{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,9]],"date-time":"2026-03-09T22:17:52Z","timestamp":1773094672477,"version":"3.50.1"},"reference-count":32,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2025,9,6]],"date-time":"2025-09-06T00:00:00Z","timestamp":1757116800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2025,9,6]],"date-time":"2025-09-06T00:00:00Z","timestamp":1757116800000},"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":["J of Clinical Ultrasound"],"published-print":{"date-parts":[[2026,2]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Acute ischemic stroke (AIS) is characterized by high incidence, sudden onset, and often poor prognosis. Carotid atherosclerosis plays a crucial role in its pathogenesis, and ultrasound imaging offers a non\u2010invasive method for evaluating carotid plaque characteristics. This study aimed to develop and validate a prediction model for AIS risk based on a novel ultrasound\u2010based carotid plaque scoring system combined with clinical risk factors.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      A retrospective case\u2013control study was conducted, including 100 patients with carotid atherosclerosis who attended Hebei General Hospital from January 2022 to December 2023. Patients were divided into an AIS group (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u200960) and a non\u2010AIS group (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u200940). Univariate and multivariable logistic regression analyses were used to identify significant ultrasound and clinical predictors of AIS. A carotid plaque ultrasound scoring system was constructed based on selected imaging features and integrated with clinical risk factors to establish a nomogram prediction model for AIS. The performance of the scoring system and the combined model was evaluated using receiver operating characteristic (ROC) curves, decision curve analysis (DCA), and calibration plots. Internal validation of the AIS prediction model was performed using the bootstrap resampling method.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Independent predictors of AIS included plaque echogenicity, morphology, contrast\u2010enhanced ultrasound score, history of hypertension, C\u2010reactive protein (CRP), fasting blood glucose (FBG), and very\u2010low\u2010density lipoprotein (VLDL). The ultrasound scoring system alone yielded an area under the curve (AUC) of 0.88, while the integrated model incorporating clinical factors achieved an AUC of 0.94. Both calibration and decision curves demonstrated excellent agreement and clinical utility. Bootstrap validation confirmed the model's robustness and reliability.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The carotid plaque ultrasound scoring system provides a reliable method for AIS risk prediction. The AIS prediction model, developed using this scoring system combined with clinical risk factors, improves predictive accuracy and helps in the early identification of high\u2010risk patients.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/jcu.70072","type":"journal-article","created":{"date-parts":[[2025,9,7]],"date-time":"2025-09-07T03:44:00Z","timestamp":1757216640000},"page":"322-333","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Development and Validation of a Prediction Model for Acute Ischemic Stroke Based on a Novel Ultrasound\u2010Based Carotid Plaque Scoring System and Clinical Factors"],"prefix":"10.1002","volume":"54","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-5834-1705","authenticated-orcid":false,"given":"Xiaowen","family":"Sun","sequence":"first","affiliation":[{"name":"Hebei Medical University  Shijiazhuang China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huimin","family":"Niu","sequence":"additional","affiliation":[{"name":"Hebei Medical University  Shijiazhuang China"},{"name":"Hebei General Hospital  Shijiazhuang China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yueying","family":"Pei","sequence":"additional","affiliation":[{"name":"Hebei General Hospital  Shijiazhuang China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaona","family":"Wang","sequence":"additional","affiliation":[{"name":"Hebei General Hospital  Shijiazhuang China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Min","family":"Chen","sequence":"additional","affiliation":[{"name":"Hebei General Hospital  Shijiazhuang China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2025,9,6]]},"reference":[{"key":"e_1_2_11_2_1","doi-asserted-by":"publisher","DOI":"10.2174\/1570161115666171116151051"},{"key":"e_1_2_11_3_1","doi-asserted-by":"publisher","DOI":"10.1111\/ene.14157"},{"key":"e_1_2_11_4_1","doi-asserted-by":"publisher","DOI":"10.3233\/CH-231959"},{"key":"e_1_2_11_5_1","first-page":"75","volume-title":"China Contrast\u2010Enhanced Ultrasound Clinical Application Guidelines","author":"China Medical Association Ultrasound Physicians Branch","year":"2017"},{"issue":"9","key":"e_1_2_11_6_1","first-page":"666","article-title":"Chinese Guidelines for the Diagnosis and Treatment of Acute Ischemic Stroke 2018","volume":"51","author":"Chinese Society of Neurology","year":"2018","journal-title":"Chinese Journal of Neurology"},{"key":"e_1_2_11_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jtumed.2022.12.008"},{"key":"e_1_2_11_8_1","doi-asserted-by":"publisher","DOI":"10.3390\/biology13070519"},{"key":"e_1_2_11_9_1","doi-asserted-by":"publisher","DOI":"10.1186\/s41983-024-00886-w"},{"key":"e_1_2_11_10_1","doi-asserted-by":"publisher","DOI":"10.3390\/ijms23084300"},{"key":"e_1_2_11_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.acra.2024.05.030"},{"key":"e_1_2_11_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.clineuro.2025.108959"},{"key":"e_1_2_11_13_1","doi-asserted-by":"publisher","DOI":"10.31083\/j.rcm2410297"},{"key":"e_1_2_11_14_1","doi-asserted-by":"publisher","DOI":"10.3390\/jcm12196416"},{"key":"e_1_2_11_15_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-022-08757-9"},{"key":"e_1_2_11_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/DSP58604.2023.10167885"},{"key":"e_1_2_11_17_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ypmed.2021.106933"},{"key":"e_1_2_11_18_1","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2018.01302"},{"key":"e_1_2_11_19_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.wneu.2021.11.064"},{"key":"e_1_2_11_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ajpath.2024.05.010"},{"key":"e_1_2_11_21_1","doi-asserted-by":"publisher","DOI":"10.21037\/atm-20-7490"},{"key":"e_1_2_11_22_1","doi-asserted-by":"publisher","DOI":"10.2174\/0115701611304241240523045704"},{"key":"e_1_2_11_23_1","doi-asserted-by":"publisher","DOI":"10.3390\/ijms25137295"},{"key":"e_1_2_11_24_1","doi-asserted-by":"publisher","DOI":"10.3389\/fmedt.2022.748949"},{"key":"e_1_2_11_25_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12967-023-04571-z"},{"key":"e_1_2_11_26_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcmg.2023.09.005"},{"issue":"10","key":"e_1_2_11_27_1","article-title":"Integrative Approaches in Acute Ischemic Stroke: From Symptom Recognition to Future Innovations","volume":"11","author":"Saceleanu V. 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