{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T08:08:50Z","timestamp":1783066130860,"version":"3.54.6"},"reference-count":42,"publisher":"SAGE Publications","issue":"5","license":[{"start":{"date-parts":[[2018,9,13]],"date-time":"2018-09-13T00:00:00Z","timestamp":1536796800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"DOI":"10.13039\/501100002996","name":"Hartstichting","doi-asserted-by":"publisher","award":["2008 T034"],"award-info":[{"award-number":["2008 T034"]}],"id":[{"id":"10.13039\/501100002996","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002996","name":"Hartstichting","doi-asserted-by":"publisher","award":["2012 T061"],"award-info":[{"award-number":["2012 T061"]}],"id":[{"id":"10.13039\/501100002996","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100008358","name":"Hersenstichting","doi-asserted-by":"publisher","award":["HA2015.01.02"],"award-info":[{"award-number":["HA2015.01.02"]}],"id":[{"id":"10.13039\/501100008358","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003142","name":"Fonds NutsOhra","doi-asserted-by":"publisher","award":["0903-012"],"award-info":[{"award-number":["0903-012"]}],"id":[{"id":"10.13039\/501100003142","id-type":"DOI","asserted-by":"publisher"}]},{"name":"The Dutch Health Care Insurers Innovation Foundation","award":["3240"],"award-info":[{"award-number":["3240"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["International Journal of Stroke"],"published-print":{"date-parts":[[2019,7]]},"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>A clinical large anterior vessel occlusion (LAVO)-prediction scale could reduce treatment delays by allocating intra-arterial thrombectomy (IAT)-eligible patients directly to a comprehensive stroke center.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Aim<\/jats:title>\n                    <jats:p>To subtract, validate and compare existing LAVO-prediction scales, and develop a straightforward decision support tool to assess IAT-eligibility.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We performed a systematic literature search to identify LAVO-prediction scales. Performance was compared in a prospective, multicenter validation cohort of the Dutch acute Stroke study (DUST) by calculating area under the receiver operating curves (AUROC). With group lasso regression analysis, we constructed a prediction model, incorporating patient characteristics next to National Institutes of Health Stroke Scale (NIHSS) items. Finally, we developed a decision tree algorithm based on dichotomized NIHSS items.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>We identified seven LAVO-prediction scales. From DUST, 1316 patients (35.8% LAVO-rate) from 14 centers were available for validation. FAST-ED and RACE had the highest AUROC (both &gt;0.81, p\u2009&lt;\u20090.01 for comparison with other scales). Group lasso analysis revealed a LAVO-prediction model containing seven NIHSS items (AUROC 0.84). With the GACE (Gaze, facial Asymmetry, level of Consciousness, Extinction\/inattention) decision tree, LAVO is predicted (AUROC 0.76) for 61% of patients with assessment of only two dichotomized NIHSS items, and for all patients with four items.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>External validation of seven LAVO-prediction scales showed AUROCs between 0.75 and 0.83. Most scales, however, appear too complex for Emergency Medical Services use with prehospital validation generally lacking. GACE is the first LAVO-prediction scale using a simple decision tree as such increasing feasibility, while maintaining high accuracy. Prehospital prospective validation is planned.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/1747493018801225","type":"journal-article","created":{"date-parts":[[2018,9,13]],"date-time":"2018-09-13T07:21:14Z","timestamp":1536823274000},"page":"530-539","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":15,"title":["Clinical prediction of thrombectomy eligibility: A systematic review and 4-item decision tree"],"prefix":"10.1177","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7138-5313","authenticated-orcid":false,"given":"Gaia T","family":"Koster","sequence":"first","affiliation":[{"name":"Department of Neurology, Leiden University Medical Center, Leiden, Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3545-3053","authenticated-orcid":false,"given":"T Truc My","family":"Nguyen","sequence":"additional","affiliation":[{"name":"Department of Neurology, Leiden University Medical Center, Leiden, Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Erik W","family":"van Zwet","sequence":"additional","affiliation":[{"name":"Department of Medical Statistics, Leiden University Medical Center, Leiden, Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bjarty L","family":"Garcia","sequence":"additional","affiliation":[{"name":"Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hannah R","family":"Rowling","sequence":"additional","affiliation":[{"name":"Department of Neurology, Leiden University Medical Center, Leiden, Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"J","family":"Bosch","sequence":"additional","affiliation":[{"name":"Department of Research and Development, RAV Hollands Midden, Leiden, Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wouter J","family":"Schonewille","sequence":"additional","affiliation":[{"name":"Department of Neurology, St. Antonius Hospital, Nieuwegein, Netherlands; Department of Neurology and Neurosurgery, Brain Center Rudolf Magnus, Utrecht, Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Birgitta K","family":"Velthuis","sequence":"additional","affiliation":[{"name":"Department of Radiology, University Medical Center Utrecht, Utrecht, Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ido R","family":"van den Wijngaard","sequence":"additional","affiliation":[{"name":"Department of Neurology, Haaglanden Medical Center, The Hague, Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Heleen M","family":"den Hertog","sequence":"additional","affiliation":[{"name":"Department of Neurology, Medisch Spectrum Twente; Department of Neurology, Isala Clinics, Zwolle, Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yvo BWEM","family":"Roos","sequence":"additional","affiliation":[{"name":"Department of Neurology, Academic Medical Center, Amsterdam, Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marianne AA","family":"van Walderveen","sequence":"additional","affiliation":[{"name":"Department of Radiology, Leiden University Medical Center, Leiden, Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marieke JH","family":"Wermer","sequence":"additional","affiliation":[{"name":"Department of Neurology, Leiden University Medical Center, Leiden, Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nyika D","family":"Kruyt","sequence":"additional","affiliation":[{"name":"Department of Neurology, Leiden University Medical Center, Leiden, 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