Thomas Stiermaier1, Alexander Jobs1, Suzanne de Waha1, Georg Fuernau1, Janine Pöss1, Steffen Desch1, Holger Thiele1, Ingo Eitel2. 1. 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. 2. 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. ingo.eitel@uskh.de.
Abstract
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%; P=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 (P=0.037), a net reclassification improvement of 0.18 (P=0.009), and an integrated discriminative improvement of 0.04 (P=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.
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 infarctionpatients. 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%; P=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 (P=0.037), a net reclassification improvement of 0.18 (P=0.009), and an integrated discriminative improvement of 0.04 (P=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 infarctionpatients. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifiers: NCT00712101 and NCT02158468.
Authors: Borja Ibanez; Anthony H Aletras; Andrew E Arai; Hakan Arheden; Jeroen Bax; Colin Berry; Chiara Bucciarelli-Ducci; Pierre Croisille; Erica Dall'Armellina; Rohan Dharmakumar; Ingo Eitel; Rodrigo Fernández-Jiménez; Matthias G Friedrich; David García-Dorado; Derek J Hausenloy; Raymond J Kim; Sebastian Kozerke; Christopher M Kramer; Michael Salerno; Javier Sánchez-González; Javier Sanz; Valentin Fuster Journal: J Am Coll Cardiol Date: 2019-07-16 Impact factor: 24.094