OBJECTIVES: The goal of this study was to evaluate the prognostic value of global longitudinal strain (GLS) derived from cardiac magnetic resonance (CMR) feature-tracking in a large multicenter population of patients with preserved ejection fraction.
BACKGROUND: Ejection fraction is the principal parameter used clinically to assess cardiac mechanics and provides prognostic information. However, significant abnormalities of myocardial deformation can be present despite preserved ejection fraction. CMR feature-tracking techniques now allow assessment of strain from routine cine images, without specialized pulse sequences. Whether abnormalities of strain measured by using CMR feature-tracking have prognostic value in patients with preserved ejection fraction is unknown.
METHODS: Consecutive patients with preserved ejection fraction (≥50%) and a clinical indication for CMR at 4 U.S. medical centers were included in this retrospective study. Feature-tracking GLS was calculated from 3 long-axis cine views. The primary endpoint was all-cause death. Cox proportional hazards regression modeling was used to examine the independent association between GLS and death. The incremental prognostic value of GLS was assessed in nested models.
RESULTS: Of the 1,274 patients in this study, 115 died during a median follow-up of 6.2 years. By Kaplan-Meier analysis, patients with GLS ≥ median (-20%) had significantly reduced event-free survival compared with those with GLS < median (log-rank test, p < 0.001). By Cox multivariable regression modeling, each 1% worsening in GLS was associated with a 22.8% increased risk of death after adjustment for clinical and imaging risk factors (hazard ratio: 1.228 per percent; p < 0.001). Addition of GLS in this model resulted in significant improvement in the global chi-square test (94 to 183; p < 0.001) and Harrell's C-statistic (0.75 to 0.83; p < 0.001).
CONCLUSIONS: GLS derived from CMR feature-tracking is a powerful independent predictor of mortality in patients with preserved ejection fraction, incremental to common clinical and imaging risk factors.
Bibliographical noteFunding Information:
Dr. Judd has an equity interest in Heart Imaging Technologies, LLC. Dr. Shah has received salary support from the National Science Foundation (grant CNS-1646566) and the National Institutes of Health (1R01HL137763-01). All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.
© 2020 American College of Cardiology Foundation
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