{ "abstract": "Objective\n\nTo evaluate the agreement between Manchester Triage System (MTS) category assignments generated by GPT-5.5 Thinking and an expert-derived reference standard in a selected cohort of emergency department (ED) patients, and to assess the model's ability to predict hospital admission and 72-hour mortality.Methods\n\nThis single-center observational study prospectively sampled consecutive ED presentations during a prespecified continuous 72-hour window, with triage-time variables and secondary outcomes obtained from hospital records. Patients classified as MTS Category 5 (Blue; nonurgent) by the expert reference standard were excluded from the analytic cohort. GPT-5.5 Thinking was prompted in a standardized single-shot format using structured clinical vignettes derived from triage data. The primary endpoint was agreement between model-assigned MTS categories and an expert reference standard established by two independent blinded emergency medicine specialist rater teams, with disagreements resolved through senior adjudication. Exact agreement, within-1-level agreement, overtriage, undertriage, and dangerous undertriage were calculated. Secondary analyses evaluated prediction of hospital admission and 72-hour mortality using diagnostic performance metrics.Results\n\nA total of 1,841 patients were included. Overall agreement between GPT-5.5 Thinking and the expert reference standard was substantial (κ = 0.721; 95% CI 0.691-0.740). Exact agreement rate was 62.0%, and within-1-level agreement rate was 99.0%. Overtriage occurred in 35.3% of cases, undertriage in 2.7%, and dangerous undertriage in 0.2%. Exact agreement rate was significantly lower in patients aged ≥ 65 years than in younger adults (57.1% vs. 64.2%, p = 0.013). For hospital admission, accuracy rate was 79.9%, sensitivity 83.8%, positive predictive value (PPV) 45.2%, and negative predictive value (NPV) 95.9%. For 72-hour mortality, accuracy rate was 86.5%, sensitivity 72.3%, PPV 12.6%, and NPV 99.1%.Conclusion\n\nWithin this selected ED cohort, GPT-5.5 Thinking showed substantial agreement with expert MTS-based ED triage and generally preserved the ordinal hierarchy of clinical urgency. Its performance was characterized by frequent adjacent-level agreement, predominant overtriage, and very rare but nonzero dangerous undertriage. The model also showed stronger rule-out than rule-in characteristics for hospital admission and 72-hour mortality.", "abstract_shown": true, "affiliations": [ "Department of Emergency Medicine, University of Health Sciences, Haseki Training and Research Hospital, Ugur Mumcu, Belediye Str. No:7 Sultangazi, Istanbul, Türkiye, Turkey. kaymaker4303@gmail.com.", "Department of Emergency Medicine, University of Health Sciences, Haseki Training and Research Hospital, Ugur Mumcu, Belediye Str. No:7 Sultangazi, Istanbul, Türkiye, Turkey.", "Department of Emergency Medicine, University of Health Sciences, Kanuni Sultan Suleyman Training and Research Hospital, Istanbul, Türkiye, Turkey." ], "article_type": "research article", "arxiv": null, "author_total": 15, "authors": [ { "affs": [ 0 ], "name": "Sureyya Tuba Fettahoglu", "orcid": "0000-0001-7882-5086" }, { "affs": [ 1 ], "name": "Adem Az", "orcid": "0000-0002-7204-6185" }, { "affs": [ 1 ], "name": "Ozgur Sogut", "orcid": "0000-0003-3365-3713" }, { "affs": [ 1 ], "name": "Tarik Akdemir", "orcid": "0000-0003-1178-2274" }, { "affs": [ 1 ], "name": "Muhammed Furkan Ozden", "orcid": "0000-0003-1027-0015" }, { "affs": [ 2 ], "name": "Salih Fettahoglu", "orcid": "0000-0003-0405-3938" }, { "affs": [ 1 ], "name": "Mucahide Samli Helvacı", "orcid": "0009-0003-0195-712X" }, { "affs": [ 1 ], "name": "Enes Sisman", "orcid": "0009-0001-4925-7291" }, { "affs": [ 1 ], "name": "Mehmet Ozcomlekci", "orcid": "0009-0000-4740-2005" }, { "affs": [ 1 ], "name": "Emir Bilici", "orcid": "0009-0006-8097-1641" }, { "affs": [ 1 ], "name": "Nurbaki Kilic", "orcid": "0009-0007-6526-0777" }, { "affs": [ 1 ], "name": "Tugay Saricicek", "orcid": "0009-0002-9522-683X" }, { "affs": [ 1 ], "name": "Ayse Feyza Celik", "orcid": "0009-0000-2911-2282" }, { "affs": [ 1 ], "name": "Zekeriya Colak", "orcid": "0009-0006-2526-213X" }, { "affs": [ 1 ], "name": "Zulkuf Eralp", "orcid": "0009-0007-6299-0045" } ], "bibtex": "https://research.draconitic.com/paper/8kwq689cehqmg.bib", "cited_by": 0, "doi": "10.1186/s12873-026-01704-7", "fulltext_url": "https://europepmc.org/articles/PMC13685258", "id": "8kwq689cehqmg", "issns": [ "1471-227X" ], "landing_url": "https://europepmc.org/article/MED/42902219", "language": "eng", "licence": "CC-BY-NC-ND", "licence_label": "CC BY-NC-ND", "licence_source": "article", "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/", "metadata_licence": null, "native_subjects": [ [ "lcc", "RC86-88.9" ], [ "lcc", "RC952-1245" ], [ "openalex", "2711|Emergency and Acute Care Studies" ] ], "openalex": "W7170963960", "pdf_url": "https://europepmc.org/articles/PMC13685258?pdf=render", "pmcid": "PMC13685258", "pmid": "42902219", "published": "2026-07-01", "publisher": "BMC", "ris": "https://research.draconitic.com/paper/8kwq689cehqmg.ris", "sources": [ { "first_seen": "2026-10-30T12:19:41Z", "native_id": "MED:42902219", "source": "europepmc", "url": "https://europepmc.org/article/MED/42902219" }, { "first_seen": "2026-10-30T13:45:50Z", "native_id": "db46e0bd667044dc9b70e6317a2ff456", "source": "doaj", "url": "https://doi.org/10.1186/s12873-026-01704-7" } ], "subjects": [ { "field": "medicine", "origin": "openalex:2711|Emergency and Acute Care Studies", "subfield": "general" } ], "title": "Performance of GPT-5.5 thinking for Manchester Triage System-based emergency department triage: agreement with an expert reference standard and prediction of short-term outcomes.", "title_text": "Performance of GPT-5.5 thinking for Manchester Triage System-based emergency department triage: agreement with an expert reference standard and prediction of short-term outcomes.", "type": "peer-reviewed", "updated_at": "2026-10-30T13:45:50Z", "url": "https://research.draconitic.com/paper/8kwq689cehqmg", "venue": "BMC emergency medicine", "versions": [] }