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|Title:||Role of Coronary Angiography in Pre–Liver Transplantation Cardiac Evaluation: Experience From an Asian Transplant Institution||Authors:||Pang N.Q.
|Issue Date:||1-Oct-2017||Publisher:||Elsevier USA||Citation:||Pang N.Q., Kow W.C.A., Law J.H., Pan L.T.T., Lim B.L.K., Wong C.C.R., Chang K.Y.S., Ganpathi I.S., Krishnakumar Madhavan (2017-10-01). Role of Coronary Angiography in Pre–Liver Transplantation Cardiac Evaluation: Experience From an Asian Transplant Institution. Transplantation Proceedings 49 (8) : 1797-1805. ScholarBank@NUS Repository. https://doi.org/10.1016/j.transproceed.2017.04.021||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. � 2017 Elsevier Inc.||Source Title:||Transplantation Proceedings||URI:||http://scholarbank.nus.edu.sg/handle/10635/146799||ISSN:||00411345||DOI:||10.1016/j.transproceed.2017.04.021|
|Appears in Collections:||Staff Publications|
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