{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,21]],"date-time":"2026-08-21T12:58:43Z","timestamp":1787317123452,"version":"build-2736575974"},"reference-count":37,"publisher":"Wiley","issue":"12","license":[{"start":{"date-parts":[[2025,7,11]],"date-time":"2025-07-11T00:00:00Z","timestamp":1752192000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2025,7,11]],"date-time":"2025-07-11T00:00:00Z","timestamp":1752192000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Head &amp;amp; Neck"],"published-print":{"date-parts":[[2025,12]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Importance<\/jats:title>\n                    <jats:p>Predicting primary hyperparathyroidism in data may facilitate earlier diagnosis and treatment.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>Primary Hyperparathyroidism (pHPT) is the leading cause of hypercalcemia and up to 75% of hypercalcemic patients go undiagnosed. The purpose of this study was to examine the use of predictive modeling using a large clinical database to predict pHPT in patients with benign thyroid nodules.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Design<\/jats:title>\n                    <jats:p>Retrospective analysis and predictive modeling of pHPT using a large discharge database. A predictive model of pHPT was created using logistic regression and compared to three machine learning algorithms: a Gaussian naive Bayes classifier, a stochastic gradient descent classifier, and a histogram\u2010based gradient boosting classifier.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Setting<\/jats:title>\n                    <jats:p>Vizient hospital discharge database from over 1000 hospitals including academic health centers.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Participants<\/jats:title>\n                    <jats:p>Data from the Vizient Clinical Database (CDB), 2\u2009541\u2009901 patients with benign thyroid nodules were identified between 2020 and 2023, of whom 83\u2009555 (3.29%) had pHPT.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Intervention(s) (For Clinical Trials) or Exposure(s) (For Observational Studies)<\/jats:title>\n                    <jats:p>Analyses controlled for demographics (age, sex, race), comorbidities (body mass index (BMI), diabetes, hypertension, smoking status, renal disease) and use of proton pump inhibitors and bisphosphonates.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Main Outcome(s) and Measure(s)<\/jats:title>\n                    <jats:p>The primary outcome measure was the presence of pHPT, which was identified using ICD\u201010 codes. Model performance was compared using the area under the receiver operating characteristics (ROC) curve.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>In the baseline predictive model, several demographic characteristics were significant predictors of pHPT. The logistic regression model had an area under the ROC curve of 68.1%, which was lower than that of the histogram gradient boosting model (68.7%) but equivalent to the gradient descent classifier (68.1%). Furthermore, the logistic regression model correctly classified 80.4% of pHPT cases, compared to 80.5% for both the histogram gradient boosting classifier and the gradient descent classifier. A threshold of 5% yielded a sensitivity of 38.5% and specificity of 81.8% for logistic regression.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions and Relevance<\/jats:title>\n                    <jats:p>Predictive modeling of pHPT among patients with benign thyroid nodules is possible using a large clinical database. The predictive equation could be built into decision support systems to alert clinicians to potentially undiagnosed pHPT and aid in timely diagnosis and treatment of pHPT.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/hed.28247","type":"journal-article","created":{"date-parts":[[2025,7,12]],"date-time":"2025-07-12T04:19:40Z","timestamp":1752293980000},"page":"3251-3260","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Predictive Modeling of Hyperparathyroidism in Patients With Benign Thyroid Nodules: A Cohort Study Using the Vizient Database"],"prefix":"10.1002","volume":"47","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3362-814X","authenticated-orcid":false,"given":"Christopher S.","family":"Hollenbeak","sequence":"first","affiliation":[{"name":"Department of Health Policy and Administration College of Health and Human Development, The Pennsylvania State University  Pennsylvania USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4760-3517","authenticated-orcid":false,"given":"Qiang","family":"Hao","sequence":"additional","affiliation":[{"name":"Department of Health Policy and Administration College of Health and Human Development, The Pennsylvania State University  Pennsylvania USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Melody","family":"Greer","sequence":"additional","affiliation":[{"name":"Department of Biomedical Informatics College of Medicine, University of Arkansas for Medical Sciences  Little Rock Arkansas USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Totton A.","family":"Hollenbeak","sequence":"additional","affiliation":[{"name":"Department of Health Policy and Administration College of Health and Human Development, The Pennsylvania State University  Pennsylvania USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2896-1615","authenticated-orcid":false,"suffix":"Jr.","given":"Brendan C.","family":"Stack","sequence":"additional","affiliation":[{"name":"Retired From Department of Otolaryngology\u2010Head and Neck Surgery Southern Illinois University School of Medicine  Springfield Illinois USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2025,7,11]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.0954-6820.1973.tb10557.x"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.surg.2019.07.031"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.1002\/jbmr.5650061413"},{"key":"e_1_2_8_5_1","doi-asserted-by":"publisher","DOI":"10.1007\/BF03346443"},{"key":"e_1_2_8_6_1","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2022.18331"},{"key":"e_1_2_8_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.otc.2023.07.010"},{"key":"e_1_2_8_8_1","doi-asserted-by":"publisher","DOI":"10.1210\/jc.2002\u2010021404"},{"key":"e_1_2_8_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.surg.2013.06.051"},{"key":"e_1_2_8_10_1","doi-asserted-by":"publisher","DOI":"10.1097\/SLA.0000000000002370"},{"key":"e_1_2_8_11_1","doi-asserted-by":"publisher","DOI":"10.1002\/lio2.415"},{"key":"e_1_2_8_12_1","doi-asserted-by":"publisher","DOI":"10.1161\/ATVBAHA.113.303062"},{"key":"e_1_2_8_13_1","doi-asserted-by":"publisher","DOI":"10.21037\/gs.2017.04.01"},{"key":"e_1_2_8_14_1","doi-asserted-by":"publisher","DOI":"10.1001\/archotol.133.10.1013"},{"key":"e_1_2_8_15_1","doi-asserted-by":"publisher","DOI":"10.1097\/01.JMQ.0000755648.57078.39"},{"key":"e_1_2_8_16_1","doi-asserted-by":"publisher","DOI":"10.1097\/00005650\u2010199801000\u201000004"},{"key":"e_1_2_8_17_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.amjoto.2004.03.006"},{"key":"e_1_2_8_18_1","doi-asserted-by":"publisher","DOI":"10.1001\/jamasurg.2020.2423"},{"key":"e_1_2_8_19_1","doi-asserted-by":"publisher","DOI":"10.1210\/clinem\/dgab540"},{"key":"e_1_2_8_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jocd.2012.12.001"},{"key":"e_1_2_8_21_1","doi-asserted-by":"publisher","DOI":"10.21037\/gs\u201023\u2010487"},{"key":"e_1_2_8_22_1","doi-asserted-by":"publisher","DOI":"10.1210\/jc.2012\u20104022"},{"key":"e_1_2_8_23_1","doi-asserted-by":"publisher","DOI":"10.1038\/nrendo.2017.104"},{"key":"e_1_2_8_24_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.surg.2024.06.026"},{"key":"e_1_2_8_25_1","unstructured":"US Census Bureau \u201cCensus Regions and Divisions of the United States \u201daccessed October 8 2024 https:\/\/www2.census.gov\/geo\/pdfs\/maps\u2010data\/maps\/reference\/us_regdiv.pdf."},{"key":"e_1_2_8_26_1","doi-asserted-by":"publisher","DOI":"10.1002\/hed.26970"},{"key":"e_1_2_8_27_1","doi-asserted-by":"publisher","DOI":"10.1002\/jbmr.4677"},{"key":"e_1_2_8_28_1","doi-asserted-by":"publisher","DOI":"10.1177\/0194599820983728"},{"key":"e_1_2_8_29_1","doi-asserted-by":"publisher","DOI":"10.1530\/EJE\u201017\u20100485"},{"key":"e_1_2_8_30_1","doi-asserted-by":"publisher","DOI":"10.2174\/0115701611280905231227045826"},{"key":"e_1_2_8_31_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00774\u2010021\u201001256\u20109"},{"key":"e_1_2_8_32_1","doi-asserted-by":"publisher","DOI":"10.1210\/jc.2011\u20100569"},{"key":"e_1_2_8_33_1","doi-asserted-by":"publisher","DOI":"10.1111\/cen.15118"},{"key":"e_1_2_8_34_1","doi-asserted-by":"publisher","DOI":"10.3389\/fendo.2021.665984"},{"key":"e_1_2_8_35_1","doi-asserted-by":"publisher","DOI":"10.1210\/jc.2013\u20103903"},{"key":"e_1_2_8_36_1","doi-asserted-by":"publisher","DOI":"10.1002\/jbmr.4665"},{"key":"e_1_2_8_37_1","doi-asserted-by":"publisher","DOI":"10.1111\/jgs.13661"},{"key":"e_1_2_8_38_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.amjsurg.2011.09.014"}],"container-title":["Head &amp; Neck"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/hed.28247","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/hed.28247","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/hed.28247","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T16:01:05Z","timestamp":1772985665000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/hed.28247"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,11]]},"references-count":37,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2025,12]]}},"alternative-id":["10.1002\/hed.28247"],"URL":"https:\/\/doi.org\/10.1002\/hed.28247","archive":["Portico"],"relation":{},"ISSN":["1043-3074","1097-0347"],"issn-type":[{"value":"1043-3074","type":"print"},{"value":"1097-0347","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,7,11]]},"assertion":[{"value":"2025-03-18","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-07-04","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-07-11","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}