Development and Validation of a User Friendly Morphology Grading System (PATENT) Predicting Aortic Remodelling After Thoracic Endovascular Aortic Repair in High Risk Uncomplicated Type B Aortic Dissection.

ABSTRACT

OBJECTIVE: This study aimed to create a morphology grading system, solely based on 2D images from computed tomography angiography, to predict negative aortic remodelling (NAR) for patients with high risk uncomplicated type B aortic dissection (TBAD) after thoracic endovascular aortic repair (TEVAR). METHODS: This single centre retrospective cohort study extracted and analysed consecutive patients diagnosed with high risk uncomplicated TBAD. Negative aortic remodelling was defined as an increase in the diameter of a false lumen or total aorta, or decrease in the diameter of a true lumen. The multivariate Cox regression model identified risk factors and a prediction model was created for two year freedom from NAR. A three category grading system, in which patients were classified into low, medium, and high risk groups, was further developed and internally validated. RESULTS: Of 351 patients included, 99 (28%) of them developed NAR. The median age was 52 years (interquartile range 45, 62 years) and 56 of them (16%) were female. The rate of two year freedom from NAR was 71% (95% CI 65 - 77%). After the multivariate Cox regression analysis, Patent false lumen, Aberrant right subclavian artery, Taper ratio, abdominal circumferential Extent, coeliac artery or reNal artery involved, and four channelled dissection (Three false lumens) remained independent predictors and were included in the PATENT grading system. The risk score was significantly associated with NAR (HR 1.21; 95% CI 1.14 - 1.29; p < .001). The medium and high risk groups demonstrated a higher rate of NAR (medium risk, HR 2.82; 95% CI 1.57 - 5.01; p = .001; high risk, HR 4.39; 95% CI 2.58 - 7.48; p < .001). The grading system was characterised by robust discrimination with Harrell's C index of 0.68 (95% CI 0.63 - 0.75). CONCLUSION: The PATENT grading system was characterised with good discrimination and calibration, which may serve as a clinician friendly tool to aid in risk stratification for TBAD patients after TEVAR.