Background: Approximately one-third of patients with ischemic stroke treated with endovascular treatment do not recover to functional independence despite rapid and successful recanalization. We aimed to quantify the importance of predictors of poor functional outcome despite successful reperfusion. Methods: We analyzed patients from the MR CLEAN Registry between March 2014 and November 2017 with successful reperfusion (extended Thrombolysis In Cerebral Infarction ≥2B). First, predictors were selected based on expert opinion and were clustered according to acquisition over time (ie, baseline patient factors, imaging factors, treatment factors, and postprocedural factors). Second, several models were constructed to predict 90-day functional outcome (modified Rankin Scale (mRS)). The relative importance of individual predictors in the most extensive model was expressed by the proportion of unique added χ2 to the model of that individual predictor. Results: Of 3180 patients, 1913 (60%) had successful reperfusion. Of these 1913 patients, 1046 (55%) were functionally dependent at 90 days (mRS >2). The most important predictors for mRS were baseline patient factors (ie, pre-stroke mRS, added χ2 0.16; National Institutes of Health Stroke Scale score at baseline, added χ2 0.12; age, added χ2 0.10), and postprocedural factors (ie, symptomatic intracranial hemorrhage (sICH), added χ2 0.12; pneumonia, added χ2 0.09). The probability of functional independence for a typical stroke patient with sICH was 54% (95% CI 36% to 72%) lower compared with no sICH, and 21% (95% CI 4% to 38%) for pneumonia compared with no pneumonia. Conclusion: Baseline patient factors and postprocedural adverse events are important predictors of poor functional outcome in successfully reperfused patients with ischemic stroke. This implies that prevention of postprocedural adverse events has the greatest potential to further improve outcomes in these patients.
|Number of pages||6|
|Journal||Journal of NeuroInterventional Surgery|
|Early online date||15 Jul 2021|
|Publication status||Published - 1 Jul 2022|
Bibliographical noteFunding Information:
Competing interests DWJD reports funding from the Dutch Heart Foundation, Brain Foundation Netherlands, The Netherlands Organisation for Health Research and Development, Health Holland Top Sector Life Sciences & Health, and unrestricted grants from Penumbra, Stryker European Operations BV, Medtronic, Thrombolytic Science, and Cerenovus for research, all paid to the institution. AvdL reports funding from the Dutch Heart Foundation, Dutch Brain Foundation, Stryker, Angiocare BV, Medtronic/Covidien/EV3, MEDAC GmbH/LAMEPRO, Penumbra, and Top Medical Concentric, all paid to the institution. CBLMM reports funding from CVON/Dutch Heart Foundation, Stryker, Health Evaluation Netherlands, all paid to the institution, and is a shareholder of Nico.lab, a company that focuses on the use of artificial intelligence for medical imaging analysis. YBWR reports funding from CVON/Dutch Heart Foundation, Stryker, Health Evaluation Netherlands, all paid to the institution, and is a shareholder of Nico.lab, a company that focuses on the use of artificial intelligence for medical imaging analysis.
Funding The authors received no funding for this study. The MR CLEAN Registry is partially funded by unrestricted grants from Toegepast Wetenschappelijk Instituut voor Neuromodulatie, Twente University (TWIN), Erasmus MC University Medical Center, Maastricht University Medical Center, and Amsterdam UMC.
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