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Outcome Stratification in Non-ST-Segment Elevation Myocardial Infarction: Standardized Assessment of Left Ventricular
Yaoyuan Xiao1, Xi Li2, Qinghua Fu1
1Department of Cardiology, Hunan Provincial People's Hospital, The First Affiliated Hospital of Hunan Normal University, Clinical Medicine Research Center of Heart Failure of Hunan Province, Hunan Normal University, 410005 Changsha, Hunan, China.
Background:
Left ventricular global longitudinal strain (LVGLS) is a sensitive index of left ventricular systolic function. However, the prognostic value of this metric in patients with acute non-ST-segment elevation myocardial infarction (NSTEMI) has not been fully established.
Methods:
We retrospectively enrolled patients with newly diagnosed NSTEMI at Hunan Provincial People's Hospital between April 2020 and October 2023. All participants underwent transthoracic echocardiography (TTE) within 48 hours before coronary revascularization. Major adverse cardiovascular events (MACEs) were defined as readmission for unstable angina, non-fatal myocardial infarction, readmission for heart failure, or cardiac death.
Results:
We followed 181 patients with NSTEMI for a median of 599 days (interquartile range (IQR): 297-800). MACEs occurred in 40 patients. Patients who experienced MACEs had significantly worse LVGLS than those without events (-11.00 [-13.70, -7.77] vs. -16.10 [-18.90, -13.50]; p < 0.001). In multivariable Cox regression analysis, LVGLS independently predicted MACEs (hazard ratio (HR) = 1.310, 95% confidence interval (CI): 1.172-1.465; p < 0.001). For 12-month risk prediction, adding LVGLS to the baseline clinical model improved discrimination, increasing the area under the curve (AUC) from 0.668 to 0.835. Kaplan-Meier analysis showed a markedly higher risk of MACEs in patients with LVGLS >-13.75% than in those with LVGLS ≤-13.75% (HR = 7.463; 95% CI, 3.831-14.540; p < 0.001).
Conclusions:
LVGLS is a strong, independent predictor of adverse cardiovascular events and may improve early risk stratification in patients with NSTEMI.