Predictors of in-hospital morbidity and mortality in patients with coronary artery disease treated with coronary artery bypass surgery
Journal
Prilozi (Makedonska akademija na naukite i umetnostite. Oddelenie za medicinski nauki)
Date Issued
2006-12-27
Author(s)
Borozanov, V
Abstract
Aim of the study: The aim of our study was to identify markers that can predict early morbidity and mortality in patients with coronary artery disease who underwent coronary artery bypass surgery (CABG) for myocardial revascularization.
Material and methods: 749 patients (pts) were enrolled in the study at mean age 55 +/- 8 years, 639 male and 119 female. We analyzed pre-operative demographic, clinical, left ventricular morphologic and functional and angiographic variables, per-operative characteristics, and we registered occurrence of hospital complications including cardiac death during the first 30 days after the operation.
Results: Hospital complications were registered in 173 (23.1%) patients, including cardiac death registered in two (3%) patients during the first 30 days after the operation. The most common complications were: pericardial effusion (8.4%), supraventricular arrhythmias (6.3%) and pleural effusion (5.6%), followed by more serious complications like infections, acute renal failure and stroke. Advanced age (>or=65 years), coexisting morbidities and risk factors: cerebrovascular disease (CVD), peripheral vascular disease (PVD), chronic obstructive pulmonary disease (COPD), hypertension (HTA), previous myocardial infarction (MI), heart failure before the operation, extensive coronary artery disease (CAD) (angiographicly identified), low left ventricular ejection fraction (LVEF), and high WMSS index were identified as predictors of in-hospital morbidity. Advanced age, Mod Gensini score (as marker of angiographic severity of CAD) and WMSS index were found to be independent predictors of in-hospital morbidity, while advanced age, heart failure before CABG and in-hospital complications were found to be independent predictors of in-hospital mortality.
Conclusion: In patients with coronary artery disease who underwent CABG surgery, preoperative variables and operative technique can predict occurrence of in-hospital morbidity, while early complications can strongly predict in-hospital mortality.
Material and methods: 749 patients (pts) were enrolled in the study at mean age 55 +/- 8 years, 639 male and 119 female. We analyzed pre-operative demographic, clinical, left ventricular morphologic and functional and angiographic variables, per-operative characteristics, and we registered occurrence of hospital complications including cardiac death during the first 30 days after the operation.
Results: Hospital complications were registered in 173 (23.1%) patients, including cardiac death registered in two (3%) patients during the first 30 days after the operation. The most common complications were: pericardial effusion (8.4%), supraventricular arrhythmias (6.3%) and pleural effusion (5.6%), followed by more serious complications like infections, acute renal failure and stroke. Advanced age (>or=65 years), coexisting morbidities and risk factors: cerebrovascular disease (CVD), peripheral vascular disease (PVD), chronic obstructive pulmonary disease (COPD), hypertension (HTA), previous myocardial infarction (MI), heart failure before the operation, extensive coronary artery disease (CAD) (angiographicly identified), low left ventricular ejection fraction (LVEF), and high WMSS index were identified as predictors of in-hospital morbidity. Advanced age, Mod Gensini score (as marker of angiographic severity of CAD) and WMSS index were found to be independent predictors of in-hospital morbidity, while advanced age, heart failure before CABG and in-hospital complications were found to be independent predictors of in-hospital mortality.
Conclusion: In patients with coronary artery disease who underwent CABG surgery, preoperative variables and operative technique can predict occurrence of in-hospital morbidity, while early complications can strongly predict in-hospital mortality.