The best diagnostic approach for classifying ischemic stroke onset time: A systematic review and meta-analysis.
Background: The success of intravenous thrombolysis with tPA (IV-tPA) as the fastest and easiest treatment for stroke patients is closely related to time since stroke onset (TSS). Administering IV-tPA after the recommended time interval (< 4.5 h) increases the risk of cerebral hemorrhage. Despite ad...
| Publicado en: | Neuroradiology Vol. 67; no. 9; pp. 2267 - 2282 |
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| Autores principales: | , , , |
| Formato: | research systematic review tables/charts Journal Article |
| Publicado: |
Springer Nature
Sep2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=188799174&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 188799174 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00283940 NYZ jtl: Neuroradiology issn: 00283940 maglogo: N pubinfo: dt: Sep2025 vid: 67 iid: 9 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 188799174 187885972 188799174 188799174 10.1007/s00234-025-03745-4 188799174 ppf: 2267 ppct: 15 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: The best diagnostic approach for classifying ischemic stroke onset time: A systematic review and meta-analysis. aug: au: Zakariaee, Seyed Salman Kadir, Dler Hussein Molazadeh, Mikaeil Abdi, Shahab affil: https://ror.org/042hptv04 Ilam University of Medical Sciences, Ilam, Islamic Republic of Iran sug: subj: Ischemic Stroke Classification Ischemic Stroke Diagnosis Age of Onset Evaluation Time Evaluation Sensitivity and Specificity Evaluation Artificial Intelligence Neuroradiography Machine Learning Prediction Models Magnetic Resonance Imaging Human Systematic Review Meta Analysis PubMed Embase Cochrane Library Stroke Patients Stroke Units Radiomics Tomography, X-Ray Computed Thrombolytic Therapy Ischemic Stroke Drug Therapy Fibrinolytic Agents Therapeutic Use Confidence Intervals Checklists Descriptive Statistics Data Analysis Software Chi Square Test Computer Simulation Male Female Regression Male Female ab: Background: The success of intravenous thrombolysis with tPA (IV-tPA) as the fastest and easiest treatment for stroke patients is closely related to time since stroke onset (TSS). Administering IV-tPA after the recommended time interval (< 4.5 h) increases the risk of cerebral hemorrhage. Despite advances in diagnostic approaches have been made, the determination of TSS remains a clinical challenge. In this study, the performances of different diagnostic approaches were investigated to classify TSS. Materials and methods: A systematic literature search was conducted in Web of Science, Pubmed, Scopus, Embase, and Cochrane databases until July 2025. The overall AUC, sensitivity, and specificity magnitudes with their 95%CIs were determined for each diagnostic approach to evaluate their classification performances. Results: This systematic review retrieved a total number of 9030 stroke patients until July 2025. The results showed that the human readings of DWI-FLAIR mismatch as the current gold standard method with AUC = 0.71 (95%CI: 0.66–0.76), sensitivity = 0.62 (95%CI: 0.54–0.71), and specificity = 0.78 (95%CI: 0.72–0.84) has a moderate performance to identify the TSS. ML model fed by radiomic features of CT data with AUC = 0.89 (95%CI: 0.80–0.98), sensitivity = 0.85 (95%CI: 0.75–0.96), and specificity = 0.86 (95%CI: 0.73-1.00) has the best performance in classifying TSS among the models reviewed. Conclusion: ML models fed by radiomic features better classify TSS than the human reading of DWI-FLAIR mismatch. An efficient AI model fed by CT radiomic data could yield the best classification performance to determine patients' eligibility for IV-tPA treatment and improve treatment outcomes. pubtype: Academic Journal doctype: meta analysis research systematic review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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