{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T09:06:42Z","timestamp":1776416802006,"version":"3.51.2"},"reference-count":17,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T00:00:00Z","timestamp":1776384000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JPM"],"abstract":"<jats:p>Background: Artificial intelligence (AI) is progressively entering perioperative medicine; however, its role in preoperative anesthetic decision-making remains insufficiently characterized. We evaluated the concordance between anesthesiologist-selected anesthetic techniques and algorithm-generated recommendations in a cohort of adult patients undergoing non-cardiac surgery. Methods: This retrospective observational study included adult patients (\u226518 years) undergoing elective non-cardiac surgery between January 2024 and January 2025 at two international centers (Mexico and Italy). Clinical, demographic, and surgical variables were extracted from electronic medical records. For each case, a structured anonymized vignette was submitted to ChatGPT (version 5.0, medical configuration) to obtain an independent recommendation regarding anesthetic technique. Concordance between AI-generated and clinician-selected techniques was assessed using agreement analysis and stratified by country and surgical specialty. Results: A total of 1965 patients were analyzed. Overall concordance between ChatGPT recommendations and anesthesiologist-selected techniques was 84.6%. Agreement remained stable across centers (Mexico 84.3%; Italy 88.7%). Disagreement rates varied by surgical specialty, with the highest values observed in vascular and proctologic surgery (28.6%), followed by urology (21.1%) and thoracic surgery (18.8%). Orthopedic procedures\u2014particularly shoulder arthroscopy\u2014accounted for a relevant proportion of divergences, where AI frequently favored regional techniques over general anesthesia. No specialty demonstrated discordance exceeding 30%. Conclusions: AI-generated anesthetic recommendations demonstrated substantial concordance with expert clinical decision-making across heterogeneous surgical settings. These findings support the potential integration of AI within a hybrid decision-making framework, complementing\u2014rather than replacing\u2014anesthesiologist expertise in contemporary perioperative care.<\/jats:p>","DOI":"10.3390\/jpm16040222","type":"journal-article","created":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T07:48:12Z","timestamp":1776412092000},"page":"222","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Clinical Application of Artificial Intelligence in Anesthesiology: A Multicenter Retrospective Comparison Between Human Anesthetic Decisions and Algorithmic Recommendations in Non-Cardiac Surgery"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4929-7111","authenticated-orcid":false,"given":"Gilberto","family":"Duarte-Medrano","sequence":"first","affiliation":[{"name":"Anesthesiology Department of Hospital Medica Sur, Mexico City 14050, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Natalia","family":"Nu\u00f1o-L\u00e1mbarri","sequence":"additional","affiliation":[{"name":"Translational Research Unit, Medica Sur Clinic & Foundation, Mexico City 14050, Mexico"},{"name":"Department of Surgery, Faculty of Medicine, The National Autonomous University of Mexico (UNAM), Mexico City 04510, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Octavio","family":"Gonzalez-Chon","sequence":"additional","affiliation":[{"name":"Anesthesiology Department of Hospital Medica Sur, Mexico City 14050, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4602-5081","authenticated-orcid":false,"given":"Rebeca Garazi","family":"Elguezabal Rodelo","sequence":"additional","affiliation":[{"name":"Anesthesiology Department of Hospital Medica Sur, Mexico City 14050, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Carmelo","family":"Calvagna","sequence":"additional","affiliation":[{"name":"Department of Anesthesia and Intensive Care, University Hospital Policlinico \u201cG. Rodolico\u2013San Marco\u201d, 95121 Catania, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-0215-5620","authenticated-orcid":false,"given":"Daniele","family":"Patern\u00f2","sequence":"additional","affiliation":[{"name":"Department of Anesthesia and Intensive Care, Hospital \u201cGiovanni Paolo II\u201d, ASP Ragusa, 97100 Ragusa, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2156-7554","authenticated-orcid":false,"given":"Luigi","family":"La Via","sequence":"additional","affiliation":[{"name":"Department of Anesthesia and Intensive Care, University Hospital Policlinico \u201cG. Rodolico\u2013San Marco\u201d, 95121 Catania, Italy"},{"name":"Department of General Surgery and Medical Surgical Specialties, University of Catania, 95131 Catania, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9331-2788","authenticated-orcid":false,"given":"Massimiliano","family":"Sorbello","sequence":"additional","affiliation":[{"name":"Faculty of Medicine and Surgery, University of Enna \u201cKore\u201d, 94100 Enna, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,4,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Cascella, M., Innamorato, M.A., and Simonini, A. (2024). Recent Advances and Perspectives in Anesthesiology: Towards Artificial Intelligence-Based Applications. J. Clin. Med., 13.","DOI":"10.3390\/jcm13154316"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Alatau, M., Bauer, J., and Sazonov, V. (2025). 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