Kenichi Nakajima1, Tsunehiko Nishimura. 1. Department of Nuclear Medicine, Faculty of Medicine, Institute of Medical, Pharmaceutical and Health Sciences, 13-1 Takaramachi, Kanazawa 920-8641, Japan. nakajima@med.kanazawa-u.ac.jp
Abstract
OBJECTIVE: The event risk of patients with coronary heart disease may be estimated by a large-scale prognostic database in a Japanese population. The aim of this study was to create a heart risk table for predicting the major cardiac event rate. METHODS: Using the J-ACCESS database created by a prognostic investigation involving 117 hospitals and >4,000 patients in Japan, multivariate logistic regression analysis was performed. The major event rate over a 3-year period that included cardiac death, non-fatal myocardial infarction, and severe heart failure requiring hospitalization was predicted by the logistic regression equation. The algorithm for calculating the event rate was simplified for creating tables. RESULTS: Two tables were created to calculate cardiac risk by age, perfusion score category, and ejection fraction with and without the presence of diabetes. A relative risk table comparing age-matched control subjects was also made. When the simplified tables were compared with the results from the original logistic regression analysis, both risk values and relative risks agreed well (P < 0.0001 for both). CONCLUSIONS: The Heart Risk Table was created for patients suspected of having ischemic heart disease and who underwent myocardial perfusion gated single-photon emission computed tomography. The validity of risk assessment using a J-ACCESS database should be validated in a future study.
OBJECTIVE: The event risk of patients with coronary heart disease may be estimated by a large-scale prognostic database in a Japanese population. The aim of this study was to create a heart risk table for predicting the major cardiac event rate. METHODS: Using the J-ACCESS database created by a prognostic investigation involving 117 hospitals and >4,000 patients in Japan, multivariate logistic regression analysis was performed. The major event rate over a 3-year period that included cardiac death, non-fatal myocardial infarction, and severe heart failure requiring hospitalization was predicted by the logistic regression equation. The algorithm for calculating the event rate was simplified for creating tables. RESULTS: Two tables were created to calculate cardiac risk by age, perfusion score category, and ejection fraction with and without the presence of diabetes. A relative risk table comparing age-matched control subjects was also made. When the simplified tables were compared with the results from the original logistic regression analysis, both risk values and relative risks agreed well (P < 0.0001 for both). CONCLUSIONS: The Heart Risk Table was created for patients suspected of having ischemic heart disease and who underwent myocardial perfusion gated single-photon emission computed tomography. The validity of risk assessment using a J-ACCESS database should be validated in a future study.