Seasonal Variations in Stroke Occurrence.

BACKGROUND: Understanding seasonal variations in stroke can help stakeholders identify underlying causes in seasonal trends, and tailor resources appropriately to times of highest needs. We sought to evaluate the seasonal occurrence of stroke and its subtypes. METHODS: We conducted a retrospective cohort study using administrative data from January 1st, 2003, to December 31st, 2017, in Ontario, Canada's most populous province. We evaluated seasonal variations in stroke occurrence by subtype, via age/sex standardized rates and adjusted rate ratios using Poisson regressions. In those with stroke, we evaluated 30-day case fatality risks by season, adjusted for age, sex, stroke type, and comorbid conditions, and then used Cox proportional hazard models to estimate the effect of season on the fatality. The administrative data used in this study were from the Canadian Institute for Health Information's Discharge Abstract Database, the National Ambulatory Care Reporting System Database, the Ontario Registered Persons Database, and the 2006 and 2011 Canada Census and linked administrative databases. RESULTS: During our study period, we observed 394,145 strokes or TIA events, with a decrease in monthly hospitalization/emergency department visits per 100,000 people between January 2003 and December 2017 from 24.22 to 17.43. Compared to the summer, overall stroke occurrence was similar in the spring but slightly lower in the fall (adjusted rate ratio [aRR] 0.97, 95% confidence interval [CI] 0.96-0.98) and winter (aRR 0.94, 95% CI: 0.94-0.95). There were minor variations by stroke subtype. Winter was associated with the highest risk of stroke case fatality compared to the summer (12.4% vs. 11.4%, adjusted hazard ratio 1.10, 95% CI: 1.07-1.13). CONCLUSIONS: We found seasonal variations in stroke occurrence and case fatality, although the absolute differences were small. Further work is needed to better understand how environmental or meteorological factors might affect stroke risk.

Validation of the Passive Surveillance Stroke Severity Score in Three Canadian Provinces.

BACKGROUND: Stroke outcomes research requires risk-adjustment for stroke severity, but this measure is often unavailable. The Passive Surveillance Stroke SeVerity (PaSSV) score is an administrative data-based stroke severity measure that was developed in Ontario, Canada. We assessed the geographical and temporal external validity of PaSSV in British Columbia (BC), Nova Scotia (NS) and Ontario, Canada. METHODS: We used linked administrative data in each province to identify adult patients with ischemic stroke or intracerebral hemorrhage between 2014-2019 and calculated their PaSSV score. We used Cox proportional hazards models to evaluate the association between the PaSSV score and the hazard of death over 30 days and the cause-specific hazard of admission to long-term care over 365 days. We assessed the models' discriminative values using Uno's c-statistic, comparing models with versus without PaSSV. RESULTS: We included 86,142 patients (n = 18,387 in BC, n = 65,082 in Ontario, n = 2,673 in NS). The mean and median PaSSV were similar across provinces. A higher PaSSV score, representing lower stroke severity, was associated with a lower hazard of death (hazard ratio and 95% confidence intervals 0.70 [0.68, 0.71] in BC, 0.69 [0.68, 0.69] in Ontario, 0.72 [0.68, 0.75] in NS) and admission to long-term care (0.77 [0.76, 0.79] in BC, 0.84 [0.83, 0.85] in Ontario, 0.86 [0.79, 0.93] in NS). Including PaSSV in the multivariable models increased the c-statistics compared to models without this variable. CONCLUSION: PaSSV has geographical and temporal validity, making it useful for risk-adjustment in stroke outcomes research, including in multi-jurisdiction analyses.

Proportion of Life Spent in Canada and the Incidence of Multiple Sclerosis in Permanent Immigrants.

BACKGROUND AND OBJECTIVES: While immigrants to high-income countries have a lower risk of multiple sclerosis (MS) compared with host populations, it is unknown whether this lower risk among immigrants increases over time. Our objective was to evaluate the association between proportion of life spent in Canada and the hazard of incident MS in Canadian immigrants. METHODS: We conducted a population-based retrospective cohort study in Ontario, using linked health administrative databases. We followed immigrants, who arrived in Ontario between 1985 and 2003, from January 1, 2003, to December 31, 2016, to record incident MS using a validated algorithm based on hospital admission or outpatient visits. We derived proportion of life spent in Canada based on age at arrival and time since immigration obtained from linked immigration records. We used multivariable proportional hazard models, adjusting for demographics and comorbidities, to evaluate the association between proportion of life in Canada and the incidence of MS, where proportion of life was modelled using restricted cubic spline terms. We further evaluated the role of age at migration (15 or younger vs older than 15 years), sex, and immigration class in sensitivity analyses. RESULTS: We included 1.5 million immigrants (49.9% female, mean age 35.9 [SD 14.2] years) who had spent a median of 20% (Q1-Q3 10%-30%) of their life in Canada. During a mean follow-up of 13.9 years (SD 1.0), 934 (0.44/100,000 person-years) were diagnosed with MS. Compared with the median, a higher risk of MS was observed at higher values of proportion of life spent (e.g., hazard ratio [70% vs 20% proportion of life] 1.38; 1.07-1.78). This association did not vary by sex (p(sex × proportion of life) = 0.70) or immigration class (p(immigration class × proportion of life) = 0.13). The results did not vary by age at migration but were statistically significant only at higher values of proportion of life for immigrants aged 15 years or younger at arrival. DISCUSSION: The risk of incident MS in immigrants varied with the proportion of life spent in Canada, suggesting an acculturation effect on MS risk. Further work is required to understand environmental and sociocultural factors driving the observed association.

Secondary Stroke Prevention in People With Schizophrenia.

BACKGROUND: People with schizophrenia are less likely than those without to be treated for cardiovascular disease. We aimed to evaluate the association between schizophrenia and secondary preventive care after ischemic stroke. METHODS AND RESULTS: In this retrospective cohort study, we used linked population-based administrative data to identify adults who survived 1 year after ischemic stroke hospitalization in Ontario, Canada between 2004 and 2017. Outcomes were screening, treatment, and control of risk factors, and receipt of outpatient physician services. We used modified Poisson regression to model the relative risk of each outcome among people with and without schizophrenia, adjusting for age and other factors. Among 81 163 people with ischemic stroke, 844 (1.04%) had schizophrenia. Schizophrenia was associated with lower rates of screening for hyperlipidemia (60.5% versus 66.0%, adjusted relative risk [aRR] 0.88 [95% CI, 0.84-0.93]) and diabetes (69.4% versus 73.9%, aRR 0.93 [95% CI, 0.89-0.97]), prescription of antihypertensive medications (91.2% versus 94.7%, aRR 0.96 [95% CI, 0.93-0.99]), achievement of target lipid levels (low-density lipoprotein <2 mmol/L) (30.6% versus 34.6%, aRR 0.86 [95% CI, 0.78-0.96]), and outpatient specialist visits (55.3% versus 67.8%, aRR 0.78 [95% CI, 0.74-0.83]) or primary care physician visits (94.5% versus 98.5%; aRR 0.96 [95% CI, 0.95-0.98]) within 1 year. There were no differences in prescription of antilipemic, antiglycemic, or anticoagulant medications, or in achievement of target hemoglobin A1c ≤7%. CONCLUSIONS: People with stroke and schizophrenia are less likely than those without to receive secondary preventive care. This may inform interventions to improve poststroke care and outcomes in those with schizophrenia.

Adverse perinatal events and maternal interpregnancy weight change: A population-based observational study.

OBJECTIVE: Mothers whose newborn experiences adversity may neglect their own health to care for their affected infant or following a perinatal death. Weight gain after pregnancy is one measure of maternal self-care. We measured interpregnancy weight gain among women whose child had an adverse perinatal event. METHODS: This population-based observational study included 192 154 primigravid women with two consecutive singleton births in Ontario, Canada. Outcomes included net weight gain, and adjusted odds ratios (aOR) of moving to a higher body mass index (BMI) category between pregnancies, comparing women whose child did versus did not experience either a perinatal death, prematurity, severe neonatal morbidity, major congenital anomaly, or severe neurologic impairment. RESULTS: Perinatal death was associated with a +3.5 kg (95% confidence interval [CI]: 2.1-4.9) net higher maternal weight gain in the subsequent pregnancy. Relative to term births, preterm birth <32 weeks (+3.2 kg, 95% CI: 1.9-4.6), 32-33 weeks (+1.8 kg, 95% CI: 0.7-2.8) and 34-36 weeks (+0.9 kg, 95% CI: 0.6-1.3) were associated with higher net weight gain. Having an infant with severe neonatal morbidity was associated with a +1.2 kg (95% CI: 0.3-2.1) weight gain. Likewise, the aOR of moving to a higher BMI category was 1.27 (95% CI, 1.14-1.42) following a perinatal death, 1.21 (95% CI: 1.04-1.41) after a preterm birth <32 weeks, and 1.11 (95% CI: 1.02-1.22) with severe neonatal morbidity. CONCLUSION: Greater interpregnancy weight gain, and movement to a higher BMI category, are each more likely in a woman whose first-born was affected by certain major adverse perinatal events.

Association Between Immigration Status and Ambulatory Secondary Stroke Preventive Care in Ontario, Canada.

BACKGROUND AND OBJECTIVES: Secondary stroke preventive care includes evaluation and control of vascular risk factors to prevent stroke recurrence. Our objective was to evaluate the quality of ambulatory stroke preventive care and its variation by immigration status in adult stroke survivors in Ontario, Canada. METHODS: We conducted a population-based administrative database-derived retrospective cohort study in Ontario, Canada. Using immigration records, we defined immigrants as those immigrating after 1985 and long-term residents as those arriving before 1985 or those born in Canada. We included community-dwelling stroke survivors 40 years and older with a first-ever stroke between 2011 and 2017. In the year following their stroke, we evaluated the following metrics of stroke prevention: testing for hyperlipidemia and diabetes; among those with the condition, control of diabetes (hemoglobin A1c ≤7%) and hyperlipidemia (low-density lipoprotein <2 mmol/L); medication use to control hypertension, diabetes, and atrial fibrillation; and visit to a family physician and a specialist (neurologist, cardiologist, or geriatrician). We determined age and sex-adjusted absolute prevalence difference (APD) between immigrants and long-term residents for each metric using generalized linear models with binomial distribution and an identity link function. RESULTS: We included 34,947 stroke survivors (median age 70 years, 46.9% women) of whom 12.4% were immigrants. The receipt of each metric ranged from 68% to 90%. Compared with long-term residents, after adjusting for age and sex, immigrants were slightly more likely to receive screening for hyperlipidemia (APD 5.58%; 95% CI 4.18-6.96) and diabetes (5.49%; 3.76-7.23), have visits to family physicians (1.19%; 0.49-1.90), receive a prescription for antihypertensive (3.12%; 1.76-4.49) and antihyperglycemic medications (9.51%; 6.46-12.57), and achieve control of hyperlipidemia (3.82%; 1.01-6.63). By contrast, they were less likely to achieve diabetes control (-4.79%; -7.86 to -1.72) or have visits to a specialist (-1.68%; -3.12 to -0.24). There was minimal variation by region of origin or time since immigration in immigrants. DISCUSSION: Compared with long-term residents, many metrics of secondary stroke preventive care were better in immigrants, albeit with small absolute differences. However, future work is needed to identify and mitigate the factors associated with the suboptimal quality of stroke preventive care for all stroke survivors.

Derivation and validation of predictive indices for cardiac readmission after coronary and valvular surgery - A multicenter study.

Objective: To derive and validate models to predict the risk of a cardiac readmission within one year after specific cardiac surgeries using information that is commonly available from hospital electronic medical records. Methods: In this retrospective cohort study, we derived and externally validated clinical models to predict the likelihood of cardiac readmissions within one-year of isolated CABG, AVR, and combined CABG+AVR in Ontario, Canada, using multiple clinical registries and routinely collected administrative databases. For all adult patients who underwent these procedures, multiple Fine and Gray subdistribution hazard models were derived within a competing-risk framework using the cohort from April 2015 to March 2018 and validated in an independent cohort (April 2018 to March 2020). Results: For the model that predicted post-CABG cardiac readmission, the c-statistic was 0.73 in the derivation cohort and 0.70 in the validation cohort at one-year. For the model that predicted post-AVR cardiac readmission, the c-statistic was 0.74 in the derivation and 0.73 in the validation cohort at one-year. For the model that predicted cardiac readmission following CABG+AVR, the c-statistic was 0.70 in the derivation and 0.66 in the validation cohort at one-year. Conclusions: Prediction of one-year cardiac readmission for isolated CABG, AVR, and combined CABG+AVR can be achieved parsimoniously using multidimensional data sources. Model discrimination was better than existing models derived from single and multicenter registries.

Development and validation of a model to categorize cardiovascular cause of death using health administrative data.

Study objective: Develop and evaluate a model that uses health administrative data to categorize cardiovascular (CV) cause of death (COD). Design: Population-based cohort. Setting: Ontario, Canada. Participants: Decedents ≥ 40 years with known COD between 2008 and 2015 in the CANHEART cohort, split into derivation (2008 to 2012; n = 363,778) and validation (2013 to 2015; n = 239,672) cohorts. Main outcome measures: Model performance. COD was categorized as CV or non-CV with ICD-10 codes as the gold standard. We developed a logistic regression model that uses routinely collected healthcare administrative to categorize CV versus non-CV COD. We assessed model discrimination and calibration in the validation cohort. Results: The strongest predictors for CV COD were history of stroke, history of myocardial infarction, history of heart failure, and CV hospitalization one month before death. In the validation cohort, the c-statistic was 0.80, the sensitivity 0.75 (95 % CI 0.74 to 0.75) and the specificity 0.71 (95 % CI 0.70 to 0.71). In the primary prevention validation sub-cohort, the c-statistic was 0.81, the sensitivity 0.71 (95 % CI 0.70 to 0.71) and the specificity 0.75 (95 % CI 0.75 to 0.75) while in the secondary prevention sub-cohort the c-statistic was 0.74, the sensitivity 0.81 (95 % CI 0.81 to 0.82) and the specificity 0.54 (95 % CI 0.53 to 0.54). Conclusion: Modelling approaches using health administrative data show potential in categorizing CV COD, though further work is necessary before this approach is employed in clinical studies.