The association between myocardial scar and the response of moderate ischemic mitral regurgitation to isolated coronary artery bypass grafting

Prognostic Value of Left Atrial Volume and Late Gadolinium Enhancement on Cardiac Magnetic Resonance Imaging in Patients with Coronary Artery Disease and Severe Left Ventricular Dysfunction Underwent CABG

RATIONALE AND OBJECTIVES

This study aims to investigate whether the combination of Left atrial volume (LAV) and late gadolinium enhancement (LGE) is helpful in stratifying the risk in CABG patients with CAD with EF≤ 35%.

MATERIALS AND METHODS

We conducted a retrospective analysis involving 205 CAD patients with EF≤ 35% who underwent CABG. All patients underwent gadolinium-enhanced CMR before surgery. The CMR images were analyzed for LAV, biventricular function, LGE, and left ventricular myocardial strain. Primary endpoint events included all-cause mortality, revascularization, re-hospitalization due to myocardial infarction or heart failure, and stroke after CABG. Multivariable Cox analysis was performed to identify independent risk factors for adverse outcomes. Kaplan-Meier curve analysis with the log-rank test was employed to evaluate survival estimates.

RESULTS

A total of 55 patients reached the primary endpoints. Univariate Cox proportional hazard regression analysis showed that LAV index (LAVi), left ventricular EF (LVEF), right ventricular EF, LGE percent, and global longitudinal strain were significantly associated with the primary outcome (all P < 0.05). Multivariable analysis showed that LAVi (hazard ratio [HR] 1.05, [95% confidence interval (CI) 1.02-1.07], P < 0.001) and LGE percent (HR 1.10, [95% CI 1.06-1.15], P < 0.001) were independently associated with the primary outcome. Kaplan-Meier analysis indicated a significant increase in the risk of endpoint occurrence when patients exhibited LAVi≥ 51.0 mL/m2 and LGE≥ 11.6% (both P < 0.05).

CONCLUSION

For CAD patients with LVEF≤ 35%, the combination of LAVi and LGE percent demonstrated good predictive value for adverse events after CABG. CMR is a helpful tool to risk-stratify patients with severe left ventricular dysfunction undergoing CABG.

Prediction of left ventricular ejection fraction improvement in patients with ischemic cardiomyopathy after coronary artery bypass grafting based on cardiac magnetic resonance

Background

To investigate the risk factors of left ventricular ejection fraction (LVEF) improvement in patients with ischemic cardiomyopathy (ICM) after coronary artery bypass grafting (CABG), and to construct a model that predicts LVEF improvement.

Methods

A retrospective analysis was performed on 106 ICM patients who received CABG and underwent cardiac magnetic resonance (CMR) at Beijing Anzhen Hospital, Capital Medical University from January 2017 to June 2022. Patients were divided into two groups with improved LVEF and no improved LVEF based on the results of postoperative 6-month transthoracic echocardiography. To analyze the risk factors affecting the LVEF non-improvement after CABG and establish a prediction model.

Results

There was LVEF non-improvement in 30.2% (32/106) of patients. Multivariate analysis showed that the number of transmural scar segments and left ventricular end-systolic volume index (LVESVI) were independent risk factors in LVEF non-improvement after CABG [odds ratio (OR) =2.398, 95% confidence interval (CI): 1.607-3.579, P<0.001; OR =1.036, 95% CI: 1.009-1.063, P=0.008]. The model is built and internally verified. ROC showed that the area under the curve (AUC) was 0.866 (95% CI: 0.792-0.940), calibration curve showed that the probability predicted by the model matched well with the clinical results, and decision curve analysis (DCA) showed that the model had good clinical applicability. During the mean follow-up time of 1.5 years, the incidence of major adverse cardiovascular and cerebrovascular events (MACCE) in the LVEF non-improvement group was higher (5.4% vs. 25.0%, P=0.009), and the NYHA grading was higher (P=0.016), when compared to the LVEF improvement group.

Conclusions

The prediction model based on the number of transmural scar segments and LVESVI has good diagnostic efficacy. Our findings help to identify patients with improved LVEF and thus guide the selection of clinical treatment strategies.