Abstract TMP41: Accuracy of Self-Reported Stroke Subtype and Functional Status Information Submitted by Patients Recruited Online: The Stroke Recovery Initiative

Abstract

Introduction: An online process for eliciting and assessing information from stroke patients to prescreen for stroke recovery studies holds potential to accelerate enrollment, but the validity of using self-reported information for online pre-screening is uncertain. Methods: Among patients in the UCSF Stroke Recovery Initiative, a nationwide, online participant recruitment registry of stroke patients that have expressed an interest in stroke recovery studies (strokerecoveryinitiative.ucsf.edu; NCT03318432), we compared self-reported information on stroke subtype (ischemic vs. hemorrhagic), location (MCA, cerebellar, brainstem), and functional status (modified Rankin Scale) elicited online to final validated responses as determined by follow-up semi-structured telephone interviews. We used descriptive statistics and Cohen’s kappa to evaluate the concordance of self-reported information against validated responses. Results: A total of 1,283 of the 3,959 participants in the recruitment registry were selected for semi-structured telephone follow-up (mean age 56; 55% male; average of 2.6 years after the index stroke). There was moderate agreement between self-report and telephone-validated responses for stroke subtype (84.4% agreement, kappa=0.68 for ischemic stroke; 83.0% agreement, 0.70 for hemorrhagic stroke) and similar performance for stroke location (86.1% agreement, kappa=0.75 for MCA location; 81.1% agreement, 0.66 for cerebellar location; 86.9% agreement, 0.78 for brainstem location). Agreement for the modified Rankin Scale for functional status was somewhat lower overall (66.7% agreement, kappa=0.53) but self-reported scores were within 1 point of the validated score 94% of the time. Conclusion: Using self-reported information to prescreen patients for stroke recovery studies requires a permissive approach to basic eligibility criteria to flag potentially-eligible candidates for additional follow-up. The efficiency and high-throughput of an online prescreening process would benefit from having studies with eligibility criteria that are developed with an efficient prescreening process in mind as well as high-throughput pre-screening instruments that are optimized for self-report.