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 false lumen or total aortic diameter, or decrease in the true lumen diameter. The multivariable 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%) developed NAR. The median age was 52 years (interquartile range 45, 62 years) and 56 (16%) were female. The rate of two year freedom from NAR was 71% (95% CI 65 – 77%). After the multivariable Cox regression analysis, Patent false lumen, Aberrant right subclavian artery, Taper ratio, abdominal circumferential Extent, coeliac artery or reNal artery involved, and four channel dissection (Three false lumens) remained independent predictors and were included in the PATENT grading system. The risk score was statistically 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 by good discrimination and calibration, which may serve as a clinician friendly tool to aid risk stratification for TBAD patients after TEVAR.