Predictive value of lymphocyte-to-C-reactive protein ratio for left ventricular thrombus in patients with ST-segment elevation myocardial infarction.

Background and purpose: Current evidence suggested a correlation between inflammation and Left Ventricular Thrombus (LVT). The lymphocyte to C-reactive protein ratio (LCR) has been established as be a reliable inflammation marker and is associated with the prognosis of patients with ST-segment elevation myocardial infarction (STEMI). However, its relationship with the occurrence of LVT remains unclear. This study aims to evaluate the effectiveness of LCR in predicting LVT in patients with STEMI after undergoing primary percutaneous coronary intervention (pPCI).

Methods: A total of 564 STEMI patients who underwent pPCI at the Affiliated Hospital of Xuzhou Medical University from September 2019 to June 2024 were included. Cardiac magnetic resonance imaging (CMR) was used to assess myocardial infarction characteristics and the presence of LVT. The definition of LCR is the lymphocyte to C-reactive protein ratio.

Results: Out of 564 patients, 57 were diagnosed with LVT. The median time for CMR testing was 5 (4, 6) days. Univariate regression analysis showed significant differences in left ventricular ejection fraction (LVEF), peak N-terminal pro B-type natriuretic peptide (peak NT-proBNP), peak high-sensitivity troponin T (peak hsTnT), LCR, Late Gadolinium Enhancement% (LGE%), and Microvascular Obstruction% (MVO%) (p < 0.05). Multivariate regression analysis indicated that LCR was an independent predictor for LVT (P = 0.007, OR: 0.001 95% CI: 0.00-0.123). Receiver operating characteristic (ROC) curve analysis showed that LCR has good predictive ability for LVT (Area under the curve: 0.704, p < 0.001). Integration of integral LCR could significantly improve the discrimination and reclassification accuracy for LVT after STEMI (NRI = 0.517, IDI = 0.030; p < 0.001).

Conclusion: Lower LCR is independently associated with the risk of LVT in patients with STEMI after pPCI. Integration of LCR can significantly improve the risk model for LVT.