Prediction of Functional Outcome After Acute Ischemic Stroke: Comparison of the CT-DRAGON Score and a Reduced Features Set

Anouk Lesenne, Jef Grieten, Ludovic Ernon, Alain Wibail, Luc Stockx, Patrick F Wouters, Leentje Dreesen, Elly Vandermeulen, Sam Van Boxstael, Pascal Vanelderen, Sven Van Poucke, Joris Vundelinckx, Sofie Van Cauter, Dieter Mesotten, Anouk Lesenne, Jef Grieten, Ludovic Ernon, Alain Wibail, Luc Stockx, Patrick F Wouters, Leentje Dreesen, Elly Vandermeulen, Sam Van Boxstael, Pascal Vanelderen, Sven Van Poucke, Joris Vundelinckx, Sofie Van Cauter, Dieter Mesotten

Abstract

Background and Purpose: The CT-DRAGON score was developed to predict long-term functional outcome after acute stroke in the anterior circulation treated by thrombolysis. Its implementation in clinical practice may be hampered by its plethora of variables. The current study was designed to develop and evaluate an alternative score, as a reduced set of features, derived from the original CT-DRAGON score. Methods: This single-center retrospective study included 564 patients treated for stroke, in the anterior and the posterior circulation. At 90 days, favorable [modified Rankin Scale score (mRS) of 0-2] and miserable outcome (mRS of 5-6) were predicted by the CT-DRAGON in 427 patients. Bootstrap forests selected the most relevant parameters of the CT-DRAGON, in order to develop a reduced set of features. Discrimination, calibration and misclassification of both models were tested. Results: The area under the receiver operating characteristic curve (AUROC) for the CT-DRAGON was 0.78 (95% CI 0.74-0.81) for favorable and 0.78 (95% CI 0.72-0.83) for miserable outcome. Misclassification was 29% for favorable and 13.5% for miserable outcome, with a 100% specificity for the latter. National Institutes of Health Stroke Scale (NIHSS), pre-stroke mRS and age were identified as the strongest contributors to favorable and miserable outcome and named the reduced features set. While CT-DRAGON was only available in 323 patients (57%), the reduced features set could be calculated in 515 patients (91%) (p < 0.001). Misclassification was 25.8% for favorable and 14.4% for miserable outcome, with a 97% specificity for miserable outcome. The reduced features set had better discriminative power than CT-DRAGON for both outcomes (both p < 0.005), with an AUROC of 0.82 (95% CI 0.79-0.86) and 0.83 (95% CI 0.77-0.87) for favorable and miserable outcome, respectively. Conclusions: The CT-DRAGON score revealed acceptable discrimination in our cohort of both anterior and posterior circulation strokes, receiving all treatment modalities. The reduced features set could be measured in a larger cohort and with better discrimination. However, the reduced features set needs further validation in a prospective, multicentre study. Clinical Trial Registration: http://www.clinicaltrials.gov. Identifiers: NCT03355690, NCT04092543.

Keywords: cerebrovascular disorders; ischemic stroke; machine learning; mortality/survival; prognosis; quality and outcomes; revascularization; stroke; thrombectomy; thrombolytic therapy; transient ischemic attack (TIA); treatment.

Copyright © 2020 Lesenne, Grieten, Ernon, Wibail, Stockx, Wouters, Dreesen, Vandermeulen, Van Boxstael, Vanelderen, Van Poucke, Vundelinckx, Van Cauter and Mesotten.

Figures

Figure 1
Figure 1
Flowchart of patients.

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