Literature DB >> 31290764

Long-term Reintervention After Endovascular Abdominal Aortic Aneurysm Repair.

Jesse A Columbo1,2,3,4, Pablo Martinez-Camblor2, Alistair James O'Malley2, Bjoern D Suckow1, Andrew W Hoel5, David H Stone1, Andres Schanzer6, Marc L Schermerhorn7, Art Sedrakyan8, Philip P Goodney1,2,4.   

Abstract

OBJECTIVE: To describe the long-term reintervention rate after endovascular abdominal aortic aneurysm repair (EVR), and identify factors predicting reintervention. SUMMARY OF BACKGROUND DATA: EVR is the most common method of aneurysm repair in America, and reintervention after EVR is common. Clinical factors predicting reintervention have not been described in large datasets with long-term follow-up.
METHODS: We studied patients who underwent EVR using the Vascular Quality Initiative registry linked to Medicare claims. Our primary outcome was reintervention, defined as any procedure related to the EVR after discharge from the index hospitalization. We used classification and regression tree modeling to inform a multivariable Cox-regression model predicting reintervention after EVR.
RESULTS: We studied 12,911 patients treated from 2003 to 2015. Mean age was 75.5 ± 7.3 years, 79.9% were male, and 89.1% of operations were elective. The 3-year reintervention rate was 15%, and the 10-year rate was 33%. Five factors predicted reintervention: operative time ≥3.0 hours, aneurysm diameter ≥6.0 cm, an iliac artery aneurysm ≥2.0 cm, emergency surgery, and a history of prior aortic surgery. Patients with no risk factors had a 3-year reintervention rate of 12%, and 10-year rate of 26% (n = 7310). Patients with multiple risk factors, such as prior aortic surgery and emergent surgery, had a 3-year reintervention rate 72%, (n = 32). Modifiable factors including EVR graft manufacturer or supra-renal fixation were not associated with reintervention (P = 0.76 and 0.79 respectively).
CONCLUSIONS: All patients retain a high likelihood of reintervention after EVR, but clinical factors at the time of repair can predict those at highest risk.
Copyright © 2019 Wolters Kluwer Health, Inc. All rights reserved.

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Year:  2021        PMID: 31290764     DOI: 10.1097/SLA.0000000000003446

Source DB:  PubMed          Journal:  Ann Surg        ISSN: 0003-4932            Impact factor:   12.969


  7 in total

1.  Surgical Repair of Juxtarenal Abdominal Aortic Aneurysms and safety of Suprarenal Aortic Clamping.

Authors:  Seonjeong Jeong; Tae-Won Kwon; Youngjin Han; Yong-Pil Cho
Journal:  World J Surg       Date:  2020-06       Impact factor: 3.352

2.  Type II Endoleak Nidus Volume on Arterial and Delayed Phases of Initial CT Angiography after Endovascular Abdominal Aortic Aneurysm Repair Predicts Persistent Endoleak and Aneurysm Sac Enlargement.

Authors:  Hyeon Yu; Joshua S Ellis; Lauren M B Burke; Ari J Isaacson; Charles T Burke
Journal:  Radiol Cardiothorac Imaging       Date:  2021-02-04

3.  Long-term Outcomes Associated With Open vs Endovascular Abdominal Aortic Aneurysm Repair in a Medicare-Matched Database.

Authors:  Kevin Yei; Asma Mathlouthi; Isaac Naazie; Nadin Elsayed; Bryan Clary; Mahmoud Malas
Journal:  JAMA Netw Open       Date:  2022-05-02

4.  Midterm outcomes of 455 patients receiving the AFX2 endovascular graft for the treatment of abdominal aortic aneurysm: A retrospective multi-center analysis.

Authors:  Raymond Vetsch; Harvey E Garrett; Christopher L Stout; Alan R Wladis; Matt Thompson; Joseph V Lombardi
Journal:  PLoS One       Date:  2021-12-31       Impact factor: 3.240

5.  Single centre experience with Excluder® stent graft; 17-year outcome.

Authors:  Ziga Snoj; Tjasa Tomazin; Vladka Salapura; Dimitrij Kuhelj
Journal:  Radiol Oncol       Date:  2022-04-13       Impact factor: 4.214

6.  Survival, reintervention and surveillance reports: long-term, centre-level evaluation and feedback of vascular interventions.

Authors:  Xavier Philip Fowler; Barbara Gladders; Kayla Moore; Jialin Mao; Art Sedrakyan; Philip Goodney
Journal:  BMJ Surg Interv Health Technol       Date:  2022-10-07

7.  Improved cardiovascular risk prediction in patients with end-stage renal disease on hemodialysis using machine learning modeling and circulating microribonucleic acids.

Authors:  David de Gonzalo-Calvo; Pablo Martínez-Camblor; Christian Bär; Kevin Duarte; Nicolas Girerd; Bengt Fellström; Roland E Schmieder; Alan G Jardine; Ziad A Massy; Hallvard Holdaas; Patrick Rossignol; Faiez Zannad; Thomas Thum
Journal:  Theranostics       Date:  2020-07-09       Impact factor: 11.556

  7 in total

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