Predicting the Outcome of Limb Revascularization in Patients With Lower-extremity Arterial Trauma: Development and External Validation of a Supervised Machine-learning Algorithm to Support Surgical Decisions.

Perkins Z. B., Yet B., Sharrock A., Rickard R., Marsh W., Rasmussen T. E., ...More

Annals of surgery, vol.272, no.4, pp.564-572, 2020 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 272 Issue: 4
  • Publication Date: 2020
  • Doi Number: 10.1097/sla.0000000000004132
  • Journal Name: Annals of surgery
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, CAB Abstracts, EMBASE, MEDLINE, Veterinary Science Database
  • Page Numbers: pp.564-572
  • Keywords: decision-support, lower-extremity arterial trauma, risk prediction, PROGNOSTIC-FACTORS, VASCULAR INJURY, SEVERITY SCORE, MANAGEMENT, AMPUTATION, MEDICINE, SALVAGE, TRIALS, SYSTEM, TIME
  • Middle East Technical University Affiliated: No

Abstract

Objectives: Estimating the likely success of limb revascularization in patients with lower-extremity arterial trauma is central to decisions between attempting limb salvage and amputation. However, the projected outcome is often unclear at the time these decisions need to be made, making them difficult and threatening sound judgement. The objective of this study was to develop and validate a prediction model that can quantify an individual patient's risk of failed revascularization.