{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T03:31:47Z","timestamp":1780371107265,"version":"3.54.1"},"reference-count":41,"publisher":"SAGE Publications","issue":"1","license":[{"start":{"date-parts":[[2025,3,3]],"date-time":"2025-03-03T00:00:00Z","timestamp":1740960000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"name":"The Key Emergency Medical Disciplines and Specialties Program of Guangzhou"},{"name":"The Multi-center Clinical Research Fund Project of the Second Affiliated Hospital of Guangzhou Medical University","award":["2021-LCYJ-DZX-02"],"award-info":[{"award-number":["2021-LCYJ-DZX-02"]}]},{"name":"The Health Promotion Project of Guangdong Province.","award":["202206261103468054"],"award-info":[{"award-number":["202206261103468054"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Clin EEG Neurosci"],"published-print":{"date-parts":[[2026,1]]},"abstract":"<jats:p>\n                    <jats:italic toggle=\"yes\">Background:<\/jats:italic>\n                    As a leading cause of severe morbidity, acute ischemic stroke (AIS) necessitates precise prognostic evaluation to inform critical treatment strategies. Recent advancements have identified quantitative electroencephalography (qEEG) as a pivotal instrument in refining prognostic accuracy for AIS. This investigation aimed to construct a robust prognostic model, anchored in qEEG parameters, to enhance the precision of clinical prognosis 6 months after discharge in AIS patients.\n                    <jats:italic toggle=\"yes\">Methods:<\/jats:italic>\n                    In a retrospective observational study, we analyzed AIS cases from January 2022 to March 2023. Data encompassing demographic profiles, clinical manifestations, qEEG findings, and modified Rankin Scale (mRS) assessments were evaluated for 109 patients with AIS. These metrics were instrumental in developing prognostic models, segregating outcomes into either favorable (mRS: 0\u20132) or unfavorable categories (mRS: 3\u20136) at 6 months post-discharge. Prognostic models were developed using clinical and qEEG parameters.\n                    <jats:italic toggle=\"yes\">Results:<\/jats:italic>\n                    The formulation of two distinct prognostic models was predicated on an integration of baseline clinical data (age, unilateral limb weakness, ataxia and red blood cell count) and specific qEEG metrics (T3-P3 (TAR) and T4-P4 (TAR)). The synthesis of these models culminated in the Prognostic Model 3, which exhibited a marked enhancement in prognostic accuracy, as evidenced by an area under the curve (AUC) of 0.8227 (95% CI: 0.7409\u20130.9045), thereby signifying a superior prediction of AIS prognosis 6 months after discharge relative to the individual models.\n                    <jats:italic toggle=\"yes\">Conclusion:<\/jats:italic>\n                    Quantitative EEG, especially increased theta\/alpha power ratio (TAR), might improve the prediction of prognosis 6 months after discharge of acute ischemic stroke in clinical practice.\n                  <\/jats:p>","DOI":"10.1177\/15500594251323119","type":"journal-article","created":{"date-parts":[[2025,3,4]],"date-time":"2025-03-04T14:10:26Z","timestamp":1741097426000},"page":"58-67","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":2,"title":["Quantitative Electroencephalogram Might Improve the Predictive Value of Prognosis 6 Months After Discharge in Acute Ischemic Stroke"],"prefix":"10.1177","volume":"57","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4799-3073","authenticated-orcid":false,"given":"Haifeng","family":"Mao","sequence":"first","affiliation":[{"name":"Guangzhou Medical University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-8651-6136","authenticated-orcid":false,"given":"Liwei","family":"Liu","sequence":"additional","affiliation":[{"name":"Guangzhou Medical University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peiyi","family":"Lin","sequence":"additional","affiliation":[{"name":"Guangzhou Medical University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-0558-0656","authenticated-orcid":false,"given":"Xinran","family":"Meng","sequence":"additional","affiliation":[{"name":"Guangzhou Medical University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Timothy H.","family":"Rainer","sequence":"additional","affiliation":[{"name":"The University of Hong Kong"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-7516-3452","authenticated-orcid":false,"given":"Qianyi","family":"Wu","sequence":"additional","affiliation":[{"name":"Guangzhou Medical 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