A multiple logistic regression model using clinical and angiographic features predicted coronary angioplasty success for chronic total occlusions with a positive predictive value of 91% (95% CI 83-96%).
Observational (n=312)
What are the clinical and angiographic predictors of procedural success in patients undergoing coronary angioplasty for chronic total occlusion?
Clinical and angiographic features can be used in a multiple logistic regression model to accurately predict the probability of procedural success in patients undergoing coronary angioplasty for chronic total occlusions.
OBJECTIVE: To study the determinants of success of coronary angioplasty in patients with chronic total occlusions, and to formulate a multiple logistic regression model to improve selection of patients. DESIGN: A retrospective analysis of clinical and angiographic data on a consecutive series of patients. PATIENTS: 312 patients (mean age 55, range 31 to 79 years, 86% men) who underwent coronary angioplasty procedure for a chronic total occlusion between 1981 and 1992. RESULTS: Procedural success was achieved in 191 lesions (61.2%). A major complication occurred in six patients (1.9%). Multiple stepwise logistic regression analysis identified the presence of bridging collaterals (p or = 70%) was 91% (95% confidence intervals (95% CI) 83% to 96%) and predictive value for procedural failure (probability < 30%) was 81% (95% CI 64% to 92%). CONCLUSIONS: Percutaneous transluminal coronary angioplasty of chronic total occlusions is associated with a low risk of acute complication. Procedural success is influenced by easily identifiable clinical and angiographic features and the multiple regression model described may help to improve selection of patients.
Tan et al. (Sun,) conducted a observational in Chronic total occlusion (n=312). Coronary angioplasty was evaluated on Procedural success. A multiple logistic regression model using clinical and angiographic features predicted coronary angioplasty success for chronic total occlusions with a positive predictive value of 91% (95% CI 83-96%).