BACKGROUND: Follow-up computed tomography angiography (CTA) scans add considerable postimplantation costs to endovascular aneurysm repairs (EVARs) of abdominal aortic aneurysms (AAAs). By building a risk model, we hope to identify patients at low risk for aneurysm sac enlargement to minimize unnecessary CTAs. METHODS: 895 consecutive patients who underwent EVAR for AAA were reviewed, of which 556 met inclusion criteria. A Probit model was created for aneurysm sac enlargement, with preoperative aneurysm morphology, patient demographics, and operative details as variables. RESULTS: Our final model included 287 patients and had a sensitivity of 100%, a specificity of 68.9%, and an accuracy of 70.4%. Ninety-nine (35%) of patients were assigned to the high-risk group, whereas 188 (65%) of patients were assigned to the low-risk group. Notably, regarding anatomic variables, our model reported that age, pulmonary comorbidities, aortic neck diameter, iliac artery length, and aneurysms were independent predictors of post-EVAR sac enlargement. With the exception of age, all statistically significant variables were qualitatively supported by prior literature. With regards to secondary outcomes, the high-risk group had significantly higher proportions of AAA-related deaths (5.1% versus 1.1%, P = 0.037) and Type 1 endoleaks (9.1% versus 3.2%, P = 0.033). CONCLUSIONS: Our model is a decent predictor of patients at low risk for post AAA EVAR aneurysm sac enlargement and associated complications. With additional validation and refinement, it could be applied to practices to cut down on the overall need for postimplantation CTA.
BACKGROUND: Follow-up computed tomography angiography (CTA) scans add considerable postimplantation costs to endovascular aneurysm repairs (EVARs) of abdominal aortic aneurysms (AAAs). By building a risk model, we hope to identify patients at low risk for aneurysm sac enlargement to minimize unnecessary CTAs. METHODS: 895 consecutive patients who underwent EVAR for AAA were reviewed, of which 556 met inclusion criteria. A Probit model was created for aneurysm sac enlargement, with preoperative aneurysm morphology, patient demographics, and operative details as variables. RESULTS: Our final model included 287 patients and had a sensitivity of 100%, a specificity of 68.9%, and an accuracy of 70.4%. Ninety-nine (35%) of patients were assigned to the high-risk group, whereas 188 (65%) of patients were assigned to the low-risk group. Notably, regarding anatomic variables, our model reported that age, pulmonary comorbidities, aortic neck diameter, iliac artery length, and aneurysms were independent predictors of post-EVAR sac enlargement. With the exception of age, all statistically significant variables were qualitatively supported by prior literature. With regards to secondary outcomes, the high-risk group had significantly higher proportions of AAA-related deaths (5.1% versus 1.1%, P = 0.037) and Type 1 endoleaks (9.1% versus 3.2%, P = 0.033). CONCLUSIONS: Our model is a decent predictor of patients at low risk for post AAA EVAR aneurysm sac enlargement and associated complications. With additional validation and refinement, it could be applied to practices to cut down on the overall need for postimplantation CTA.
Authors: George A Antoniou; Marc L Schermerhorn; Thomas L Forbes; Vincent Cheng; Stavros A Antoniou; Jonathan Golledge; Hence J M Verhagen; Francesco Torella Journal: BMJ Open Date: 2022-04-25 Impact factor: 2.692