{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T18:05:51Z","timestamp":1789063551100,"version":"build-2803163510"},"reference-count":51,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T00:00:00Z","timestamp":1788998400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Neurol."],"abstract":"<jats:sec>\n                    <jats:title>Background and purpose<\/jats:title>\n                    <jats:p>Prehospital delay remains a major barrier to timely reperfusion therapy in acute ischemic stroke (AIS). We externally validated eight prediction algorithms and examined whether complex machine-learning models added value beyond logistic regression.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      This retrospective cohort study included consecutive patients with AIS from two hospitals in Kashgar, China (January 2019\u2013December 2024). Hospital 1 (\n                      <jats:italic>n<\/jats:italic>\n                      \u202f=\u202f1,377) was the development cohort and Hospital 2 (\n                      <jats:italic>n<\/jats:italic>\n                      \u202f=\u202f1,015) the independent validation cohort. Prehospital delay was defined as onset-to-door time &amp;gt;4.5\u202fh. LASSO selection and tuning were restricted to Hospital 1. Sensitivity analyses used all 36 encoded candidate features and repeated all models without SMOTE. Evaluation included discrimination, calibration, post-hoc recalibration, and decision curves.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Delay occurred in 80.9 and 83.2% of the two cohorts. In the prespecified LASSO-plus-SMOTE analysis, XGBoost had the highest validation AUC (0.771; 95% CI, 0.734\u20130.807), but did not significantly outperform logistic regression (difference, 0.015; 95% CI, \u22120.003 to 0.034;\n                      <jats:italic>p<\/jats:italic>\n                      \u202f=\u202f0.107). Full-feature modeling produced no consistent gain. Omitting SMOTE improved calibration and often discrimination; logistic regression without SMOTE achieved AUC 0.774 and Brier score 0.122, versus 0.756 and 0.180 with SMOTE. The original SMOTE-trained logistic model underestimated absolute risk. Rural residence, non-emergency-channel presentation, referral, and non-ambulance transport were associated with absolute risk differences of 15.8, 21.5, 9.2, and 36.3 percentage points in Hospital 2.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Complex algorithms did not show a clear advantage over logistic regression. Because several predictors are available only after arrival, the framework is intended for retrospective health-system profiling and quality-improvement planning, not individual pre-arrival prediction. Universal interventions remain warranted given the high prevalence of delay.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fneur.2026.1867290","type":"journal-article","created":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T17:06:10Z","timestamp":1789059970000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["External validation of machine learning models for predicting prehospital delay in acute ischemic stroke: a retrospective cohort study"],"prefix":"10.3389","volume":"17","author":[{"given":"Shan","family":"Zeng","sequence":"first","affiliation":[{"name":"People\u2019s Hospital of Xinjiang Uygur Autonomous Region","place":["Urumqi, Xinjiang, China"]},{"name":"Xinjiang Clinical Research Center for Stroke and Rare Neurological Disease","place":["Urumqi, Xinjiang, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aishanjiang","family":"Yusufujiang","sequence":"additional","affiliation":[{"name":"People\u2019s Hospital of Xinjiang Uygur Autonomous Region","place":["Urumqi, Xinjiang, China"]},{"name":"Xinjiang Clinical Research Center for Stroke and Rare Neurological Disease","place":["Urumqi, Xinjiang, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hui","family":"Dang","sequence":"additional","affiliation":[{"name":"People\u2019s Hospital of Xinjiang Uygur Autonomous Region","place":["Urumqi, Xinjiang, China"]},{"name":"Xinjiang Clinical Research Center for Stroke and Rare Neurological Disease","place":["Urumqi, Xinjiang, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Zhu","sequence":"additional","affiliation":[{"name":"People\u2019s Hospital of Xinjiang Uygur Autonomous Region","place":["Urumqi, Xinjiang, China"]},{"name":"Xinjiang Clinical Research Center for Stroke and Rare Neurological Disease","place":["Urumqi, Xinjiang, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abudukeyoumu","family":"Yasheng","sequence":"additional","affiliation":[{"name":"Kashi Prefecture Second People\u2019s Hospital","place":["Kashi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingjing","family":"Wang","sequence":"additional","affiliation":[{"name":"The First People\u2019s Hospital of Kashi Prefecture","place":["Kashi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Yan","sequence":"additional","affiliation":[{"name":"The First People\u2019s Hospital of Kashi Prefecture","place":["Kashi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huijuan","family":"Yu","sequence":"additional","affiliation":[{"name":"The First People\u2019s Hospital of Kashi Prefecture","place":["Kashi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gulijanat","family":"Mamattursun","sequence":"additional","affiliation":[{"name":"The First People\u2019s Hospital of Kashi Prefecture","place":["Kashi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maierpu\u00b7","family":"Aini","sequence":"additional","affiliation":[{"name":"Kashi Prefecture Second People\u2019s Hospital","place":["Kashi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Di","family":"Kang","sequence":"additional","affiliation":[{"name":"Kashi Prefecture Second People\u2019s Hospital","place":["Kashi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongyan","family":"Li","sequence":"additional","affiliation":[{"name":"People\u2019s Hospital of Xinjiang Uygur Autonomous Region","place":["Urumqi, Xinjiang, China"]},{"name":"Xinjiang Clinical Research Center for Stroke and Rare Neurological Disease","place":["Urumqi, Xinjiang, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,9,10]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"e344","DOI":"10.1161\/STR.0000000000000211","article-title":"Guidelines for the early Management of Patients with Acute Ischemic Stroke: 2019 update to the 2018 guidelines for the early Management of Acute Ischemic Stroke: a guideline for healthcare professionals from the American Heart Association\/American Stroke Association","volume":"50","author":"Powers","year":"2019","journal-title":"Stroke"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"1929","DOI":"10.1016\/S0140-6736(14)60584-5","article-title":"Effect of treatment delay, age, and stroke severity on the effects of intravenous thrombolysis with alteplase for acute ischaemic stroke: a meta-analysis of individual patient data from randomised trials","volume":"384","author":"Emberson","year":"2014","journal-title":"Lancet"},{"key":"ref3","doi-asserted-by":"publisher","first-page":"1723","DOI":"10.1016\/S0140-6736(16)00163-X","article-title":"Endovascular thrombectomy after large-vessel ischaemic stroke: a meta-analysis of individual patient data from five randomised trials","volume":"387","author":"Goyal","year":"2016","journal-title":"Lancet"},{"key":"ref4","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1111\/j.1747-4949.2009.00276.x","article-title":"A comprehensive review of prehospital and in-hospital delay times in acute stroke care","volume":"4","author":"Evenson","year":"2009","journal-title":"Int J Stroke"},{"key":"ref5","doi-asserted-by":"publisher","first-page":"585","DOI":"10.1016\/S1474-4422(13)70100-5","article-title":"Streamlining of prehospital stroke management: the golden hour","volume":"12","author":"Fassbender","year":"2013","journal-title":"Lancet Neurol"},{"key":"ref6","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1161\/01.str.32.1.63","article-title":"Delay in presentation and evaluation for acute stroke: stroke time registry for outcomes knowledge and epidemiology (STROKE)","volume":"32","author":"Lacy","year":"2001","journal-title":"Stroke"},{"key":"ref7","doi-asserted-by":"publisher","first-page":"1978","DOI":"10.1161\/STROKEAHA.110.583591","article-title":"A computerized in-hospital alert system for thrombolysis in acute stroke","volume":"41","author":"Heo","year":"2010","journal-title":"Stroke"},{"key":"ref8","doi-asserted-by":"publisher","first-page":"575","DOI":"10.1161\/STROKEAHA.114.007850","article-title":"Comparing National Institutes of Health stroke scale among a stroke team and helicopter emergency medical service providers","volume":"46","author":"Kesinger","year":"2015","journal-title":"Stroke"},{"key":"ref9","doi-asserted-by":"publisher","first-page":"2763","DOI":"10.1016\/j.jstrokecerebrovasdis.2017.06.053","article-title":"Prehospital and in-hospital delays in ischemic stroke care","volume":"26","author":"Zhao","year":"2017","journal-title":"J Stroke Cerebrovasc Dis"},{"key":"ref10","doi-asserted-by":"publisher","first-page":"245","DOI":"10.1016\/j.jclinepi.2015.04.005","article-title":"Prediction models need appropriate internal, internal-external, and external validation","volume":"69","author":"Steyerberg","year":"2016","journal-title":"J Clin Epidemiol"},{"key":"ref11","doi-asserted-by":"publisher","first-page":"40","DOI":"10.1186\/1471-2288-14-40","article-title":"External validation of multivariable prediction models: a systematic review of methodological conduct and reporting","volume":"14","author":"Collins","year":"2014","journal-title":"BMC Med Res Methodol"},{"key":"ref12","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1016\/j.jclinepi.2014.09.007","article-title":"External validation of new risk prediction models is infrequent and reveals worse prognostic discrimination","volume":"68","author":"Siontis","year":"2015","journal-title":"J Clin Epidemiol"},{"key":"ref13","doi-asserted-by":"publisher","first-page":"g7594","DOI":"10.1136\/bmj.g7594","article-title":"Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement","volume":"350","author":"Collins","year":"2015","journal-title":"BMJ"},{"key":"ref14","doi-asserted-by":"publisher","first-page":"1216","DOI":"10.1056\/NEJMp1606181","article-title":"Predicting the future - big data, machine learning, and clinical medicine","volume":"375","author":"Obermeyer","year":"2016","journal-title":"N Engl J Med"},{"key":"ref15","doi-asserted-by":"publisher","first-page":"1347","DOI":"10.1056\/NEJMra1814259","article-title":"Machine learning in medicine","volume":"380","author":"Rajkomar","year":"2019","journal-title":"N Engl J Med"},{"key":"ref16","doi-asserted-by":"publisher","first-page":"1317","DOI":"10.1001\/jama.2017.18391","article-title":"Big data and machine learning in health care","volume":"319","author":"Beam","year":"2018","journal-title":"JAMA"},{"key":"ref17","doi-asserted-by":"publisher","first-page":"206","DOI":"10.1038\/s42256-019-0048-x","article-title":"Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead","volume":"1","author":"Rudin","year":"2019","journal-title":"Nat Mach Intell."},{"key":"ref18","first-page":"541","article-title":"Experience from a multicentre stroke register: a preliminary report","volume":"54","author":"Hatano","year":"1976","journal-title":"Bull World Health Organ"},{"key":"ref19","doi-asserted-by":"publisher","first-page":"611","DOI":"10.1056\/NEJMoa1804355","article-title":"MRI-guided thrombolysis for stroke with unknown time of onset","volume":"379","author":"Thomalla","year":"2018","journal-title":"N Engl J Med"},{"key":"ref20","doi-asserted-by":"publisher","first-page":"1186","DOI":"10.1161\/STROKEAHA.111.639732","article-title":"Socioeconomic status and stroke: an updated review","volume":"43","author":"Addo","year":"2012","journal-title":"Stroke"},{"key":"ref21","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2382577.2382579","article-title":"Leakage in data mining: formulation, detection, and avoidance","volume":"6","author":"Kaufman","year":"2012","journal-title":"ACM Trans Knowl Discov Data"},{"key":"ref22","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1111\/j.2517-6161.1996.tb02080.x","article-title":"Regression shrinkage and selection via the lasso","volume":"58","author":"Tibshirani","year":"1996","journal-title":"J R Stat Soc B Stat Methodol"},{"key":"ref23","doi-asserted-by":"publisher","first-page":"1","DOI":"10.18637\/jss.v033.i01","article-title":"Regularization paths for generalized linear models via coordinate descent","volume":"33","author":"Friedman","year":"2010","journal-title":"J Stat Softw"},{"key":"ref24","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1613\/jair.953","article-title":"SMOTE: synthetic minority over-sampling technique","volume":"16","author":"Chawla","year":"2002","journal-title":"J Artif Intell Res"},{"key":"ref25","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1038\/s42256-019-0138-9","article-title":"From local explanations to global understanding with explainable AI for trees","volume":"2","author":"Lundberg","year":"2020","journal-title":"Nat Mach Intell"},{"key":"ref26","doi-asserted-by":"publisher","first-page":"362","DOI":"10.1161\/STROKEAHA.111.623512","article-title":"Factors associated with prehospital delays in the presentation of acute stroke in urban China","volume":"43","author":"Jin","year":"2012","journal-title":"Stroke"},{"key":"ref27","doi-asserted-by":"publisher","first-page":"168","DOI":"10.1161\/CIRCULATIONAHA.106.176040","article-title":"Reducing delay in seeking treatment by patients with acute coronary syndrome and stroke: a scientific statement from the American Heart Association Council on cardiovascular nursing and stroke council","volume":"114","author":"Moser","year":"2006","journal-title":"Circulation"},{"key":"ref28","doi-asserted-by":"publisher","first-page":"138","DOI":"10.3988\/jcn.2010.6.3.138","article-title":"Prehospital notification from the emergency medical service reduces the transfer and intra-hospital processing times for acute stroke patients","volume":"6","author":"Bae","year":"2010","journal-title":"J Clin Neurol"},{"key":"ref29","doi-asserted-by":"publisher","first-page":"3845","DOI":"10.1161\/STROKEAHA.109.562660","article-title":"Hospital arrival time and intravenous t-PA use in US academic medical centers, 2001-2004","volume":"40","author":"Lichtman","year":"2009","journal-title":"Stroke"},{"key":"ref30","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1186\/1471-227X-11-5","article-title":"Provider perceptions of barriers to the emergency use of tPA for acute ischemic stroke: a qualitative study","volume":"11","author":"Meurer","year":"2011","journal-title":"BMC Emerg Med"},{"key":"ref31","doi-asserted-by":"publisher","first-page":"e27","DOI":"10.1161\/01.STR.0000109767.11426.17","article-title":"Eligibility for recombinant tissue plasminogen activator in acute ischemic stroke: a population-based study","volume":"35","author":"Kleindorfer","year":"2004","journal-title":"Stroke"},{"key":"ref32","doi-asserted-by":"publisher","first-page":"1632","DOI":"10.1001\/jama.2014.3203","article-title":"Door-to-needle times for tissue plasminogen activator administration and clinical outcomes in acute ischemic stroke before and after a quality improvement initiative","volume":"311","author":"Fonarow","year":"2014","journal-title":"JAMA"},{"key":"ref33","doi-asserted-by":"publisher","first-page":"427","DOI":"10.1212\/wnl.51.2.427","article-title":"Critical factors determining access to acute stroke care","volume":"51","author":"Menon","year":"1998","journal-title":"Neurology"},{"key":"ref34","doi-asserted-by":"publisher","first-page":"230","DOI":"10.1186\/s12916-019-1466-7","article-title":"Calibration: the Achilles heel of predictive analytics","volume":"17","author":"Van Calster","year":"2019","journal-title":"BMC Med"},{"key":"ref35","doi-asserted-by":"publisher","first-page":"160","DOI":"10.1161\/hs0102.101990","article-title":"Improving delivery of acute stroke therapy: the TLL Temple foundation stroke project","volume":"33","author":"Morgenstern","year":"2002","journal-title":"Stroke"},{"key":"ref36","doi-asserted-by":"publisher","first-page":"1626","DOI":"10.1161\/STROKEAHA.110.609750","article-title":"Transfer delay is a major factor limiting the use of intra-arterial treatment in acute ischemic stroke","volume":"42","author":"Prabhakaran","year":"2011","journal-title":"Stroke"},{"key":"ref37","doi-asserted-by":"publisher","first-page":"1622","DOI":"10.1001\/jama.2014.2850","article-title":"Effect of the use of ambulance-based thrombolysis on time to thrombolysis in acute ischemic stroke: a randomized clinical trial","volume":"311","author":"Ebinger","year":"2014","journal-title":"JAMA"},{"key":"ref38","doi-asserted-by":"publisher","first-page":"2616","DOI":"10.1161\/STROKEAHA.109.192360","article-title":"A review of the evidence for the use of telemedicine within stroke systems of care: a scientific statement from the American Heart Association\/American Stroke Association","volume":"40","author":"Schwamm","year":"2009","journal-title":"Stroke"},{"key":"ref39","doi-asserted-by":"publisher","first-page":"2263","DOI":"10.1161\/STROKEAHA.110.605857","article-title":"Prehospital notification by emergency medical services reduces delays in stroke evaluation: findings from the North Carolina stroke care collaborative","volume":"42","author":"Patel","year":"2011","journal-title":"Stroke"},{"key":"ref40","first-page":"359","article-title":"What clinicians want: contextualizing explainable machine learning for clinical end use","volume":"106","author":"Tonekaboni","year":"2019","journal-title":"Proc Mach Learn Res"},{"key":"ref41","doi-asserted-by":"publisher","first-page":"100804","DOI":"10.1016\/j.patter.2023.100804","article-title":"Leakage and the reproducibility crisis in machine-learning-based science","volume":"4","author":"Kapoor","year":"2023","journal-title":"Patterns (N Y)"},{"key":"ref42","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1109\/MCI.2018.2866730","article-title":"Cross-validation for imbalanced datasets: avoiding overoptimistic and overfitting approaches","volume":"13","author":"Santos","year":"2018","journal-title":"IEEE Comput Intell Mag"},{"key":"ref43","first-page":"4765","article-title":"A unified approach to interpreting model predictions","volume":"30","author":"Lundberg","year":"2017","journal-title":"Adv Neural Inf Process Syst"},{"key":"ref44","doi-asserted-by":"publisher","first-page":"279","DOI":"10.1016\/j.jclinepi.2014.06.018","article-title":"A new framework to enhance the interpretation of external validation studies of clinical prediction models","volume":"68","author":"Debray","year":"2015","journal-title":"J Clin Epidemiol"},{"key":"ref45","doi-asserted-by":"publisher","first-page":"565","DOI":"10.1177\/0272989X06295361","article-title":"Decision curve analysis: a novel method for evaluating prediction models","volume":"26","author":"Vickers","year":"2006","journal-title":"Med Decis Mak"},{"key":"ref46","doi-asserted-by":"publisher","first-page":"1373","DOI":"10.1016\/s0895-4356(96)00236-3","article-title":"A simulation study of the number of events per variable in logistic regression analysis","volume":"49","author":"Peduzzi","year":"1996","journal-title":"J Clin Epidemiol"},{"key":"ref47","doi-asserted-by":"publisher","first-page":"1453","DOI":"10.1016\/S0140-6736(07)61602-X","article-title":"The strengthening the reporting of observational studies in epidemiology (STROBE) statement: guidelines for reporting observational studies","volume":"370","author":"von Elm","year":"2007","journal-title":"Lancet"},{"key":"ref48","doi-asserted-by":"publisher","first-page":"e1001381","DOI":"10.1371\/journal.pmed.1001381","article-title":"Prognosis research strategy (PROGRESS) 3: prognostic model research","volume":"10","author":"Steyerberg","year":"2013","journal-title":"PLoS Med"},{"key":"ref49","doi-asserted-by":"publisher","first-page":"6562","DOI":"10.1073\/pnas.102102699","article-title":"Selection bias in gene extraction on the basis of microarray gene-expression data","volume":"99","author":"Ambroise","year":"2002","journal-title":"Proc Natl Acad Sci USA"},{"key":"ref50","doi-asserted-by":"crossref","DOI":"10.1007\/978-0-387-84858-7","volume-title":"The Elements of Statistical Learning: Data Mining, Inference, and Prediction","author":"Hastie","year":"2009"},{"key":"ref51","doi-asserted-by":"publisher","first-page":"1269","DOI":"10.1016\/S0140-6736(18)31269-8","article-title":"Prevention of stroke: a global perspective","volume":"392","author":"Pandian","year":"2018","journal-title":"Lancet"}],"container-title":["Frontiers in Neurology"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fneur.2026.1867290\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T17:06:13Z","timestamp":1789059973000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fneur.2026.1867290\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9,10]]},"references-count":51,"alternative-id":["10.3389\/fneur.2026.1867290"],"URL":"https:\/\/doi.org\/10.3389\/fneur.2026.1867290","relation":{},"ISSN":["1664-2295"],"issn-type":[{"value":"1664-2295","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,9,10]]},"article-number":"1867290"}}