@article{2302c81534064ad2838431daab2c8e50,
title = "Machine Learning–Based Identification of Target Groups for Thrombectomy in Acute Stroke",
abstract = "Whether endovascular thrombectomy (EVT) improves functional outcome in patients with large-vessel occlusion (LVO) stroke that do not comply with inclusion criteria of randomized controlled trials (RCTs) but that are considered for EVT in clinical practice is uncertain. We aimed to systematically identify patients with LVO stroke underrepresented in RCTs who might benefit from EVT. Following the premises that (i) patients without reperfusion after EVT represent a non-treated control group and (ii) the level of reperfusion affects outcome in patients with benefit from EVT but not in patients without treatment benefit, we systematically assessed the importance of reperfusion level on functional outcome prediction using machine learning in patients with LVO stroke treated with EVT in clinical practice (N = 5235, German-Stroke-Registry) and in patients treated with EVT or best medical management from RCTs (N = 1488, Virtual-International-Stroke-Trials-Archive). The importance of reperfusion level on outcome prediction in an RCT-like real-world cohort equaled the importance of EVT treatment allocation for outcome prediction in RCT data and was higher compared to an unselected real-world population. The importance of reperfusion level was magnified in patient groups underrepresented in RCTs, including patients with lower NIHSS scores (0–10), M2 occlusions, and lower ASPECTS (0–5 and 6–8). Reperfusion level was equally important in patients with vertebrobasilar as with anterior LVO stroke. The importance of reperfusion level for outcome prediction identifies patient target groups who likely benefit from EVT, including vertebrobasilar stroke patients and among patients underrepresented in RCT patients with low NIHSS scores, low ASPECTS, and M2 occlusions.",
keywords = "Endovascular thrombectomy, Machine learning, Outcome prediction, Real-world data, Stroke",
author = "Fanny Quandt and Fabian Flottmann and Madai, {Vince I.} and Anna Alegiani and Clemens K{\"u}pper and Lars Kellert and Adam Hilbert and Dietmar Frey and Thomas Liebig and Jens Fiehler and Mayank Goyal and Saver, {Jeffrey L.} and Christian Gerloff and Thomalla, {G. tz} and Steffen Tiedt and {the GSR investigators and the VISTA-Endovascular Collaborators} and J. Berrouschot and A. Bormann and G. Bohner and Nolte, {C. H.} and E. Siebert and S. Zweynert and F. Dorn and Petzold, {G. C.} and F. Keil and W. Pfeilschifter and Hamann, {G. F.} and M. Braun and B. Eckert and J. R{\"o}ther and A. Alegiani and J. Fiehler and C. Gerloff and G. Thomalla and C. Kraemer and K. Gr{\"o}schel and T. Uphaus and L. Kellert and S. Tiedt and C. Trumm and T. Boeckh-Behrens and S. Wunderlich and A. Ludolph and M. Petersen and F. St{\"o}gbauer and U. Ernemann and S. Poli and P. Khatri and M. Bendszuz and S. Bracard and Majoie, {C. B.}",
note = "Funding Information: FF reports personal fees from Eppdata. LK has received funding for travel or speaker honoraria from Bayer Vital, Boehringer Ingelheim, Bristol-Meyer-Squibb, Daiichi Sankyo, and Pfizer outside of this study. AH reports a grant from the European Commission Horizon2020 program (PRECISE4Q Grant No. 777 107, coordinator: Dietmar Frey) during the conduct of the study. DF reports grants from the European Commission: Horizon2020 program (PRECISE4Q Grant No. 777 107, coordinator: DF) and grants from the Federal Ministry of Research and Education (GO-Bio Grant No. 031B0154, lead: DF) during the conduct of the study. JF reports grants and personal fees from Anandis, Cerenovus, Microvention, Medtronic, Stryker, and personal fees from Phenox and Penumbra, all outside the submitted work. JF also serves as the CEO of Eppdata. MG reports personal fees from Medtronic, Stryker, Microvention, and Mentice, all outside the submitted work. In addition, MG has a patent on “Systems of acute stroke diagnosis” licensed to GE Healthcare, and a patent on “Systems of intracranial access” licensed to Microvention. CG reports personal fees from Amgen, Boehringer Ingelheim, Daiichi Sankyo, Abbott, Prediction Biosciences, Novartis, and Bayer, all outside the submitted work. GT reports grants and personal fees from Bayer, and personal fees from Acandis, BristolMyersSquibb/Pfizer, Boehringer Ingelheim, Daiichi Sankyo, Portola, and Stryker, all outside the submitted work. ST received funding from the Corona foundation outside of the submitted work. All the other authors declare no competing interests. Funding Information: Open Access funding enabled and organized by Projekt DEAL. S. T. was supported by a grant from the Corona foundation. Publisher Copyright: {\textcopyright} 2022, The Author(s).",
year = "2022",
doi = "https://doi.org/10.1007/s12975-022-01040-5",
language = "English",
journal = "Translational Stroke Research",
issn = "1868-4483",
publisher = "Springer US",
}