Charles de Mestral




Dr. Charles de Mestral is a vascular surgeon at St. Michael’s Hospital and a Surgeon-Scientist in the Department of Surgery of the University of Toronto. He conducts research on clinical effectiveness, as well as the provision, quality and costs of surgical care.  His primary research focus is amputation prevention in people with diabetes and peripheral artery disease. His work is based out of the Li Ka Shing Knowledge Institute of St. Michael’s Hospital and ICES.

Please note: Dr. de Mestral is no longer accepting summer students.


Recent Publications

  1. de Mestral, C, Abdel-Qadir, HM, Austin, PC, Chong, AS, McAlister, FA, Lindsay, TF et al.. Ambulatory Cardiology or General Internal Medicine Assessment Prior to Scheduled Major Vascular Surgery is Associated with Improved Outcomes. Ann Surg. 2024; :. doi: 10.1097/SLA.0000000000006321. PubMed PMID:38709199 .
  2. de Mestral, C. Is it time to expand screening criteria for abdominal aortic aneurysms?. J Vasc Surg. 2024;79 (5):1068. doi: 10.1016/j.jvs.2024.01.001. PubMed PMID:38642969 .
  3. Li, B, Aljabri, B, Verma, R, Beaton, D, Hussain, MA, Lee, DS et al.. Predicting Outcomes Following Lower Extremity Endovascular Revascularization Using Machine Learning. J Am Heart Assoc. 2024;13 (9):e033194. doi: 10.1161/JAHA.123.033194. PubMed PMID:38639373 .
  4. Soenens, G, Gorden, L, Doyen, B, Wheatcroft, M, de Mestral, C, Palter, V et al.. Development and Testing of Step, Error, and Event Frameworks to Evaluate Technical Performance in Peripheral Endovascular Interventions. Eur J Vasc Endovasc Surg. 2024; :. doi: 10.1016/j.ejvs.2024.03.007. PubMed PMID:38492630 .
  5. Li, B, Warren, BE, Eisenberg, N, Beaton, D, Lee, DS, Aljabri, B et al.. Machine Learning to Predict Outcomes of Endovascular Intervention for Patients With PAD. JAMA Netw Open. 2024;7 (3):e242350. doi: 10.1001/jamanetworkopen.2024.2350. PubMed PMID:38483388 PubMed Central PMC10940965.
  6. Li, B, Verma, R, Beaton, D, Tamim, H, Hussain, MA, Hoballah, JJ et al.. Predicting outcomes following lower extremity open revascularization using machine learning. Sci Rep. 2024;14 (1):2899. doi: 10.1038/s41598-024-52944-1. PubMed PMID:38316811 PubMed Central PMC10844206.
  7. Vervoort, D, Hirode, G, Lindsay, TF, Tam, DY, Kapila, V, de Mestral, C et al.. One-time screening for abdominal aortic aneurysm in Ontario, Canada: a model-based cost-utility analysis. CMAJ. 2024;196 (4):E112-E120. doi: 10.1503/cmaj.230913. PubMed PMID:38316457 PubMed Central PMC10843437.
  8. Walker, RJB, Stukel, TA, de Mestral, C, Nathens, A, Breau, RH, Hanna, WC et al.. Hospital learning curves for robot-assisted surgeries: a population-based analysis. Surg Endosc. 2024;38 (3):1367-1378. doi: 10.1007/s00464-023-10625-6. PubMed PMID:38127120 .
  9. Li, B, Eisenberg, N, Beaton, D, Lee, DS, Aljabri, B, Verma, R et al.. Using Machine Learning (XGBoost) to Predict Outcomes After Infrainguinal Bypass for Peripheral Artery Disease. Ann Surg. 2024;279 (4):705-713. doi: 10.1097/SLA.0000000000006181. PubMed PMID:38116648 .
  10. Li, B, Eisenberg, N, Beaton, D, Lee, DS, Aljabri, B, Wijeysundera, DN et al.. Using machine learning to predict outcomes following suprainguinal bypass. J Vasc Surg. 2024;79 (3):593-608.e8. doi: 10.1016/j.jvs.2023.09.037. PubMed PMID:37804954 .
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Affiliations & Other Activities

  • Surgeon, Division of Vascular Surgery, St. Michael’s Hospital
  • Assistant Professor, Department of Surgery, University of Toronto
  • Adjunct Scientist, Institute for Clinical Evaluative Sciences