Bypassing the intensive care unit for patients with acute ischemic stroke secondary to large-vessel occlusion

Endovascular mechanical thrombectomy is safe and effective for the treatment of acute ischemic stroke (AIS) due to large-vessel occlusion (LVO). Still, despite high rates of procedural success, it is routine practice to uniformly admit postthrombectomy patients to an intensive care unit (ICU) for postoperative observation. Predictors of ICU criteria and care requirements in the postmechanical thrombectomy ischemic stroke patient population are lacking. The goal of the present study is to identify risk factors associated with requiring ICU-level intervention following mechanical thrombectomy.

The authors retrospectively analyzed data from 245 patients undergoing thrombectomy for AIS from anterior circulation LVO at a comprehensive stroke and tertiary care center from January 2015 to March 2020. Clinical variables that predicted the need for critical care intervention were identified and compared. The performance of a binary classification test constructed from these predictive variables was also evaluated using a validation cohort.

Seventy-six patients (31%) required critical care interventions. A recanalization grade lower than modified Thrombolysis in Cerebral Infarction (mTICI) scale grade 2B (odds ratio [OR] 3.625, p = 0.001), Alberta Stroke Program Early Computed Tomography Score (ASPECTS) < 8 (OR 3.643, p < 0.001), and presence of hyperdensity on postprocedure cone-beam CT (OR 2.485, p = 0.005) were significantly associated with the need for postthrombectomy critical care intervention. When applied to a validation cohort, a clearance classification scheme using these three variables demonstrated high positive predictive value (0.88).

A recanalization grade lower than mTICI 2B, ASPECTS < 8, and postprocedure hyperdensity on cone-beam CT were shown to be independent predictors of requiring ICU-level care. Routine admission to ICU-level care can be costly and confer increased risk for hospital-acquired conditions. Safely and reliably identifying low-risk patients has the potential for cost savings, value-based care, and decreasing hospital-acquired conditions.