Transient ischemic attack (TIA) is associated with a substantial short-term risk of recurrent stroke.Reference Giles and Rothwell 1 Although observational studies suggest that prompt assessment and risk factor modification can reduce the risk of subsequent stroke,Reference Rothwell, Giles and Chandratheva 2 , Reference Lavallée, Meseguer and Abboud 3 there is ongoing debate about the relative merits and disadvantages of hospitalization versus outpatient care in such patients.Reference Amarenco 4 - Reference Lindley 7
Prediction scores have been developed to estimate the risk of recurrent stroke; these generally incorporate clinical factors (age, comorbid conditions) and presenting symptoms (weakness, speech disturbance, duration of symptoms), with some scores also including the results of initial brain or vascular imaging.Reference Rothwell, Giles and Flossmann 8 - Reference Coutts, Modi, Patel and Demchuk 12 Although many clinical practice guidelines recommend hospitalization for patients with risk scores above a certain cutoff (typically an age, blood pressure, clinical features, duration of symptoms [ABCD]2 score >2 or 3), such risk scores may perform less well than the initial validation studies suggested,Reference Perry, Sharma and Sivilotti 13 , Reference Hill and Coutts 14 contributing to further uncertainty about when to hospitalize patients with minor stroke or TIA.
We used data from a clinical stroke registry in Ontario, Canada, linked with administrative databases, to determine the association between patient and system-level factors with the proportion of patients with TIA or minor stroke admitted to hospital. We hypothesized that both patient-level factors (such as presenting symptoms and comorbid conditions) and system-level factors (such as availability of a stroke prevention clinic) would be associated with hospitalization.
Methods
Data Sources and Study Sample
The Ontario Stroke Registry (formerly known as the Registry of the Canadian Stroke Network) performs a biennial audit on a population-based random sample of patients seen at all acute care institutions in Ontario.Reference Kapral, Silver and Richards 15 Events are reviewed by trained neurology research personnel and only included in the registry database if chart review confirms a diagnosis of stroke or TIA. The registry database includes information on stroke type and severity, presenting symptoms and comorbid conditions, and validation by duplicate chart abstraction has shown almost perfect agreement (kappa scores of >0.80) for key variables including age, sex, stroke type, admission to hospital, and the diagnoses of diabetes and hypertensionReference Kapral, Silver and Richards 15 and substantial agreement (kappa scores of 0.61-0.80) for presenting symptoms (unpublished data). For the present study, we included all patients with TIA (defined as transient focal neurological symptoms of less than 24 hours’ duration, with no evidence of infarction on neuroimaging) or minor ischemic stroke (defined as a Canadian Neurological Scale score of greater than 10, corresponding to a National Institutes of Health Stroke Scale score of <3) who were aged 18 years or older and who were seen in the emergency department (ED) or admitted to hospital between April 1, 2008, and March 31, 2009, or April 1, 2010, and March 31, 2011. For patients with more than one ED presentation during the study period, only the first event was included.
The Ontario Stroke Registry is housed at the Institute for Clinical Evaluative Sciences (ICES) where it is linked to population-based administrative databases using unique encoded patient identifiers. We used the National Ambulatory Care Reporting System database to identify times of ED overcrowding, defined as a mean length of stay in the ED of greater than 4 hours for patients of similar acuity seen in the ED on the same shift as the index patient,Reference Asplin 16 the 2010 Canada Census to provide information on socioeconomic status based on median neighbourhood income for each patient and the 2010 Stroke Secondary Prevention Clinic Resource Survey to provide information on the characteristics of stroke prevention clinics.
Analysis
We determined the proportion of patients admitted to hospital in the overall cohort, in the subgroups with TIA alone and minor ischemic stroke alone, and by region, based on Ontario’s 14 Local Health Integration Network regions. We compared baseline characteristics between admitted and discharged patients using chi-square tests for categorical variables and the Wilcoxon rank-sum test for continuous variables.
We used multiple logistic regression to evaluate the effect of the following predictor variables on the odds of hospital admission: (1) patient characteristics (age, sex, place of residence before admission, rural residence, neighbourhood income group, prestroke functional status, and comorbid conditions [defined by having documentation of any of these in the patient chart] including diabetes mellitus, hypertension, smoking, atrial fibrillation, and coronary artery disease); (2) characteristics of the index event (motor or speech deficits, duration of symptoms, systolic blood pressure >140 mm Hg on presentation, diastolic blood pressure >90 mm Hg on presentation, ABCD2 score7); (3) characteristics of the care encounter (ED overcrowding, presentation off-hours); and (4) hospital characteristics (hospital size, designation as a stroke centre, availability of a stroke unit, presence of a stroke prevention clinic on-site, and number of days of operation of the stroke prevention clinic) and health region of care. We used a hierarchical logistic regression that incorporated hospital-specific and region-specific random effects to account for the clustering of patients within hospitals and regions. We used variance partition coefficients to describe the percentage of variation in the odds of admission that could be attributed to the patient level versus institutional and regional levels.
Ethics
Chart review for the Ontario Stroke Registry (OSR) is done without patient consent because ICES is named as a prescribed entity under provincial privacy legislation. This study was approved by the Sunnybrook Health Sciences Centre Research Ethics Board.
Results
The study sample consisted of 8540 patients seen in the ED with TIA or minor ischemic stroke between April 1, 2008, and March 31, 2011. Overall, 4030 (47.2%) were admitted to hospital. Baseline characteristics of participants are shown in Table 1.
Baseline characteristics of patients with minor ischemic stroke/TIA admitted to hospital or discharged from the ED
IQR, interquartile range; DBP, diastolic blood pressure; ED, emergency department; mRS, modified Rankin score; SBP, systolic blood pressure; TIA, transient ischemic attack.
* Neighbourhoods were divided into quintiles based on median income from 2006 Canada Census data, in which quintile 1 represents the lowest and quintile 5 represents the highest income quintile. An overcrowded ED shift was defined as one in which the mean ED length of stay was greater than 4 hours for patients of similar acuity seen in the same ED shift as the index patient.
In the multivariable analyses, significant predictors of hospital admission were disability before admission (adjusted odds ratio [AOR], 2.20; 95% confidence interval [CI], 1.75-2.76), diabetes (AOR, 1.14; 95% CI, 1.00-1.29), hypertension (AOR, 1.15; 95% CI, 1.02-1.31), smoking (AOR, 1.05; 95% CI, 1.05-1.46), atrial fibrillation (AOR, 1.71; 95% CI, 1.47-1.99), presentation with weakness (AOR, 1.17; 95% CI, 1.05-1.31), speech disturbance (AOR, 1.38; 95% CI, 1.22-1.56) or prolonged/persistent symptoms (AOR, 3.05; 95% CI, 2.18 2.76), arrival by ambulance (AOR, 2.45; 95% CI, 2.18-2.76), and presentation on a weekend (AOR, 1.14; 05% CI, 1.01-1.29) or during period of ED overcrowding (AOR, 1.26; 95% CI, 1.06-1.50) (Figure 1). Presentation with TIA rather than minor stroke was associated with a reduced odds of admission (AOR, 0.15; 95% CI, 0.13-0.17). Age, sex, neighbourhood income, rural residence, time from symptom onset to hospital arrival, hospital designation (regional or district stroke centre), and teaching status were not significant predictors of admission, nor was the presence of a stroke unit or a stroke prevention clinic on-site (Figure 1). Results were similar when the subgroups with minor stroke and TIA were analyzed separately (data not shown).
Forest plot of predictors of admission in patients with TIA and minor stroke.
There were variations in the proportion of patients admitted across regions, from a low of 37.5% to a high of 70.3%. After adjusting for patient, hospital, and regional characteristics, 88.4% of the remaining variation was due to between-patient variation, 11% was due to between-hospital variation, and 0.6% was due to between-region variation.
Discussion
In this contemporary population-based study, more than one-half of patients seen in the ED across the province of Ontario with TIA or minor ischemic stroke were not admitted to hospital, and there were wide regional variations in the proportion of patients admitted.
We found that the key predictors of hospital admission were preadmission dependence and vascular risk factors as well as high-risk presenting features such as weakness, speech disturbance, or prolonged/persistent symptoms. This likely reflects clinical decision-making based on the need to manage comorbid conditions as well as the use of prognostic scores such as the ABCD2 score to determine whether patients should be admitted or discharged.Reference Rothwell, Giles and Flossmann 8 , Reference Johnston, Rothwell and Nguyen-Huynh 9 However, the uneven performance of such scoring systems suggests a need for updated strategies to guide decisions about admission of patients with minor stroke and TIA. More recent risk prediction scores that incorporate the findings of initial imaging and other investigations may improve patient risk stratification.Reference Hill and Coutts 14
Studies from the United States have also documented admission rates for TIA in the range of 54% to 91%, with regional variations,Reference Edlow, Kim, Pelletier and Camargo 17 - Reference Chaudhry, Tariq and Majidi 19 although one study of patients seen in the era before publication of risk prediction tools found that only 14% of patients with TIA were admitted, and that admission only weakly correlated with the ABCD2 score.20 Another study using data from the National Emergency Department Sample evaluated predictors of hospitalization and found that, after adjustment for age and comorbid conditions, higher median household income, Medicare insurance type, and care at a teaching hospital were all associated with admission; the administrative data sources used for this study did not have information on presenting symptoms, so the effect of these and other clinical factors on the likelihood of admission could not be evaluated.Reference Chaudhry, Tariq and Majidi 19 In contrast, we found that hospital factors such as annual stroke patient volumes, designation as a stroke centre, rural location, teaching status, and having a stroke unit or a stroke prevention clinic on site were not associated with hospitalization, nor was median neighbourhood income. These differences may be a reflection of care provided within Canada’s universal health care system.
Our finding of a greater likelihood of hospitalization among patients presenting off hours or on weekends likely reflects a limited ability to coordinate and obtain rapid outpatient care at such times. Although individual patient circumstances will dictate admission in many cases, particularly those in which inpatient rehabilitation or management of comorbid conditions is required or in which there are concerns about the patient’s ability to return for follow-up, timely outpatient care is an alternative to hospitalization for many other patients. There is increasing recognition that it is the timing of the tests and treatments that is most important, rather than the specific setting in which these are provided. Rapid outpatient TIA assessment units have been successfully implemented in some jurisdictions internationally, but were not widely available in Ontario at the time of our study.Reference Torres MacHo, Peña Lillo and Pérez Martínez 21 - Reference Wu, Manns, Hill and Ghali 25
Our study had some limitations. It was not designed to determine which factors were associated with outcomes after stroke, to develop a risk prediction score, or to evaluate potential differences in outcomes between patients who were admitted to hospital and discharged from the ED. Although the Ontario Stroke Registry included detailed information on sociodemographic factors and presenting symptoms, there may have been specific features of the index event that prompted hospitalization but were not available in our data sources, such as lack of social supports, need for management of comorbid illnesses, availability of vascular neurologists, and patient preferences. In addition, we did not have information on whether hospitals used institutional protocols or local criteria for admission, or whether a local rapid TIA clinic was available, all factors that could have affected admission rates. Although charts were reviewed by trained neurology research nurses who consulted with stroke specialists and patients in which the diagnosis was uncertain were excluded from the analysis, there may have been differential misclassification of ED patients in whom TIA/stroke mimics are more common than in admitted patients, and we do not have information on how many discharged patients were ultimately diagnosed with something other than stroke/TIA. Finally, Ontario has a well-established regional system of stroke care that operates within a universal health care system, and some of our findings, such as the lack of association between income and hospitalization, may not be generalizable to other settings. However, our study strengths include the use of data from a large, population-based provincial registry with detailed information on presenting characteristics.
In summary, we found that almost one-half of patients seen in the ED with TIA and minor stroke were admitted to hospital. Although clinical factors such as comorbid conditions and presenting symptoms were the strongest predictors of admission, system factors such as presentation off-hours and on weekends were also associated with hospitalization, suggesting that some admissions could be avoided through improved access to outpatient care. Future activities should focus on updating clinical practice recommendations to provide more guidance on which patients with TIA/minor stroke warrant admission, and on developing and implementing appropriate alternatives to inpatient care.
Acknowledgements
We thank Brennan Rashkovan for his assistance with manuscript preparation.
The Ontario Stroke Registry is funded by the Canadian Stroke Network and the Ontario Ministry of Health and Long-Term Care (MOHLTC). The Institute for Clinical Evaluative Sciences (ICES) is supported by an operating grant from the MOHLTC. The sponsors had no role in the design and conduct of the study; in the collection, analysis, and interpretation of the data; or in the preparation, review, or approval of the manuscript. The opinions, results, and conclusions reported in this paper are those of the authors and are independent from the funding sources. No endorsement by ICES or the Ontario MOHLTC is intended or should be inferred.
Disclosures
MKK is supported by a Career Investigator award from the Heart and Stroke Foundation, Ontario Provincial Office. PCA was previously supported by a Career Investigator award from the Heart and Stroke Foundation, was a consultant for Boehringer Ingelhelm, Inc.’s for RESPECT-ESUS clinical trial, received consulting fees from, honoraria from, and was an advisory board member for Boehringer Ingelhelm, Inc. LKC served as an independent contractor (patient assessor for SURTAVI) for Medtronic and received consulting fees from and was a site principal investigator for NoNO Inc. FLS has served as a speaker for Boehringer Ingelheim Canada and Servier Canada and as a Canadian study coordinator for Boehringer Ingelheim Canada. DJG served on an advisory board for and received speaker’s fees from Bayer, BMS, and Pfizer and received speaker’s fees from Boehringer Ingelhelm, Inc. JT is supported by a Canada Research Chair in Health Services Research and an Eaton Scholar Award.
