We have located links that may give you full text access.
Role of Coronary Angiography in Pre-Liver Transplantation Cardiac Evaluation: Experience From an Asian Transplant Institution.
Transplantation Proceedings 2017 October
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.
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.
Full text links
Related Resources
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app
All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.
By using this service, you agree to our terms of use and privacy policy.
Your Privacy Choices
You can now claim free CME credits for this literature searchClaim now
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app