A tool to improve stroke outcome prediction: The charlotte large artery occlusion endovascular therapy outcome score

We sought to optimize functional outcome prediction for large artery occlusion (LAO) patients treated with endovascular thrombectomy (EVT).

Patients presenting with an anterior circulation LAO treated with EVT from November 2016-July 2020 were included from a health system's code stroke registry. Data were separated into training and validation cohorts using a simple random sampling method. Logistic regression analysis was used to identify pre-intervention prognostic factors independently associated with 90-day modified Rankin score 4-6 in the training cohort. The model was tested in the validation cohort and compared to previously reported scales using Area Under Curve (AUC) analyses.

646 total patients were included. The Charlotte Large artery occlusion Endovascular therapy Outcome Score, CLEOS = (5 x Age) + (10 x NIHSS) + Glucose - (150 x Cerebral Blood Volume Index). CLEOS was associated with an increased odds of poor 90-day outcome (per 1-point increase, OR 1.008, 95% CI 1.006-1.010, p < 0.0001) and performed better than Stroke Prognostication using Age and National Institute of Health Stroke Scale - 100 (AUC 0.62, p < 0.0001) and Houston Intra-Arterial Therapy 2 (AUC 0.70, p < 0.0063), with a trend observed versus Pittsburgh Response to Endovascular therapy (AUC 0.72, p = 0.0884), in the combined analysis of the derivation and validation cohorts. CLEOS ≥ 700 was not associated with a lower risk of poor outcome despite excellent endovascular reperfusion.

CLEOS can predict poor 90-day outcomes after thrombectomy and help risk stratify patients based on the degree of revascularization after EVT.