Predictive Value of Cardiac Magnetic Resonance for Left Ventricular Remodeling of Patients with Acute Anterior Myocardial Infarction.
Diagnostics (Basel)
; 12(11)2022 Nov 14.
Article
in En
| MEDLINE
| ID: mdl-36428840
Background: Heart failure is a serious complication resulting from left ventricular remodeling (LVR), especially in patients experiencing acute anterior myocardial infarction (AAMI). It is crucial to explore the predictive parameters for LVR following primary percutaneous coronary intervention (PPCI) in patients with AAMI. Methods: A total of 128 AAMI patients who were reperfused successfully by PPCI were enrolled sequentially from June 2018 to December 2019. Cardiovascular magnetic resonance (CMR) was performed at the early stage (<7 days) and after the 6-month follow-up. The patients were divided into LVR and non-LVR groups according to the increase of left ventricular end diastolic volume (LVEDV) measured by the second cardiac magnetic resonance examination ≥20% from baseline. (3) Results: The left ventricular ejection fraction (LVEF), the global longitudinal strain (GLS), the peak circumferential strain in infarcted segments, and the infarct size (IS) remained significantly different in the multivariate logistic regression analysis (all p < 0.05). The area under the receiver operating characteristic curve of Model 1, wherein the GLS was added to the LVEF, was 0.832 (95% CI 0.758−0.907, p < 0.001). The C-statistics for Model 2, which included the infarct-related regional parameters (IS and the peak circumferential strain in infarcted segments)was 0.917 (95% CI 0.870−0.965, p < 0.001). Model 2 was statistically superior to Model 1 in predicting LVR (IDI: 0.190, p = 0.002). (4) Conclusions: Both the global and regional CMR parameters were valuable in predicting LVR in patients with AAMI following the PPCI. The local parameters of the infarct zones were superior to those of the global ones.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Type of study:
Prognostic_studies
/
Risk_factors_studies
Language:
En
Journal:
Diagnostics (Basel)
Year:
2022
Document type:
Article
Affiliation country:
China
Country of publication:
Switzerland