ABSTRACT
BACKGROUND: Liver transplant (LT) patients with significant coronary artery disease (CAD) have poorer outcomes. Pre-LT coronary angiography (CA) is associated with significant complications in cirrhotic patients. METHODS: This study aimed to identify predictors of abnormal CA in pre-LT cardiac assessment and to develop a predictive model to reduce unnecessary CA. From January 2006 to June 2013, 122 patients underwent CA based on the current institutional protocol. RESULTS: Forty-one (33.6%) patients had abnormal CA. Univariate analysis showed age ≥65 years (P = .001), cryptogenic cirrhosis (P = .046), cardiac comorbidities (P = .027), ischemic heart disease (IHD; P = .002), left ventricular hypertrophy (LVH; P = .004), hypertension (P = .002), diabetes mellitus (P = .017), dyslipidemia (P < .001), metabolic syndrome (P = .003), ≥2 CAD risk factors (P = .001), and high Framingham risk score (hard CAD risk, P = .018; cardiovascular disease: lipids, P = .002; body mass index, P < .001) to be significant predictors of abnormal CA. A predictive model was developed with the use of multivariable logistic regression and included diabetes, dyslipidemia, IHD, age ≥65 years, and LVH, achieving a specificity of 55.1% and sensitivity of 90.0%. This would reduce unnecessary CA by up to one-half in our study population (from 81 to 35) while maintaining a false negative rate of only 8.5%. CONCLUSIONS: Diabetes, dyslipidemia, IHD, age ≥65 years, and LVH appear to be predictors of abnormal CA in pre-LT patients. Our predictive model may help to better select patients for CA, although further validation is required.
