BACKGROUND: The magnitude of prognostically relevant myocardial injury after percutaneous coronary interventions remains poorly defined. The Society for Cardiovascular Angiography and Interventions (SCAI) proposed marked biomarker elevations to define periprocedural myocardial infarction (PMI). These consensus-based thresholds have not been validated in the era of high-sensitivity cardiac troponins. We sought to assess the prognostic impact of SCAI-defined PMI and explore optimal prognostic thresholds of high-sensitivity cardiac troponin T (hs-cTnT) after elective percutaneous coronary interventions. METHODS AND RESULTS: We evaluated patients who underwent elective percutaneous coronary interventions at 2 tertiary care centers with serial hs-cTnT measurements. PMI was defined as peak postprocedural hs-cTnT >70× upper reference limit (URL) in patients with nonelevated (≤1× URL) baseline levels; or incremental increase >70× URL in patients with elevated baseline levels. The primary outcome was 1-year all-cause mortality. Of 8140 patients, 220 (2.7%) died within 1 year. In multivariable analyses, patients with SCAI-defined PMI (n=140; 1.7%) had a higher risk of 1-year mortality (12.9% versus 2.5%, adjusted hazard ratio 4.10, 95% CI 2.51-6.68; P<0.001) as well as cardiac mortality (11.4% versus 2.1%, adjusted hazard ratio 4.21, 95% CI 2.50-7.11; P<0.001). Based on receiver operating characteristics analysis, the optimal prognostic threshold of hs-cTnT was >10×URL, observed in 14.6% of patients. This threshold showed lower specificity (85.7% versus 98.4%) but higher sensitivity (25.4% versus 8.2%) and better overall performance for prediction of 1-year mortality compared with the SCAI-defined cutoff value of troponin. CONCLUSIONS: In patients undergoing elective percutaneous coronary interventions, SCAI-defined PMI emerged as an independent, highly specific, but insensitive predictor of 1-year mortality. Optimal trade-off between sensitivity and specificity was observed at a lower threshold of hs-cTnT (10× URL) in this cohort.
BACKGROUND: The magnitude of prognostically relevant myocardial injury after percutaneous coronary interventions remains poorly defined. The Society for Cardiovascular Angiography and Interventions (SCAI) proposed marked biomarker elevations to define periprocedural myocardial infarction (PMI). These consensus-based thresholds have not been validated in the era of high-sensitivity cardiac troponins. We sought to assess the prognostic impact of SCAI-defined PMI and explore optimal prognostic thresholds of high-sensitivity cardiac troponin T (hs-cTnT) after elective percutaneous coronary interventions. METHODS AND RESULTS: We evaluated patients who underwent elective percutaneous coronary interventions at 2 tertiary care centers with serial hs-cTnT measurements. PMI was defined as peak postprocedural hs-cTnT >70× upper reference limit (URL) in patients with nonelevated (≤1× URL) baseline levels; or incremental increase >70× URL in patients with elevated baseline levels. The primary outcome was 1-year all-cause mortality. Of 8140 patients, 220 (2.7%) died within 1 year. In multivariable analyses, patients with SCAI-defined PMI (n=140; 1.7%) had a higher risk of 1-year mortality (12.9% versus 2.5%, adjusted hazard ratio 4.10, 95% CI 2.51-6.68; P<0.001) as well as cardiac mortality (11.4% versus 2.1%, adjusted hazard ratio 4.21, 95% CI 2.50-7.11; P<0.001). Based on receiver operating characteristics analysis, the optimal prognostic threshold of hs-cTnT was >10×URL, observed in 14.6% of patients. This threshold showed lower specificity (85.7% versus 98.4%) but higher sensitivity (25.4% versus 8.2%) and better overall performance for prediction of 1-year mortality compared with the SCAI-defined cutoff value of troponin. CONCLUSIONS: In patients undergoing elective percutaneous coronary interventions, SCAI-defined PMI emerged as an independent, highly specific, but insensitive predictor of 1-year mortality. Optimal trade-off between sensitivity and specificity was observed at a lower threshold of hs-cTnT (10× URL) in this cohort.
Authors: Bernard R Chaitman; Karen P Alexander; Derek D Cyr; Jeffrey S Berger; Harmony R Reynolds; Sripal Bangalore; William E Boden; Renato D Lopes; Marcin Demkow; Gian Piero Perna; Robert K Riezebos; Edward O McFalls; Subhash Banerjee; Akshay Bagai; Gilbert Gosselin; Sean M O'Brien; Frank W Rockhold; David D Waters; Kristian A Thygesen; Gregg W Stone; Harvey D White; David J Maron; Judith S Hochman Journal: Circulation Date: 2020-12-03 Impact factor: 29.690
Authors: Johannes Mair; Allan Jaffe; Bertil Lindahl; Nicholas Mills; Martin Möckel; Louise Cullen; Evangelos Giannitsis; Ola Hammarsten; Kurt Huber; Konstantin Krychtiuk; Christian Mueller; Kristian Thygesen Journal: Biomarkers Date: 2022-05-26 Impact factor: 2.663
Authors: Heerajnarain Bulluck; Valeria Paradies; Emanuele Barbato; Andreas Baumbach; Hans Erik Bøtker; Davide Capodanno; Raffaele De Caterina; Claudio Cavallini; Sean M Davidson; Dmitriy N Feldman; Péter Ferdinandy; Sebastiano Gili; Mariann Gyöngyösi; Vijay Kunadian; Sze-Yuan Ooi; Rosalinda Madonna; Michael Marber; Roxana Mehran; Gjin Ndrepepa; Cinzia Perrino; Stefanie Schüpke; Johanne Silvain; Joost P G Sluijter; Giuseppe Tarantini; Gabor G Toth; Linda W Van Laake; Clemens von Birgelen; Michel Zeitouni; Allan S Jaffe; Kristian Thygesen; Derek J Hausenloy Journal: Eur Heart J Date: 2021-07-15 Impact factor: 29.983