213 HISTORY OF CORONARY ARTERY DISEASE PREDICTS INFERIOR SURVIVAL IN LIVER TRANSPLANT RECIPIENTS OF ADVANCED AGE IN A LARGE MULTICENTER U.S. COHORT

2020 ◽  
Vol 158 (6) ◽  
pp. S-1261
Author(s):  
Margarita N. German ◽  
Alexander Hristov ◽  
Alexander S. Lee ◽  
Fauzia Osman ◽  
Allison J. Kwong ◽  
...  
2019 ◽  
Vol 156 (6) ◽  
pp. S-1221
Author(s):  
Samarth S. Patel ◽  
Viviana A. Rodriquez ◽  
Mohammad B. Siddiqui ◽  
Fei-Pi Lin ◽  
Masoud Faridnia ◽  
...  

2017 ◽  
Vol 37 (suppl_1) ◽  
Author(s):  
Hilda M Gonzalez-Bonilla ◽  
Akanksha Thakkar ◽  
Antonio Duran ◽  
Alpana Senapati ◽  
Nakul Gupta ◽  
...  

Background: Coronary angiography (CAG) remains the gold standard to diagnose coronary artery disease (CAD). However, it is associated with multiple risks and its utility is not well defined in the liver transplant population. Alternatives to evaluate for CAD such as coronary artery calcium score (CACS) are being increasingly investigated. Hypothesis: To determine if the absence of coronary arterial calcium (CACS=0) on non-contrast, non-ECG gated chest CT scan can exclude obstructive CAD in liver transplant patients. Methods: We performed a retrospective analysis of data collected from liver transplant recipients. We included patients who had a CT chest without contrast and CAG less than one year apart. Agatston score was derived from non-IV contrast, non-ECG gated chest CT’s utilizing the syngo.via platform (Siemens Healthcare). CACS was compared against CAG. Patients with coronary stents were excluded. We determined NPV, PPV, sensitivity and specificity of using CACS = 0 as predictor of the absence of obstructive CAD. Results: Mean age at date of transplant was 59.03 and males accounted for 68.8% of our population. The negative predictive value for CACS=0 as a predictor of non-obstructive CAD was 100%. Positive predictive value for CACS≥1 was 6.8%. Sensitivity and specificity for the correlation between CACS and CAD were 100% and 33% respectively (Figure 1). CACS was stratified into four subgroups based severity, and we found that all patients with obstructive CAD had scores >400 (Figure 2). Conclusion: The absence of coronary arterial calcium (CACS=0) on non-contrast, non ECG gated chest CT has a high negative predictive value and can exclude the presence of obstructive CAD.


2017 ◽  
Vol 101 (4) ◽  
pp. 793-803 ◽  
Author(s):  
Sanjaya K. Satapathy ◽  
Jason M. Vanatta ◽  
Ryan A. Helmick ◽  
Albert Flowers ◽  
Satish K. Kedia ◽  
...  

Author(s):  
Mario Romero‐Cristóbal ◽  
Teresa Mombiela ◽  
Aranzazu Caballero ◽  
Ana Clemente ◽  
Ainhoa Fernández‐Yunquera ◽  
...  

2017 ◽  
Vol 23 (3) ◽  
pp. 386-395 ◽  
Author(s):  
Brian J. Hogan ◽  
Enoka Gonsalkorala ◽  
Michael A. Heneghan

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Rayan Jo Rachwan ◽  
Issa Kutkut ◽  
Lava R Timsina ◽  
Rody G Bou Chaaya ◽  
Edward El-Am ◽  
...  

Background: Patients with significant coronary artery disease (CAD) are more likely to develop post-liver transplant (LT) cardiac events. We developed the CAD-LT screening score and testing algorithm to predict the risk of significant CAD in LT candidates. Methods: Patients who underwent pre-LT evaluation at Indiana University (2010-2017) were studied retrospectively (n=1814). Stress tests (ST) (n=1677) and cardiac catheterization (CATH) reports (n=1300) were reviewed. CATH was performed in patients with predefined CAD risk factors. Significant CAD was defined as disease requiring percutaneous or surgical intervention. Multivariable estimates (Adjusted Odds Ratio i.e. AOR [95%CI]) with assessment of model performance using Receiver Operating Curve analysis were used to compute a point-based risk score and stratify patients. A 10-fold internal cross-validation (CV) model was done. Results: There were 950 LT and 864 no-LT patients. The risk-adjusted predictors of significant CAD were older age (AOR 1.06 [95%CI 1.03-1.09]), male gender (1.69 [1.13-2.50]), diabetes (1.44 [1.01-2.06]), hypertension (1.50 [1.05-2.15]), current smoking history (1.81 [1.16-2.82]), family history of CAD (1.76 [1.24-2.50]), and personal history of CAD (5.41 [3.48-8.43]). The CAD-LT score is shown in Table 1. Figure 1 is an algorithm for its use. The mean CV Area Under the Curve [95% CI] was 0.75 [0.71-0.79]. The algorithm detected 97% of the patients with significant CAD and would decrease the number of ST by 718 (43%; 671 in high-risk group and 47 in low-risk group) and CATH by 409 (30%). Conclusion: The CAD-LT score identifies LT candidates at high risk for significant CAD and guides pre-LT testing.


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