BACKGROUND: We tested the hypothesis that the universal application of myocardial scanning with single-photon emission computed tomography (SPECT) would result in better risk stratification in renal transplant candidates (RTC) compared with SPECT being restricted to patients who, in addition to renal disease, had other clinical risk factors. METHODS: RTCs (n=363) underwent SPECT and clinical risk stratification according to the American Society of Transplantation (AST) algorithm and were followed up until a major adverse cardiovascular event (MACE) or death. RESULTS: Of the 363 patients, 79 patients (22%) had an abnormal SPECT scan and 270 (74%) were classified as high risk. Both methods correctly identified patients with increased probability of MACE. However, clinical stratification performed better (sensitivity and negative predictive value 99% and 99% vs. 25% and 87%, respectively). High-risk patients with an abnormal SPECT scan had a modest increased risk of events (log-rank = 0.03; hazard ratio [HR] = 1.37; 95% confidence interval [95% CI], 1.02-1.82). Eighty-six patients underwent coronary angiography, and coronary artery disease (CAD) was found in 60%. High-risk patients with CAD had an increased incidence of events (log-rank = 0.008; HR=3.85; 95% CI, 1.46-13.22), but in those with an abnormal SPECT scan, the incidence of events was not influenced by CAD (log-rank = 0.23). Forty-six patients died. Clinical stratification, but not SPECT, correlated with the probability of death (log-rank = 0.02; HR=3.25; 95% CI, 1.31-10.82). CONCLUSION: SPECT should be restricted to high-risk patients. Moreover, in contrast to SPECT, the AST algorithm was also useful for predicting death by any cause in RTCs and for selecting patients for invasive coronary testing.
BACKGROUND: We tested the hypothesis that the universal application of myocardial scanning with single-photon emission computed tomography (SPECT) would result in better risk stratification in renal transplant candidates (RTC) compared with SPECT being restricted to patients who, in addition to renal disease, had other clinical risk factors. METHODS: RTCs (n=363) underwent SPECT and clinical risk stratification according to the American Society of Transplantation (AST) algorithm and were followed up until a major adverse cardiovascular event (MACE) or death. RESULTS: Of the 363 patients, 79 patients (22%) had an abnormal SPECT scan and 270 (74%) were classified as high risk. Both methods correctly identified patients with increased probability of MACE. However, clinical stratification performed better (sensitivity and negative predictive value 99% and 99% vs. 25% and 87%, respectively). High-risk patients with an abnormal SPECT scan had a modest increased risk of events (log-rank = 0.03; hazard ratio [HR] = 1.37; 95% confidence interval [95% CI], 1.02-1.82). Eighty-six patients underwent coronary angiography, and coronary artery disease (CAD) was found in 60%. High-risk patients with CAD had an increased incidence of events (log-rank = 0.008; HR=3.85; 95% CI, 1.46-13.22), but in those with an abnormal SPECT scan, the incidence of events was not influenced by CAD (log-rank = 0.23). Forty-six patients died. Clinical stratification, but not SPECT, correlated with the probability of death (log-rank = 0.02; HR=3.25; 95% CI, 1.31-10.82). CONCLUSION: SPECT should be restricted to high-risk patients. Moreover, in contrast to SPECT, the AST algorithm was also useful for predicting death by any cause in RTCs and for selecting patients for invasive coronary testing.
Authors: Louis W Wang; Magid A Fahim; Andrew Hayen; Ruth L Mitchell; Laura Baines; Stephen Lord; Jonathan C Craig; Angela C Webster Journal: Cochrane Database Syst Rev Date: 2011-12-07
Authors: Charles A Herzog; Mengistu A Simegn; Yifan Xu; Salvatore P Costa; Roy O Mathew; Mohammad C El-Hajjar; Sanjeev Gulati; Rafael A Maldonado; Eric Daugas; Magdelena Madero; Jerome L Fleg; Rebecca Anthopolos; Gregg W Stone; Mandeep S Sidhu; David J Maron; Judith S Hochman; Sripal Bangalore Journal: J Am Coll Cardiol Date: 2021-05-11 Impact factor: 27.203