Validation of a Decision Tree to Streamline Infrainguinal Vein Graft Surveillance.

Autor:	Mofidi R; Department of Vascular Surgery, The James Cook University Hospital, Middlesbrough, UK. Electronic address: rezamofidi@nhs.net., McBride OMB; Department of Vascular Surgery, Royal Infirmary of Edinburgh, Edinburgh, UK., Green BR; Department of Vascular Surgery, The James Cook University Hospital, Middlesbrough, UK., Gatenby T; Department of Vascular Surgery, The James Cook University Hospital, Middlesbrough, UK., Walker P; Department of Interventional Radiology, The James Cook University Hospital, Middlesbrough, UK., Milburn S; Department of Interventional Radiology, The James Cook University Hospital, Middlesbrough, UK.
Jazyk:	angličtina
Zdroj:	Annals of vascular surgery [Ann Vasc Surg] 2017 Apr; Vol. 40, pp. 216-222. Date of Electronic Publication: 2016 Nov 24.
DOI:	10.1016/j.avsg.2016.07.082
Abstrakt:	Background: Duplex ultrasound (DU)-based graft surveillance remains controversial. The aim of this study was to assess the ability of a recently proposed decision tree in identifying high-risk grafts which would benefit from DU-based surveillance. Materials and Methods: Consecutive patients undergoing infrainguinal vein graft bypass from January 2008 to December 2015 were identified from the National Vascular registry and enrolled in a duplex surveillance program. An early postoperative DU was performed at a median of 6 weeks (range: 4-9 weeks). Grafts were classified into high risk or low risk based on the findings of the earliest postoperative scan and 4 established risk factors for graft failure (diabetes, smoking, infragenicular distal anastomosis, and revision bypass surgery) using a classification and regression tree (CRT). The accuracy of the CRT model was evaluated using area under receiver operator characteristic (AROC) curve. Results: About 278 vein graft bypasses were performed; 29 grafts had occluded by the first surveillance visit; 249 vein grafts were entered into surveillance. Sixty-four (23%) developed critical stenosis. Overall 30-month primary patency, primary-assisted patency, and secondary patency rates were 71.2%, 77.2%, and 80.1%, respectively. AROC for prediction of graft stenosis or occlusion was 83% (95% confidence interval [CI]: 78-87%). The sensitivity and specificity of the CRT model for prediction of graft stenosis or occlusion were 95% (95% CI: 88-98%) and 52.2% (95% CI: 45-60%). Conclusions: A prediction model based on commonly recorded clinical variables and early postoperative DU scan is accurate at identifying grafts which are at high risk of failure. These high-risk grafts may benefit from DU-based surveillance. (Copyright © 2016 Elsevier Inc. All rights reserved.)
Databáze:	MEDLINE
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