Delayed Hospital Arrival for Acute Stroke: The Minnesota Stroke Survey

Recent advances have been made in the treatment of acute stroke, but the effectiveness of the new therapies is highly time-dependent [1]. For example, the American Heart Association guidelines recommend the use of thrombolytic therapy with tissue plasminogen activator for a subset of patients with acute ischemic stroke, but this agent must be administered within 3 hours after the onset of stroke to be effective [2-5]. The effectiveness of tissue plasminogen activator diminishes with time; the longer the delay, the smaller the probability of improving blood flow to the affected area of the brain and the greater the risk for hemorrhagic complications [3]. Patients with acute stroke often arrive at the hospital too late to receive the maximum benefit from these new stroke therapies. Efforts to reduce delay time of therapy for acute stroke may be more effective if the factors that delay hospital arrival are identified and targeted for specific intervention; however, only a few studies have extensively examined this issue in the United States [6-10]. In contrast, factors influencing hospital arrival time for acute myocardial infarction have been studied in detail [11-21]. Several factors that delay hospital arrival after acute stroke parallel those for acute myocardial infarction, including living alone [8, 12], being at home during symptom onset [7, 11, 12], and first contacting a physician rather than an emergency service [7-9, 12-17]. By using medical record review, we investigated factors that influence the time from stroke onset to patient arrival at metropolitan Minneapolis-St. Paul hospitals. Methods Sample Selection The Minnesota Stroke Survey is a population-based surveillance study of acute cerebrovascular disease [22]. The target population comprises residents 30 to 79 years of age living in the seven-county metropolitan area of Minneapolis-St. Paul, Minnesota. We report on factors that influenced hospital arrival time during the early 1990s by using combined data from surveys from three calendar years (1991, 1992, and 1993). Discharge diagnosis lists based on the International Classification of Diseases, 9th Revision (ICD-9), stroke codes were obtained from 23 of 25 acute care hospitals in the Minneapolis-St. Paul area for each surveillance year. The two hospitals that did not provide data have low patient volume (an estimated two to four valid patients with stroke per hospital per year). The sampling frame included all Minneapolis-St. Paul residents 30 to 79 years of age who were discharged with an acute cerebrovascular disease code (ICD-9 codes 430, 431, 432, 434, 436, and 437). For each surveillance year, a 50% random sample was selected from the listings for detailed record abstraction. No data were available for patients who were not hospitalized. Previous studies have estimated that 81% of all patients with a first stroke event were hospitalized, and patients with fatal strokes were less likely to be hospitalized than those with nonfatal strokes (76% and 89%, respectively) [23]. Data Collection Trained nurses used standardized data collection forms to abstract clinical data from the medical record, including date and time of symptom onset, data and time of admission to the hospital, demographic characteristics, medical history, symptoms at stroke onset, physician examination findings, stroke severity, and stroke type. Neuroimaging and autopsy reports were photocopied and abstracted by study physicians who did not have knowledge of the patient's other medical record data. The study was approved by the institutional review board of the University of Minnesota. Stroke Validation and Classification Because factors influencing delay time were assumed to be unrelated to stroke type, we included all stroke types in the sample. Events were included when the patient had a new neurologic deficit that lasted at least 24 hours or until death. Patients with brain tumors, subdural hematomas, and subarachnoid hemorrhages were excluded. Autopsy results were available for only 9% of patients who died while they were hospitalized. Accordingly, autopsy results were used to confirm the diagnosis of stroke for less than 1% of patients (n = 16). Stroke events were classified as hemorrhagic or ischemic on the basis of neuroimaging results and autopsy reports or as undetermined when neither data source was available. Ischemic stroke was divided into possibly embolic and nonembolic subtypes. A stroke was considered possibly embolic if ICD-9 code 434.1 (cerebral embolism) was listed among the discharge diagnoses, if the medical record indicated that the stroke was definitely or probably embolic (including embolism from the carotid arteries), or if one or more of the following conditions was documented in the medical record: atrial fibrillation, mitral stenosis, intracardiac thrombus, systemic embolus, recent myocardial infarction, or cerebral or cardiac angiography that closely preceded the stroke. Patients were excluded if symptoms developed while the patient was hospitalized for another condition (n = 294) or if the patient had been transferred from another hospital (n = 41). During the initial stages of the medical record abstraction, we did not collect information on whether the patient was admitted to the hospital through the emergency department; these patients were also excluded (n = 216). At the time of analysis, data collection was 77% complete. The final available sample size was 1895 hospitalizations for acute stroke. Variables The main variable of interest, delay time, was defined as the time from the onset of new neurologic symptoms to the time of hospital arrival. Time of hospital arrival was defined as the time the patient presented to the emergency department or the hospital (if the patient was not admitted through the emergency department). The time of symptom onset was recorded in the medical record of 70% of the patients (n = 1334). The delay time was calculated by subtracting the recorded time of symptom onset from the hospital arrival time when both times were available. For the remaining patients (n = 561), the time of symptom onset was not recorded in the medical record; therefore, we approximated the delay time on the basis of all available information (<24 hours, 24 hours to <48 hours, 48 hours to <72 hours, and 72 hours to <6 weeks). Demographic characteristics included age, sex, and ethnicity. Ethnicity was categorized as white, African American, Asian/Pacific Islander, and other. We also identified whether the patient was enrolled in a health maintenance organization, whether the patient lived alone or in a nursing home before the stroke, whether do-not-resuscitate or do-not-intubate orders existed before hospital admission, and whether the patient was admitted to the hospital through the emergency department. A history of the following conditions was recorded: transient ischemic attack, stroke, myocardial infarction, diabetes, hypertension, hypercholesterolemia, whether the patient ever smoked, and daily use of aspirin or warfarin. The level of comorbidity was estimated by using a modified Charlson comorbidity index, excluding two conditions specific to acute stroke (cerebrovascular disease and hemiplegia) [24]. The patient's prestroke functional status was measured by determining whether the patient was dependent in at least one activity of daily living (bathing, continence, feeding, going to the toilet, and transfer into or out of a bed or chair) before the onset of the stroke [25]. The presence of the following symptoms at stroke onset was recorded: limb or facial weakness, impaired speech, impaired vision, dizziness, unsteadiness, tingling, seizures, syncope, headache, and vomiting. The time of symptom onset was classified by the quarter of the day that the stroke occurred (morning = 6 a.m. to noon, afternoon = noon to 6 p.m., evening = 6 p.m. to midnight, night = midnight to 6 a.m.). The date of symptom onset was used to characterize whether the stroke occurred on a weekend (Saturday or Sunday). Several variables were used to indicate the severity of the stroke at presentation. The level of consciousness was assigned one of three categories (unconscious, conscious but abnormal, or normal). The level of disability was estimated by using the Rankin score (from 1 = no disability to 5 = severe disability) [26]. The following findings on physician examination were also noted: weakness or paralysis of the limbs and face, visual defects, ataxia, sensory loss, aphasia, dysarthria, impaired swallowing, abnormal findings on pupil examination, and abnormal plantar (Babinski) reflex. Statistical Analysis Parametric survival regression analysis based on an accelerated failure time model was used to examine the influence of the explanatory variables on delay time. Patients with a calculated delay time were treated as uncensored data. Patients with an approximated delay time that indicated arrival within 24 hours of symptom onset were treated as left-censored at 24 hours. Patients with an approximated delay time that indicated arrival within 24 to 48 hours, 48 to 72 hours, and 72 hours to 6 weeks were treated as interval-censored data. The generalized model and three models nested within the generalized model (exponential, Weibull, and log-normal models) were compared by using the likelihood ratio statistic. The two best-fitting models were the generalized model and the log-normal model. The conclusions did not differ between the two models, and the results from the log-normal model are presented. The coefficients estimated from this model were converted to the percentage difference in delay time associated with a one-unit increment in the explanatory variable X [% Delta Delay/Delta X = (e- 1) 100]. For continuous variables, this value indicates the percentage difference in delay time associated with a one-unit increment in the explanatory variable. For indicator variables, this value indicates the perc