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Charles de Mestral

MDCM, FRCSC, PhD

Scientist

Email: Charles.deMestral@unityhealth.to
Tel: 416-864-5459
Twitter: @vasc_surg

Research Programs

Biography

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. 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 .
  2. 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.
  3. 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.
  4. 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.
  5. 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 .
  6. 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 .
  7. 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 .
  8. Li, B, Verma, R, Beaton, D, Tamim, H, Hussain, MA, Hoballah, JJ et al.. Predicting Major Adverse Cardiovascular Events Following Carotid Endarterectomy Using Machine Learning. J Am Heart Assoc. 2023;12 (20):e030508. doi: 10.1161/JAHA.123.030508. PubMed PMID:37804197 PubMed Central PMC10757546.
  9. Stephenson, R, Sarhangian, V, Park, J, Sankar, A, Baxter, NN, Stukel, TA et al.. Evolution of the surgical procedure gap during and after the COVID-19 pandemic in Ontario, Canada: cross-sectional and modelling study. Br J Surg. 2023;110 (12):1887-1889. doi: 10.1093/bjs/znad289. PubMed PMID:37724806 PubMed Central PMC10638533.
  10. Li, B, Aljabri, B, Verma, R, Beaton, D, Eisenberg, N, Lee, DS et al.. Machine learning to predict outcomes following endovascular abdominal aortic aneurysm repair. Br J Surg. 2023;110 (12):1840-1849. doi: 10.1093/bjs/znad287. PubMed PMID:37710397 .
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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