Understanding reasons for delay in seeking acute stroke care in an underserved urban population.

BACKGROUND AND PURPOSE: Few patients arrive early enough at hospitals to be eligible for emergent stroke treatment. There may be barriers specific to underserved, urban populations that need to be identified before effective educational interventions to reduce delay times can be developed. METHODS: A survey of respondents' likely action in a hypothetical stroke situation was given to 253 community volunteers in the catchment areas of a large urban community hospital. Concurrently, 100 structured interviews were conducted in the same hospital with patients with acute stroke or a proxy. RESULTS: In this predominantly urban, black population, if faced with a hypothetical stroke, 89% of community volunteers surveyed said they would call 911 first, and few felt any of the suggested potential barriers applied to them. However, only 12% of patients with stroke interviewed actually called 911 first (OR, 63.9; 95% CI, 29.5 to 138.2). Instead, 75% called a relative/friend. Eighty-nine percent of patients with stroke reported significant delay in seeking medical attention, and almost half said the reason for the delay was thinking the symptoms were not serious and/or they would self-resolve. For those arriving by ambulance, only 25% did so because they thought it would be faster, whereas 35% cited having no other transportation options. CONCLUSIONS: In this predominantly black urban population, although 89% of community volunteers report the intent of calling 911 during a stroke, only 12% of actual patients with stroke did so. Further research is needed to determine and conquer the barriers between behavioral intent and actual behavior to call 911 for witnessed stroke.

Optimizing stroke clinical trial design: estimating the proportion of eligible patients.

BACKGROUND AND PURPOSE: Clinical trial planning and site selection require an accurate estimate of the number of eligible patients at each site. In this study, we developed a tool to calculate the proportion of patients who would meet a specific trial's age, baseline severity, and time to treatment inclusion criteria. METHODS: From a sample of 1322 consecutive patients with acute ischemic cerebrovascular syndromes, we developed regression curves relating the proportion of patients within each range of the 3 variables. We used half the patients to develop the model and the other half to validate it by comparing predicted vs actual proportions who met the criteria for 4 current stroke trials. RESULTS: The predicted proportion of patients meeting inclusion criteria ranged from 6% to 28% among the different trials. The proportion of trial-eligible patients predicted from the first half of the data were within 0.4% to 1.4% of the actual proportion of eligible patients. This proportion increased logarithmically with National Institutes of Health Stroke Scale score and time from onset; lowering the baseline limits of the National Institutes of Health Stroke Scale score and extending the treatment window would have the greatest impact on the proportion of patients eligible for a stroke trial. CONCLUSIONS: This model helps estimate the proportion of stroke patients eligible for a study based on different upper and lower limits for age, stroke severity, and time to treatment, and it may be a useful tool in clinical trial planning.