{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T11:36:27Z","timestamp":1791286587336,"version":"4.1.0"},"reference-count":56,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2025,6,23]],"date-time":"2025-06-23T00:00:00Z","timestamp":1750636800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004836","name":"Danmarks Frie Forskningsfond","doi-asserted-by":"publisher","award":["4308\u201000002B"],"award-info":[{"award-number":["4308\u201000002B"]}],"id":[{"id":"10.13039\/501100004836","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Acta Anaesthesiol Scand"],"published-print":{"date-parts":[[2025,7]]},"abstract":"<jats:title>ABSTRACT<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Despite advances in pain management, inadequate pain relief and opioid\u2010related adverse events remain common challenges in perioperative care, often contributing to prolonged recovery and reduced quality of life. The perioperative opioid algorithms for individualized dosing (OPIAID) project aims to develop machine\u2010learning algorithms tailored to provide patient\u2010specific opioid dosing across the different phases of perioperative care. For each phase, eight models are trained on granular data from 1.1\u2009million surgical procedures, including demographic and surgical details, vital signs, administered analgesics, pain, and opioid\u2010related adverse events. The two most accurate models will proceed to external validation. The best\u2010performing model will subsequently be tested as a decision support against current standard of care.<\/jats:p><\/jats:sec><jats:sec><jats:title>Objectives<\/jats:title><jats:p>This protocol describes the design and external validation of the intraoperative OPIAID algorithm, which suggests the end\u2010of\u2010surgery opioid dose intended for postoperative analgesia by approximating clinical performance and evaluating reliability, agreement, and calibration.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>In this multicenter, TRIPOD+AI\u2010adherent, prospective observational cohort study, we will collect data from a diverse surgical population of 656 adult patients undergoing elective or acute surgery under general anesthesia. All patients will require intraoperative opioid administration at the end of surgery for postoperative pain management and a subsequent stay in the post\u2010anesthesia care unit. The cohort will be used to externally validate two machine\u2010learning models through standardized measures of reliability, agreement, and calibration, and thereby designate the intraoperative OPIAID algorithm. Subsequently, the cohort will be used to approximate the clinical efficacy, safety and overall performance of the intraoperative OPIAID algorithm's recommended doses versus the clinician\u2010administered doses. These comparisons will be based on each approach's proximity to a golden standard \u201coptimal dose,\u201d which is calculated based on a predefined generic ruleset incorporating intraoperative opioid dosing, postoperative pain, opioid\u2010related adverse events, and need for rescue opioid administrations.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>The intraoperative OPIAID algorithm is intended as a clinical decision aid for anesthesiologists and nurse anesthetists in providing adequate postoperative pain management.<\/jats:p><\/jats:sec>","DOI":"10.1111\/aas.70071","type":"journal-article","created":{"date-parts":[[2025,6,24]],"date-time":"2025-06-24T00:05:22Z","timestamp":1750723522000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["External Validation of an Algorithm to Guide Opioid Administration at the End of Surgery\u2014Protocol for an Observational Cohort Study of the <scp>OPIAID<\/scp> Algorithm"],"prefix":"10.1111","volume":"69","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0338-3751","authenticated-orcid":false,"given":"Anders Peder H\u00f8jer","family":"Karlsen","sequence":"first","affiliation":[{"name":"Department of Anaesthesia and Intensive Care Copenhagen University Hospital\u2014Bispebjerg and Frederiksberg  Copenhagen Denmark"},{"name":"Department of Clinical Medicine University of Copenhagen  Copenhagen Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-8860-076X","authenticated-orcid":false,"given":"Pernille Bjersand","family":"Sunde","sequence":"additional","affiliation":[{"name":"Department of Anaesthesia and Intensive Care Copenhagen University Hospital\u2014Bispebjerg and Frederiksberg  Copenhagen Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-7290-5254","authenticated-orcid":false,"given":"Ida 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