Optimized Prognosis Assessment in ST-Segment-Elevation Myocardial Infarction Using a Cardiac Magnetic Resonance Imaging Risk Score.
作者信息
Stiermaier Thomas, Jobs Alexander, de Waha Suzanne, Fuernau Georg, Pöss Janine, Desch Steffen, Thiele Holger, Eitel Ingo
机构信息
From the University Heart Center Lübeck, Medical Clinic II (Cardiology/Angiology/Intensive Care Medicine), University Hospital Schleswig-Holstein, Lübeck, Germany; and German Center for Cardiovascular Research (DZHK), Partner Site Hamburg/Kiel/Lübeck, Germany.
出版信息
Circ Cardiovasc Imaging. 2017 Nov;10(11). doi: 10.1161/CIRCIMAGING.117.006774.
BACKGROUND
Cardiac magnetic resonance (CMR) demonstrated great potential for the prediction of major adverse cardiac events (MACE) in ST-segment-elevation myocardial infarction. The aim of this study was to develop and validate a CMR-based risk score for ST-segment-elevation myocardial infarction patients.
METHODS AND RESULTS
The scoring model was developed and validated on ST-segment-elevation myocardial infarction cohorts from 2 independent randomized controlled trials (n=738 and n=458 patients, respectively) and included left ventricular (LV) ejection fraction, infarct size, and microvascular obstruction. Primary end point was the 12-month MACE rate consisting of death, reinfarction, and new congestive heart failure. In the derivation cohort, LV ejection fraction ≤47%, infarct size ≥19%LV, and microvascular obstruction ≥1.4%LV were identified as the best cutoff values for MACE prediction. According to the hazard ratios in multivariable regression analysis, the CMR risk score was created by attributing 1 point for LV ejection fraction ≤47%, 1 point for infarct size ≥19%LV, and 2 points for microvascular obstruction ≥1.4%LV. In the validation cohort, the score showed a good prediction of MACE (area under the curve: 0.76). Stratification into a low (0/1 point) and high-risk group (≥2 points) resulted in significantly higher MACE rates in high-risk patients (9.0% versus 2.2%; =0.001). Inclusion of the CMR score in addition to a model of clinical risk factors led to a significant increase of C statistics from 0.74 to 0.83 (=0.037), a net reclassification improvement of 0.18 (=0.009), and an integrated discriminative improvement of 0.04 (=0.010).
CONCLUSIONS
Our approach integrates the prognostic information of CMR imaging into a simple risk score that showed incremental prognostic value over clinical risk factors in ST-segment-elevation myocardial infarction patients.
CLINICAL TRIAL REGISTRATION
URL: http://www.clinicaltrials.gov. Unique identifiers: NCT00712101 and NCT02158468.