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To investigate the combined predictive value of cardiac magnetic resonance (CMR)-derived global longitudinal strain (GLS) and peripheral blood neutrophil-to-lymphocyte ratio (NLR) for major adverse cardiovascular events (MACEs) following percutaneous coronary intervention (PCI) in patients with first-time acute myocardial infarction (AMI).
In this single-center prospective cohort study, 134 patients with first-time AMI (99 male and 35 female patients aged 33-83 years, mean 60.19±11.7 years) were enrolled between June, 2022 and July, 2025. All the patients underwent PCI and were followed up via outpatient visits or telephone for a median of 538 days post-discharge. The patients were divided into non-MACEs (n=103) and MACEs groups (n=31) for comparison of baseline clinical parameters.
Baseline comparisons revealed that the MACEs group had a significantly older age, higher white blood cell count, neutrophil count, NLR, platelet-to-lymphocyte ratio, and NT-proBNP, and lower monocyte counts (all P<0.05) with had higher Gensini scores and incidences of anterior wall infarction, more frequent left anterior descending artery culprit lesions, but fewer right coronary artery lesions and lower rates of TIMI low-risk chest pain (P<0.05). In patients with MACEs, CMR findings revealed significantly higher frequencies of late gadolinium enhancement, end-systolic volume index, paradoxical motion, and aneurysmal wall formation, decreased left ventricular ejection fraction, and reduced infarct-segment and global radial, circumferential, and longitudinal strains (P<0.05). Multivariate logistic regression identified NLR and GLS as independent predictors for MACEs. ROC curve analysis demonstrated that both GLS (AUC=0.825) and NLR (AUC=0.820) alone had predictive ability for MACEs, but their combination significantly increased the AUC to 0.921 (P< 0.05).
CMR-derived GLS and peripheral blood NLR are both strongly associated with post-PCI prognosis in first-time AMI patients, and their combination allows more accurate prediction of MACEs to facilitate effective early risk stratification and clinical decision-making.
This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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