Applying a Random Forest Approach in Predicting Health Status in Patients with Carotid Artery Stenosis 30 Days Post Stenting.

backgroundApproximately 20% of ischemic strokes in the United States result from carotid artery stenosis. Carotid artery stenting (CAS) can reduce stroke risk, but variability in poststenting health outcomes and their predictors is poorly understood. We examined the 30-day post-CAS health status and derived its most important predictors.

methodsThe Stenting and Angioplasty with Protection of Patients with High Risk for Endarterectomy (SAPPHIRE) Worldwide Registry measured preprocedural and 30-day health status for patients undergoing transfemoral CAS using the 36-item Short Form Survey Mental Component Summary and Physical Component Summary, EuroQoL 5-Dimension Index Value, and Visual Analogue Scale. Random Forest models ranked 66 preprocedural candidate variables by relative importance (RI) in predicting 30-day post-CAS health status, stratified by patient symptomatic status. Variables with the highest relative importance were identified and used to develop predictive multivariable linear regression models, which were evaluated using R-square (coefficient of determination) and root mean square error.

resultsHealth status was assessed using the 36-item Short Form Survey in 3017 patients and EuroQoL 5-Dimension in 3930 patients. Random forest models identified 9 key predictors of post-CAS health status: preprocedural health status (RI 100%), Modified Rankin Scale score (RI 26.2%-76.5%), National Institutes of Health Stroke Scale score (RI 12.1%-28.0%), history of stroke (RI 9.2%-19.8%), congestive heart failure (RI 12.3%-19.7%), spinal immobility (RI 6.7%-31.0%), diabetes mellitus (RI 8.1%-32.9%), severe pulmonary disease/chronic obstructive pulmonary disease (RI 13.8%-45.6%), and non-Hispanic/Latino ethnicity (RI 8.4%-32.4%). Multivariable linear regression models explained ∼36%-61% of the health status variance, with 36-item Short Form Survey models (R-square = 36%-61%) outperforming EuroQoL 5-Dimension models (R-square 37%-44%) with regard to R-square and visual fit of observed versus predicted values.

conclusionsWe derived multivariable linear regression-based prediction models that partially explained 30-day post-CAS health status outcomes. Preprocedural health status scores, stroke scale scores, and medical comorbidities may have utility in appropriately risk-stratifying patients under consideration for CAS and should be considered when discussing health status benefits in pre-CAS treatment shared decision-making discussions. Clinical Trial Registration Information: This study analyzed data from the SAPPHIRE Worldwide: Stenting and Angioplasty with Protection of Patients with High Risk for Endarterectomy trial. ClinicalTrialsgov ID: NCT00403078.URL: https://clinicaltrials.gov/study/NCT00403078.