Development of pneumonia after stroke was associated with mortality at 30 days and 1 year, longer length of stay, and dependency at discharge. Patients who received more inpatient stroke services had reduced mortality after pneumonia.

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Background and Purpose-Previous estimates of the number and prevalence of individuals experiencing the effects of stroke in Canada are out of date and exclude critical population groups. It is essential to have complete data that report on stroke disability for monitoring and planning purposes. The objective was to provide an updated estimate of the number of individuals experiencing the effects of stroke in Canada (and its regions), trending since 2000 and forecasted prevalence to 2038. Methods-The prevalence, trends, and projected number of individuals experiencing the effects of stroke were estimated using region-specific survey data and adjusted to account for children aged <12 years and individuals living in homes for the aged. Results-In 2013, we estimate that there were 405 000 individuals experiencing the effects of stroke in Canada, yielding a prevalence of 1.15%. This value is expected to increase to between 654 000 and 726 000 by 2038. Trends in stroke data between 2000 and 2012 suggest a nonsignificant decrease in stroke prevalence, but a substantial and rising increase in the number of individuals experiencing the effects of stroke. Stroke prevalence varied considerably between regions. Conclusions-Previous estimates of stroke prevalence have underestimated the true number of individuals experiencing the effects of stroke in Canada. Furthermore, the projected increases that will result from population growth and demographic changes highlight the importance of maintaining up-to-date estimates.

BackgroundAlthough psychoses and ethnicity are well researched, the importance of culture, race and ethnicity has been overlooked in Personality Disorders (PD) research. This study aimed to review the published literature on ethnic variations of prevalence, aetiology and treatment of PD.MethodA systematic review of studies of PD and race, culture and ethnicity including a narrative synthesis of observational data and meta-analyses of prevalence data with tests for heterogeneity.ResultsThere were few studies with original data on personality disorder and ethnicity. Studies varied in their classification of ethnic group, and few studies defined a specific type of personality disorder. Overall, meta-analyses revealed significant differences in prevalence between black and white groups (OR 0.476, CIs 0.248 - 0.915, p = 0.026) but no differences between Asian or Hispanic groups compared with white groups. Meta-regression analyses found that heterogeneity was explained by some study characteristics: a lower prevalence of PD was reported among black compared with white patients in UK studies, studies using case-note diagnoses rather than structured diagnostic interviews, studies of borderline PD compared with the other PD, studies in secure and inpatient compared with community settings, and among subjects with co-morbid disorders compared to the rest. The evidence base on aetiology and treatment was small.ConclusionThere is some evidence of ethnic variations in prevalence of personality disorder but methodological characteristics are likely to account for some of the variation. The findings may indicate neglect of PD diagnosis among ethnic groups, or a true lower prevalence amongst black patients. Further studies are required using more precise cultural and ethnic groups.

Objective: Administrative data validation is essential for identifying biases and misclassification in research. The objective of this study was to determine the accuracy of diagnostic codes for acute stroke and transient ischemic attack (TIA) using the Ontario Stroke Registry (OSR) as the reference standard. Methods: We identified stroke and TIA events in inpatient and emergency department (ED) administrative data from eight regional stroke centres in Ontario, Canada, from April of 2006 through March of 2008 using ICD-10-CA codes for subarachnoid haemorrhage (I60, excluding I60.8), intracerebral haemorrhage (I61), ischemic (H34.1 and I63, excluding I63.6), unable to determine stroke (I64), and TIA (H34.0 and G45, excluding G45.4). We linked administrative data to the Ontario Stroke Registry and calculated sensitivity and positive predictive value (PPV). Results: We identified 5,270 inpatient and 4,411 ED events from the administrative data. Inpatient administrative data had an overall sensitivity of 82.2% (95% confidence interval [CI 95% ] = 81.0, 83.3) and a PPV of 68.8% (CI 95% = 67.5, 70.0) for the diagnosis of stroke, with notable differences observed by stroke type. Sensitivity for ischemic stroke increased from 66.5 to 79.6% with inclusion of I64. The sensitivity and PPV of ED administrative data for diagnosis of stroke were 56.8% (CI 95% = 54.8, 58.7) and 59.1% (CI 95% = 57.1, 61.1), respectively. For all stroke types, accuracy was greater in the inpatient data than in the ED data. Conclusion: The accuracy of stroke identification based on administrative data from stroke centres may be improved by including I64 in ischemic stroke type, and by considering only inpatient data.

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Background: Rural residence is associated with stroke incidence and mortality, but little is known about potential rural/urban differences in ambulatory stroke care. Methods and Results: We used the CANHEART (Cardiovascular Health in Ambulatory Care Research Team) cohort, created from linked administrative databases from the province of Ontario, Canada, and divided into primary (N=6 207 032) and secondary (N=75 823) prevention cohorts based on the absence or presence of prior stroke. We defined rural communities as those with a population size of ≤10 000 and within each of the primary and secondary prevention cohorts, compared cardiovascular risk factors and care between rural and urban areas. We then calculated sex-/age-standardized rates of stroke incidence and mortality per 1000 person-years between January 1, 2008 and December 31, 2012 and used cause-specific hazard models to compare outcomes in rural versus urban areas adjusting for age, sex, income, ethnicity, smoking, physical activity and comorbid conditions, and accounting for the competing risk of death in the model for the occurrence of stroke incidence. In the primary prevention cohort, rural residents were less likely than urban ones to be screened for diabetes mellitus (70.9% versus 81.3%) and hyperlipidemia (66.2% versus 78.4%) and less likely to achieve diabetes mellitus control (hemoglobin A1c ≤7% in 51.3% versus 54.3%; P <0.001 for all comparisons). In the secondary prevention cohort, the prevalence and treatment of risk factors were similar in rural and urban residents. After adjustment for sociodemographic and comorbid conditions, rural residence was associated with higher rates of stroke and all-cause mortality in both the primary prevention (adjusted hazard ratio [aHR] for stroke, 1.06; 95% CI, 1.04–1.09; aHR for mortality, 1.09; 95% CI, 1.08–1.10) and the secondary prevention cohort (aHR for stroke, 1.11; 95% CI, 1.02–1.19; aHR for mortality, 1.07; 95% CI, 1.03–1.11). Conclusions: In this population-based study of over 6 million people with universal access to physician and hospital services, risk factors were more prevalent but less likely to be controlled in rural than in urban residents without prior stroke, whereas in those with prior stroke, risk factor prevalence and treatment were similar. Rural residence was associated with the rate of stroke and death even after adjustment for risk factors. Future efforts should focus not only on control of known vascular risk factors but also on addressing other determinants of health in rural communities.