{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,9]],"date-time":"2026-03-09T04:39:17Z","timestamp":1773031157617,"version":"3.50.1"},"reference-count":40,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2022,6,15]],"date-time":"2022-06-15T00:00:00Z","timestamp":1655251200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>Differential diagnosis of thyrotoxicosis is essential because therapeutic approaches differ based on disease etiology. We aimed to perform differential diagnosis of thyrotoxicosis using machine learning algorithms with initial laboratory findings. This is a retrospective study through medical records. Patients who visited a single hospital for thyrotoxicosis from June 2016 to December 2021 were enrolled. In total, 230 subjects were analyzed: 124 (52.6%) patients had Graves\u2019 disease, 65 (28.3%) suffered from painless thyroiditis, and 41 (17.8%) were diagnosed with subacute thyroiditis. In consideration that results for the thyroid autoantibody test cannot be immediately confirmed, two different models were devised: Model 1 included triiodothyronine (T3), free thyroxine (FT4), T3 to FT4 ratio, erythrocyte sediment rate, and C-reactive protein (CRP); and Model 2 included all Model 1 variables as well as thyroid autoantibody test results, including thyrotropin binding inhibitory immunoglobulin (TBII), thyroid-stimulating immunoglobulin, anti-thyroid peroxidase antibody, and anti-thyroglobulin antibody (TgAb). Differential diagnosis accuracy was calculated using seven machine learning algorithms. In the initial blood test, Graves\u2019 disease was characterized by increased thyroid hormone levels and subacute thyroiditis showing elevated inflammatory markers. The diagnostic accuracy of Model 1 was 65\u201370%, and Model 2 accuracy was 78\u201390%. The random forest model had the highest classification accuracy. The significant variables were CRP and T3 in Model 1 and TBII, CRP, and TgAb in Model 2. We suggest monitoring the initial T3 and CRP levels with subsequent confirmation of TBII and TgAb in the differential diagnosis of thyrotoxicosis.<\/jats:p>","DOI":"10.3390\/diagnostics12061468","type":"journal-article","created":{"date-parts":[[2022,6,15]],"date-time":"2022-06-15T22:17:01Z","timestamp":1655331421000},"page":"1468","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Differential Diagnosis of Thyrotoxicosis by Machine Learning Models with Laboratory Findings"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4581-9493","authenticated-orcid":false,"given":"Jinyoung","family":"Kim","sequence":"first","affiliation":[{"name":"Division of Endocrinology and Metabolism, Department of Internal Medicine, Yeouido St. Mary\u2019s Hospital, College of Medicine, The Catholic University of Korea, 10 63-ro, Yeongdeungpo-gu, Seoul 07345, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6896-9024","authenticated-orcid":false,"given":"Han-Sang","family":"Baek","sequence":"additional","affiliation":[{"name":"Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary\u2019s Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jeonghoon","family":"Ha","sequence":"additional","affiliation":[{"name":"Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary\u2019s Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mee Kyoung","family":"Kim","sequence":"additional","affiliation":[{"name":"Division of Endocrinology and Metabolism, Department of Internal Medicine, Yeouido St. Mary\u2019s Hospital, College of Medicine, The Catholic University of Korea, 10 63-ro, Yeongdeungpo-gu, Seoul 07345, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4026-4572","authenticated-orcid":false,"given":"Hyuk-Sang","family":"Kwon","sequence":"additional","affiliation":[{"name":"Division of Endocrinology and Metabolism, Department of Internal Medicine, Yeouido St. Mary\u2019s Hospital, College of Medicine, The Catholic University of Korea, 10 63-ro, Yeongdeungpo-gu, Seoul 07345, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ki-Ho","family":"Song","sequence":"additional","affiliation":[{"name":"Division of Endocrinology and Metabolism, Department of Internal Medicine, Yeouido St. Mary\u2019s Hospital, College of Medicine, The Catholic University of Korea, 10 63-ro, Yeongdeungpo-gu, Seoul 07345, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0995-6482","authenticated-orcid":false,"given":"Dong-Jun","family":"Lim","sequence":"additional","affiliation":[{"name":"Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary\u2019s Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4097-1077","authenticated-orcid":false,"given":"Ki-Hyun","family":"Baek","sequence":"additional","affiliation":[{"name":"Division of Endocrinology and Metabolism, Department of Internal Medicine, Yeouido St. Mary\u2019s Hospital, College of Medicine, The Catholic University of Korea, 10 63-ro, Yeongdeungpo-gu, Seoul 07345, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,6,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1343","DOI":"10.1089\/thy.2016.0229","article-title":"2016 American thyroid association guidelines for diagnosis and management of hyperthyroidism and other causes of thyrotoxicosis","volume":"26","author":"Ross","year":"2016","journal-title":"Thyroid"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1159\/000490384","article-title":"2018 European thyroid association guideline for the management of graves\u2019 hyperthyroidism","volume":"7","author":"Kahaly","year":"2018","journal-title":"Eur. 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