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., ...Daha Fazla

Annals of surgery, cilt.272, sa.4, ss.564-572, 2020 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 272 Sayı: 4
  • Basım Tarihi: 2020
  • Doi Numarası: 10.1097/sla.0000000000004132
  • Dergi Adı: Annals of surgery
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, CAB Abstracts, EMBASE, MEDLINE, Veterinary Science Database
  • Sayfa Sayıları: ss.564-572
  • Anahtar Kelimeler: decision-support, lower-extremity arterial trauma, risk prediction, PROGNOSTIC-FACTORS, VASCULAR INJURY, SEVERITY SCORE, MANAGEMENT, AMPUTATION, MEDICINE, SALVAGE, TRIALS, SYSTEM, TIME
  • Orta Doğu Teknik Üniversitesi Adresli: Hayır

Özet

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.