MACHINE LEARNING-BASED ASSESSMENT OF THE BENEFIT OF THROMBECTOMY FOR ACUTE ISCHEMIC STROKE IN REAL-WORLD AND RCT DATA IDENTIFIES POTENTIAL TREATMENT TARGET GROUPS

Session Type
Scientific Communication
Date
Wed, 01.09.2021
Session Time
08:30 - 10:00
Room
Hall G
Lecture Time
09:07 - 09:15
Presenter
  • Fanny Quandt (Germany)

Abstract

Group Name

on behalf of the GSR investigators and the VISTA-Endovascular Collaborators

Background And Aims

Whether endovascular thrombectomy (EVT) improves functional outcome in patients that do not comply with inclusion criteria of randomized controlled trials (RCT) from large-vessel occlusion (LVO) stroke but that are considered for EVT in clinical practice, is uncertain. We aimed to identify patients with LVO stroke underrepresented in RCTs who might also benefit from EVT.

Methods

We used level of reperfusion as a graded treatment marker and its value for prediction of functional independence in a machine learning model to assess treatment benefit in real-world (N=5,235, German-Stroke-Registry) and RCT data (N=1,488, Virtual-International-Stroke-Trials-Archive). We further analyzed the influence of patient characteristics on clinical outcome.

Results

In real-world data, leading predictors of functional independence were NIHSS upon admission, age, and pre-stroke mRS; while in RCT data, leading predictors were NIHSS and onset-to-puncture time. The importance of reperfusion level for outcome prediction in an RCT-like real-world cohort was similar compared to EVT treatment allocation for outcome prediction in RCT data and was considerably 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, longer onset-to-puncture times, and lower ASPECTS (0-5 and 6-8). Reperfusion level was equally important in patients with vertebrobasilar as with anterior LVO stroke.

Conclusions

The importance of reperfusion level for outcome prediction identifies patients who likely benefit from EVT, including vertebrobasilar stroke patients and among patients underrepresented in RCTs patients with low NIHSS scores, low ASPECTS, and M2 occlusions.

Trial Registration Number

Not applicable

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