The Negative Predictive Value of Preoperative Stress Testing for Non-Fatal Cardiac Events After Orthotopic Liver Transplantation in the Modern Era.

2014 ◽  
Vol 98 ◽  
pp. 174
Author(s):  
F. Niyazi ◽  
R. Patel ◽  
Y. Nasr ◽  
J. Perez ◽  
S. Mawri ◽  
...  
2022 ◽  
Vol 2022 ◽  
pp. 1-8
Author(s):  
Zhenxing Yu ◽  
Guixue Ou ◽  
Ruihua Wang ◽  
Qinghua Zhang

The study focused on the clinical application value of artificial intelligence-based computed tomography angiography (CTA) in the diagnosis of orthotopic liver transplantation (OLT) after ischemic type biliary lesions (ITBL). A total of 66 patients receiving OLT in hospital were selected. Convolutional neural network (CNN) algorithm was used to denoise and detect the edges of CTA images of patients. At the same time, the quality of the processed image was subjectively evaluated and quantified by Hmax, Ur, Cr, and other indicators. Then, the digital subtraction angiography (DSA) diagnosis and CTA diagnosis based on CNN were compared for the sensitivity, specificity, positive predictive value, negative predictive value, and patient classification results. It was found that CTA can clearly reflect the information of hepatic aorta lesions and thrombosis in patients with ischemic single-duct injury after liver transplantation. After neural network algorithm processing, the image quality is obviously improved, the lesions are more prominent, and the details of lesion parts are also well displayed. ITBL occurred in 40 (71%) of 56 patients with abnormal CTA at early stage. ITBL occurred in only 8 (12.3%) of 65 patients with normal CTA at early stage. Early CTA manifestations had high sensitivity (72.22%), specificity (87.44%), positive predictive value (60.94%), and negative predictive value (92.06%) for the diagnosis of ITBL. It was concluded that artificial intelligence-based CTA had high clinical application value in the diagnosis of ITBL after OLT.


2004 ◽  
Vol 10 (5) ◽  
pp. 1789-1795 ◽  
Author(s):  
Michelangelo Fiorentino ◽  
Annalisa Altimari ◽  
Matteo Ravaioli ◽  
Elisa Gruppioni ◽  
Elena Gabusi ◽  
...  

2021 ◽  
Vol 10 (15) ◽  
pp. 3401
Author(s):  
Chen-Fang Lee ◽  
Hao-Chien Hung ◽  
Wei-Chen Lee

Background: Diagnostic tests for early allograft dysfunction (EAD) after living donor liver transplantation (LDLT) vary widely. We aimed to evaluate the predictive value of rotational thromboelastometry (ROTEM)-derived parameters in EAD. Materials and Methods: A total of 121 patients were reviewed. The definition of EAD proposed by Olthoff et al. included the presence of any of the following at postoperative day 7: bilirubin level ≥ 10 mg/dL, INR ≥ 1.6, or serum AST or ALT levels > 2000 IU/L. All patients underwent ROTEM assay, which consisted of an extrinsically activated thromboelastometric test (EXTEM) before and 24 h after LDLT. Results: The 1-year/2-year OS were 68.%8/64.5% and 94.4%/90.8% for the EAD and non-EAD groups, respectively (p = 0.001). Two independent risks were identified for EAD, the postoperative clotting time (CT, p = 0.026) and time to maximum clot firmness (maximum clot firmness (MCF)-t, p = 0.009) on the EXTEM. CT yielded a specificity of 82.0% and negative predictive value of 83.0%, and MCF-t displayed a specificity of 76.4% and negative predictive value of 81.9% in diagnosing EAD. The use of the 24 h post-LDLT ROTEM increased the effectiveness of predicting overall survival (OS) compared to using the Olthoff’s EAD criteria alone (p < 0.001). Conclusion: We conclude that CT and MCF on EXTEM were independent predictors of EAD. The 24 h post-LDLT ROTEM can be used with conventional laboratory tests to diagnose EAD. It increases the effectiveness of predicting OS.


2020 ◽  
Vol 21 (Supplement_1) ◽  
Author(s):  
J N Khan ◽  
T Griffiths ◽  
K Sandhu ◽  
S Cabezon ◽  
C S Kwok ◽  
...  

Abstract Funding Acknowledgements No funding sources Background Cardiac physiologist-led stress echocardiography (PLSE) services provide potential for expansion of SE services and increased productivity for cardiologists. There is no published data on the accuracy or prognostic value of PLSE. Purpose To assess and compare the accuracy and prognostic value of PLSE and cardiologist-led stress echocardiography (CLSE) for CAD assessment Methods Retrospective study of 898 subjects undergoing PLSE (n = 393) or CLSE (n = 505) for CAD assessment using exercise or dobutamine. For accuracy assessment, the primary outcome was the ability of stress echocardiography to identify significant CAD on invasive angiography (ICA). Incidence of 24-month non-fatal myocardial infarction (MI), total and cardiac mortality, revascularisation and combined major adverse cardiac events (MACE) were assessed. Results Demographics, comorbidities, CAD predictors and cardiac medications were matched between the PLSE and CLSE groups. PLSE had high sensitivity, specificity, positive and negative predictive value and accuracy (85%, 74%, 69%, 88%, 78% respectively). PLSE accuracy measures were similar and non-inferior to CLSE. There was a similar incidence of individual and combined outcomes in PLSE and CLSE subjects. Negative stress echocardiography conferred a low incidence of non-fatal MI (PLSE 1.4% vs. CLSE 0.9%, p = 0.464), cardiac mortality (0.6% vs. 0.0%, p = 0.277) and MACE (6.8% vs. 3.1%, p = 0.404). Conclusion This is the largest study of PLSE accuracy and first study of the prognostic value of PLSE. PLSE demonstrates high and non-inferior accuracy compared with CLSE for CAD assessment. Negative PLSE and CLSE confer a similarly very low incidence of cardiac outcomes, confirming for the first time the important prognostic value of PLSE. Accuracy of PLSE and CLSE for CAD Marker of diagnostic test Total (n = 72) PLSE (n = 32) CLSE (n = 40) p Significant CAD present (n, %) 20 (27.8%) 12 (37.5%) 8 (20.0%) 0.167 * Single-vessel CAD 12 (60.0%) 7 (58.3%) 5 (62.5%) 0.325 * Multi-vessel CAD 8 (40.0%) 5 (41.7%) 3 (37.5%) 0.325 Sensitivity 76% (66-76%) 85% (73-97%) 63% (48-78%) Non-significant Specificity 73% (63-73%) 74% (59-89%) 72% (58-86%) Non-significant Positive predictive value (PPV) 53% (42-64%) 69% (53-85%) 29% (15-43%) Significant Negative predictive value (NPV) 88% (80-96%) 88% (77-99%) 88% (78-98%) Non-significant Overall accuracy 74% (64-84%) 78% (64-92%) 70% (56-84%) Non-significant Accuracy data expressed as value (95% confidence interval). CAD= coronary artery disease. Differences in values between PLSE and CLSE considered statistically significant if no crossover in 95% confidence intervals Abstract 1673 Figure. Predicted coronary artery lesion from SE


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