{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T20:19:35Z","timestamp":1785442775051,"version":"3.56.0"},"reference-count":10,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"8","content-domain":{"domain":["www.ahajournals.org"],"crossmark-restriction":true},"short-container-title":["Stroke"],"published-print":{"date-parts":[[2021,8]]},"abstract":"\n Background and Purpose:<\/jats:title>\n Accurate prehospital diagnosis of stroke by emergency medical services (EMS) can increase treatments rates, mitigate disability, and reduce stroke deaths. We aimed to develop a model that utilizes natural language processing of EMS reports and machine learning to improve prehospital stroke identification.<\/jats:p>\n <\/jats:sec>\n \n Methods:<\/jats:title>\n We conducted a retrospective study of patients transported by the Chicago EMS to 17 regional primary and comprehensive stroke centers. Patients who were suspected of stroke by the EMS or had hospital-diagnosed stroke were included in our cohort. Text within EMS reports were converted to unigram features, which were given as input to a support-vector machine classifier that was trained on 70% of the cohort and tested on the remaining 30%. Outcomes included final diagnosis of stroke versus nonstroke, large vessel occlusion, severe stroke (National Institutes of Health Stroke Scale score >5), and comprehensive stroke center-eligible stroke (large vessel occlusion or hemorrhagic stroke).<\/jats:p>\n <\/jats:sec>\n \n Results:<\/jats:title>\n \n Of 965 patients, 580 (60%) had confirmed acute stroke. In a test set of 289 patients, the text-based model predicted stroke nominally better than models based on the Cincinnati Prehospital Stroke Scale (\n c<\/jats:italic>\n -statistic: 0.73 versus 0.67,\n P<\/jats:italic>\n =0.165) and was superior to the 3-Item Stroke Scale (\n c<\/jats:italic>\n -statistic: 0.73 versus 0.53,\n P<\/jats:italic>\n <0.001) scores. Improvements in discrimination were also observed for the other outcomes.\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions:<\/jats:title>\n We derived a model that utilizes clinical text from paramedic reports to identify stroke. Our results require validation but have the potential of improving prehospital routing protocols.<\/jats:p>\n <\/jats:sec>","DOI":"10.1161\/strokeaha.120.033580","type":"journal-article","created":{"date-parts":[[2021,6,24]],"date-time":"2021-06-24T09:01:55Z","timestamp":1624525315000},"page":"2676-2679","update-policy":"https:\/\/doi.org\/10.1161\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":32,"title":["Improving Prehospital Stroke Diagnosis Using Natural Language Processing of Paramedic Reports"],"prefix":"10.1161","volume":"52","author":[{"given":"Anoop","family":"Mayampurath","sequence":"first","affiliation":[{"name":"Department of Pediatrics (A.M.), University of Chicago, IL."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zahra","family":"Parnianpour","sequence":"additional","affiliation":[{"name":"Department of Neurology (Z.P., S.J.M., J.L.H., S.P.), University of Chicago, IL."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3728-3860","authenticated-orcid":true,"given":"Christopher T.","family":"Richards","sequence":"additional","affiliation":[{"name":"Department of Emergency Medicine, University of Cincinnati, OH (C.T.R.)."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1158-5302","authenticated-orcid":true,"given":"William J.","family":"Meurer","sequence":"additional","affiliation":[{"name":"Department of Emergency Medicine, University of Michigan, Ann Arbor, IL (W.J.M.)."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jungwha","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL (J.L.)."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bruce","family":"Ankenman","sequence":"additional","affiliation":[{"name":"Department of Industrial Engineering and Management Studies, Northwestern University (B.A., O.P.)."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ohad","family":"Perry","sequence":"additional","affiliation":[{"name":"Department of Industrial Engineering and Management Studies, Northwestern University (B.A., O.P.)."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3512-4332","authenticated-orcid":true,"given":"Scott J.","family":"Mendelson","sequence":"additional","affiliation":[{"name":"Department of Neurology (Z.P., S.J.M., J.L.H., S.P.), University of Chicago, IL."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jane L.","family":"Holl","sequence":"additional","affiliation":[{"name":"Department of Neurology (Z.P., S.J.M., J.L.H., S.P.), University of Chicago, IL."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0724-1694","authenticated-orcid":true,"given":"Shyam","family":"Prabhakaran","sequence":"additional","affiliation":[{"name":"Department of Neurology (Z.P., S.J.M., J.L.H., S.P.), University of Chicago, IL."}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"276","reference":[{"key":"e_1_3_6_2_2","doi-asserted-by":"publisher","DOI":"10.1161\/CIR.0000000000000152"},{"key":"e_1_3_6_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(10)60491-6"},{"key":"e_1_3_6_4_2","doi-asserted-by":"publisher","DOI":"10.1212\/WNL.0b013e31829e0fdd"},{"key":"e_1_3_6_5_2","doi-asserted-by":"publisher","DOI":"10.1016\/s0196-0644(99)70299-4"},{"key":"e_1_3_6_6_2","doi-asserted-by":"crossref","first-page":"773","DOI":"10.1161\/01.STR.0000157591.61322.df","article-title":"A simple 3-item stroke scale.","volume":"36","author":"Singer OC","year":"2005","unstructured":"Singer, OC, Dvorak, F, du Mesnil de Rochemont, R, Lanfermann, H, Sitzer, M, Neumann-Haefelin, T. A simple 3-item stroke scale. Stroke. 2005;36:773\u2013776.","journal-title":"Stroke"},{"key":"e_1_3_6_7_2","doi-asserted-by":"publisher","DOI":"10.1161\/STROKEAHA.115.008650"},{"key":"e_1_3_6_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jstrokecerebrovasdis.2017.10.036"},{"key":"e_1_3_6_9_2","doi-asserted-by":"publisher","DOI":"10.1212\/WNL.0000000000000523"},{"key":"e_1_3_6_10_2","doi-asserted-by":"publisher","DOI":"10.1161\/strokeaha.116.013144"},{"key":"e_1_3_6_11_2","doi-asserted-by":"publisher","DOI":"10.1161\/STROKEAHA.118.021794"}],"container-title":["Stroke"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.ahajournals.org\/doi\/full\/10.1161\/STROKEAHA.120.033580","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,5,13]],"date-time":"2024-05-13T15:30:58Z","timestamp":1715614258000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ahajournals.org\/doi\/10.1161\/STROKEAHA.120.033580"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8]]},"references-count":10,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2021,8]]}},"alternative-id":["10.1161\/STROKEAHA.120.033580"],"URL":"https:\/\/doi.org\/10.1161\/strokeaha.120.033580","relation":{},"ISSN":["0039-2499","1524-4628"],"issn-type":[{"value":"0039-2499","type":"print"},{"value":"1524-4628","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,8]]},"assertion":[{"value":"2020-10-19","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2021-03-31","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2021-06-24","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}