to TLR, we utilized multivariate logistic regression analysis and receiver operating characteristic (ROC) curve analysis.

Results: The study revealed a significant elevation in the MHR value within the TLR group compared to the non-TLR group (12.34 vs 8.97; P < 0.001). MHR was identified as an independent predictor of TLR (Odds Ratio [OR] = 1.162; 95% Confidence Interval [CI]: 1.102-1.225). The area under the curve (AUC) was found to be 0.712 (95% CI: 0.664-0.759). When the MHR exceeded 10.98, the specificity for predicting TLR was 75.8%, and the sensitivity was 58.0%. When the MHR was incorporated into the predictive model comprising established risk factors, there was a notable improvement in the AUC, from 0.689 to 0.749 (P < 0.001). Additionally, there was a significant categorical net reclassification improvement (NRI) of 0.183 (P < 0.001) and an integrated discrimination improvement (IDI) of 0.074 (P < 0.001).

Conclusion: The MHR functions as a predictor for TLR subsequent to DES implantation. Incorporating MHR into the predictive model improves the model's accuracy, indicating its potential value for clinical application.