التفاصيل البيبلوغرافية
| العنوان: |
Clinical prediction of thrombectomy eligibility: A systematic review and 4-item decision tree |
| المؤلفون: |
Koster, Gaia T., Nguyen, T. Truc My, van Zwet, Erik W., Garcia, Bjarty L., Rowling, Hannah R., Bosch, J., Schonewille, Wouter J., Velthuis, Birgitta K., van den Wijngaard, Ido R., den Hertog, Heleen M., Roos, Yvo B.W.E.M., van Walderveen, Marianne A.A., Wermer, Marieke J.H., Kruyt, Nyika D. |
| المساهمون: |
Researchgr. Systems Radiology, UMC Utrecht, Researchgr. Hart-brein as., Brain, Circulatory Health |
| سنة النشر: |
2019 |
| مصطلحات موضوعية: |
Acute ischemic stroke, clinical scale, endovascular thrombectomy, intra-arterial thrombectomy, large vessel occlusion, prehospital, Severity of Illness Index, Predictive Value of Tests, Prospective Studies, Humans, Middle Aged, Male, Patient Selection, Algorithms, Female, Aged, Decision Trees, Thrombectomy/standards, Databases, Factual, Neurology, Research Support, Non-U.S. Gov't, Multicenter Study, Journal Article, Validation Studies |
| الوصف: |
BACKGROUND: 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. AIM: To subtract, validate and compare existing LAVO-prediction scales, and develop a straightforward decision support tool to assess IAT-eligibility. METHODS: 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. RESULTS: 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 >0.81, p < 0.01 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. CONCLUSION: 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. |
| نوع الوثيقة: |
article in journal/newspaper |
| وصف الملف: |
image/pdf |
| اللغة: |
English |
| تدمد: |
1747-4930 |
| العلاقة: |
https://dspace.library.uu.nl/handle/1874/390526Test |
| الإتاحة: |
https://dspace.library.uu.nl/handle/1874/390526Test |
| حقوق: |
info:eu-repo/semantics/OpenAccess |
| رقم الانضمام: |
edsbas.F4C23BF7 |
| قاعدة البيانات: |
BASE |
