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BACKGROUND AND AIMS: Female sex is associated with higher rates of stroke in atrial fibrillation (AF) after adjustment for other CHA2DS2-VASc factors. This study aimed to describe sex differences in age and cardiovascular care to examine their relationship with stroke hazard in AF. METHODS: Population-based cohort study using administrative datasets of people aged ≥66 years diagnosed with AF in Ontario between 2007 and 2019. Cause-specific hazard regression was used to estimate the adjusted hazard ratio (HR) for stroke associated with female sex over a 2-year follow-up. Model 1 included CHA2DS2-VASc factors, with age modelled as 66-74 vs. ≥ 75 years. Model 2 treated age as a continuous variable and included an age-sex interaction term. Model 3 further accounted for multimorbidity and markers of cardiovascular care. RESULTS: The cohort consisted of 354 254 individuals with AF (median age 78 years, 49.2% female). Females were more likely to be diagnosed in emergency departments and less likely to receive cardiologist assessments, statins, or LDL-C testing, with higher LDL-C levels among females than males. In Model 1, the adjusted HR for stroke associated with female sex was 1.27 (95% confidence interval 1.21-1.32). Model 2 revealed a significant age-sex interaction, such that female sex was only associated with increased stroke hazard at age >70 years. Adjusting for markers of cardiovascular care and multimorbidity further decreased the HR, so that female sex was not associated with increased stroke hazard at age ≤80 years. CONCLUSION: Older age and inequities in cardiovascular care may partly explain higher stroke rates in females with AF.
Subject(s)
Atrial Fibrillation , Stroke , Female , Humans , Male , Aged , Aged, 80 and over , Atrial Fibrillation/complications , Atrial Fibrillation/epidemiology , Atrial Fibrillation/diagnosis , Cohort Studies , Cholesterol, LDL , Stroke/etiology , Stroke/complications , Proportional Hazards Models , Risk Factors , Risk AssessmentABSTRACT
BACKGROUND: Interhospital transfer for patients with stroke due to large vessel occlusion for endovascular thrombectomy (EVT) has been associated with treatment delays. METHODS: We analyzed data from Optimizing Patient Treatment in Major Ischemic Stroke With EVT, a quality improvement registry to support EVT implementation in Canada. We assessed for unadjusted differences in baseline characteristics, time metrics, and procedural outcomes between patients with large vessel occlusion transferred for EVT and those directly admitted to an EVT-capable center. RESULTS: Between January 1, 2018, and December 31, 2021, a total of 6803 patients received EVT at 20 participating centers (median age, 73 years; 50% women; and 50% treated with intravenous thrombolysis). Patients transferred for EVT (n=3376) had lower rates of M2 occlusion (22% versus 27%) and higher rates of basilar occlusion (9% versus 5%) compared with those patients presenting directly at an EVT-capable center (n=3373). Door-to-needle times were shorter in patients receiving intravenous thrombolysis before transfer compared with those presenting directly to an EVT center (32 versus 36 minutes). Patients transferred for EVT had shorter door-to-arterial access times (37 versus 87 minutes) but longer last seen normal-to-arterial access times (322 versus 181 minutes) compared with those presenting directly to an EVT-capable center. No differences in arterial access-to-reperfusion times, successful reperfusion rates (85% versus 86%), or adverse periprocedural events were found between the 2 groups. Patients transferred to EVT centers had a similar likelihood for good functional outcome (modified Rankin Scale score, 0-2; 41% versus 43%; risk ratio, 0.95 [95% CI, 0.88-1.01]; adjusted risk ratio, 0.98 [95% CI, 0.91-1.05]) and a higher risk for all-cause mortality at 90 days (29% versus 25%; risk ratio, 1.15 [95% CI, 1.05-1.27]; adjusted risk ratio, 1.14 [95% CI, 1.03-1.28]) compared with patients presenting directly to an EVT center. CONCLUSIONS: Patients transferred for EVT experience significant delays from the time they were last seen normal to the initiation of EVT.
Subject(s)
Endovascular Procedures , Ischemic Stroke , Patient Transfer , Registries , Thrombectomy , Time-to-Treatment , Humans , Female , Male , Aged , Endovascular Procedures/methods , Canada/epidemiology , Middle Aged , Aged, 80 and over , Thrombectomy/methods , Ischemic Stroke/surgery , Ischemic Stroke/therapy , Stroke/therapy , Stroke/surgery , Stroke/epidemiology , Thrombolytic Therapy/methods , Treatment OutcomeABSTRACT
BACKGROUND: Understanding sex differences in stroke care is important in reducing potential disparities. Our objective was to explore sex differences in workflow efficiency, treatment efficacy, and safety in the AcT trial (Alteplase Compared to Tenecteplase). METHODS: AcT was a multicenter, registry-linked randomized noninferiority trial comparing tenecteplase (0.25 mg/kg) with alteplase (0.9 mg/kg) in acute ischemic stroke within 4.5 hours of onset. In this post hoc analysis, baseline characteristics, workflow times, successful reperfusion (extended Thrombolysis in Cerebral Infarction score ≥2b), symptomatic intracerebral hemorrhage, 90-day functional independence (modified Rankin Scale score, 0-1), and 90-day mortality were compared by sex. Mixed-effects regression analysis was used adjusting for age, stroke severity, and occlusion site for outcomes. RESULTS: Of 1577 patients treated with intravenous thrombolysis (2019-2022), 755 (47.9%) were women. Women were older (median, 77 [68-86] years in women versus 70 [59-79] years in men) and had a higher proportion of severe strokes (National Institutes of Health Stroke Scale score >15; 32.4% versus 24.9%) and large vessel occlusions (28.7% versus 21.5%) compared with men. All workflow times were comparable between sexes. Women were less likely to achieve functional independence (31.7% versus 39.8%; unadjusted relative risk, 0.80 [95% CI, 0.70-0.91]) and had higher mortality (17.7% versus 13.3%; unadjusted relative risk, 1.33 [95% CI, 1.06-1.69]). Adjusted analysis showed no difference in outcomes between sexes. CONCLUSIONS: Differences in prognostic factors of age, stroke severity, and occlusion site largely accounted for higher functional dependence and mortality in women. No sex disparities were apparent in workflow quality indicators. Given the integration of the AcT trial into clinical practice, these results provide reassurance that no major sex biases are apparent in acute stroke management throughout participating Canadian centers. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT03889249.
Subject(s)
Ischemic Stroke , Tenecteplase , Tissue Plasminogen Activator , Female , Humans , Male , Canada , Ischemic Stroke/drug therapy , Tenecteplase/adverse effects , Tissue Plasminogen Activator/adverse effects , Treatment Outcome , Workflow , Multicenter Studies as Topic , Randomized Controlled Trials as Topic , Equivalence Trials as TopicABSTRACT
Women face a disproportionate burden of stroke mortality and disability. Biologic sex and sociocultural gender both contribute to differences in stroke risk factors, assessment, treatment, and outcomes. There are substantial differences in the strength of association of stroke risk factors, as well as female-specific risk factors. Moreover, there are differences in presentation, response to treatment, and stroke outcomes in women. This review outlines current knowledge of impact of sex and gender on stroke, as well as delineates research gaps and areas for future inquiry.
Subject(s)
Sex Characteristics , Stroke/epidemiology , Stroke/physiopathology , Diabetes Mellitus/blood , Diabetes Mellitus/epidemiology , Diabetes Mellitus/physiopathology , Estrogens/blood , Female , Humans , Hypertension/blood , Hypertension/epidemiology , Hypertension/physiopathology , Pregnancy , Pregnancy Complications, Cardiovascular/blood , Pregnancy Complications, Cardiovascular/epidemiology , Pregnancy Complications, Cardiovascular/physiopathology , Risk Factors , Sex Factors , Stroke/bloodABSTRACT
OBJECTIVE: To examine the association of co-morbidity with home-time after acute stroke and whether the association is influenced by age. METHODS: We conducted a province-wide study using linked administrative databases to identify all admissions for first acute ischemic stroke or intracerebral hemorrhage between 2007 and 2018 in Alberta, Canada. We used ischemic stroke-weighted Charlson Co-morbidity Index of 3 or more to identify those with severe co-morbidity. We used zero-inflated negative binomial models to determine the association of severe co-morbidity with 90-day and 1-year home-time, and logistic models for achieving ≥ 80 out of 90 days of home-time, assessing for effect modification by age and adjusting for sex, stroke type, comprehensive stroke center care, hypertension, atrial fibrillation, year of study, and separately adjusting for estimated stroke severity. We also evaluated individual co-morbidities. RESULTS: Among 28,672 patients in our final cohort, severe co-morbidity was present in 27.7% and was associated with lower home-time, with a greater number of days lost at younger age (-13 days at age < 60 compared to -7 days at age 80+ years for 90-day home-time; -69 days at age < 60 compared to -51 days at age 80+ years for 1-year home-time). The reduction in probability of achieving ≥ 80 days of home-time was also greater at younger age (-22.7% at age < 60 years compared to -9.0% at age 80+ years). Results were attenuated but remained significant after adjusting for estimated stroke severity and excluding those who died. Myocardial infarction, diabetes, and cancer/metastases had a greater association with lower home-time at younger age, and those with dementia had the greatest reduction in home time. CONCLUSION: Severe co-morbidity in acute stroke is associated with lower home-time, more strongly at younger age.
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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.
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BACKGROUND AND PURPOSE: To assess cost-effectiveness of late time-window endovascular treatment (EVT) in a clinical trial setting and a "real-world" setting. METHODS: Data are from the randomized ESCAPE trial and a prospective cohort study (ESCAPE-LATE). Anterior circulation large vessel occlusion patients presenting > 6 hours from last-known-well were included, whereby collateral status was an inclusion criterion for ESCAPE but not ESCAPE-LATE. A Markov state transition model was built to estimate lifetime costs and quality-adjusted life-years (QALYs) for EVT in addition to best medical care vs. best medical care only in a clinical trial setting (comparing ESCAPE-EVT to ESCAPE control arm patients) and a "real-world" setting (comparing ESCAPE-LATE to ESCAPE control arm patients). We performed an unadjusted analysis, using 90-day modified Rankin Scale(mRS) scores as model input and analysis adjusted for baseline factors. Acceptability of EVT was calculated using upper/lower willingness-to-pay thresholds of 100,000 USD/50,000 USD/QALY. RESULTS: Two-hundred and forty-nine patients were included (ESCAPE-LATE:n = 200, ESCAPE EVT-arm:n = 29, ESCAPE control-arm:n = 20). Late EVT in addition to best medical care was cost effective in the unadjusted analysis both in the clinical trial and real-world setting, with acceptability 96.6%-99.0%. After adjusting for differences in baseline variables between the groups, late EVT was marginally cost effective in the clinical trial setting (acceptability:49.9%-61.6%), but not the "real-world" setting (acceptability:32.9%-42.6%). CONCLUSION: EVT for LVO-patients presenting beyond 6 hours was cost effective in the clinical trial setting and "real-world" setting, although this was largely related to baseline patient differences favoring the "real-world" EVT group. After adjusting for these, EVT benefit was reduced in the trial setting, and absent in the real-world setting.
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BACKGROUND: Estimates of attributable costs of stroke are scarce, as most prior studies do not account for the baseline health care costs in people at risk of stroke. We estimated the attributable costs of stroke in a universal health care setting and their variation across stroke types and several social determinants of health. METHODS: We undertook a population-based administrative database-derived matched retrospective cohort study in Ontario, Canada. Community-dwelling adults aged ≥40 years with a stroke between 2003 and 2018 were matched (1:1) on demographics and comorbidities with controls without stroke. Using a difference-in-differences approach, we estimated the mean 1-year direct health care costs attributable to stroke from a public health care payer perspective, accounting for censoring with a weighted available sample estimator. We described health sector-specific costs and reported variation across stroke type and social determinants of health. RESULTS: The mean 1-year attributable costs of stroke were Canadian dollars 33â 522 (95% CI, $33â 231-$33â 813), with higher costs for intracerebral hemorrhage ($40â 244; $39â 193-$41â 294) than ischemic stroke ($32â 547; $32â 252-$32â 843). Most of these costs were incurred in acute care hospitals ($15â 693) and rehabilitation facilities ($7215). Compared with all patients with stroke, the mean attributable costs were higher among immigrants ($40â 554; $39â 316-$41â 793), those aged <65 years ($35â 175; $34â 533-$35â 818), and those residing in low-income neighborhoods ($34â 687; $34â 054-$35â 320) and lower among rural residents ($29â 047; $28â 362-$29â 731). CONCLUSIONS: Our findings of high attributable costs of stroke, especially in immigrants, younger patients, and residents of low-income neighborhoods, can be used to evaluate potential health care cost savings associated with different primary stroke prevention strategies.
Subject(s)
Social Determinants of Health , Stroke , Adult , Humans , Ontario/epidemiology , Retrospective Studies , Stroke/epidemiology , Stroke/therapy , Health Care CostsABSTRACT
BACKGROUND: Studying the baseline incidence of cerebral venous thrombosis (CVT) prior to COVID-19 and the limitations of how this has been previously reported in the literature will help improve understanding of this disease and how risks may have changed in the post-COVID era. METHODS: We examined CVT incidence using linked administrative data in British Columbia, Canada (population 5.2 million). To contextualize our findings, we also examined CVT incidence in the published literature and searched MEDLINE and EMBASE for article titles and abstracts up to Nov 2, 2021 on CVT incidence in adults. We performed abstract screening and full-text review prior to data extraction and explored associations between CVT incidence and year of study, geographic location, and study quality with meta-analyses and meta-regression. A random-effects restricted maximum likelihood model was used. Publication bias was assessed using the Egger tests and using visual inspection of the funnel plot for symmetry. RESULTS: There were 554 unique CVT cases (mean age 50.9 years, 55.4% women) in British Columbia from 2000 to 2017; overall annual incidence was 8.7 (95%CI' 8.0-9.4) per million. Incidence increased over time in men across the entire study period, and from 2011 to 2017 in women. We identified 22 other studies on CVT incidence before 2020 (21/23 total studies included in meta-analysis). Annual incidence overall was 12.1 (95% CI' 9.9-14.3) per million with significant between-study heterogeneity (I2 98.8%, Qp-value<0.001). There were no significant associations on meta-regression between incidence and study year, study quality score, or gross national income per capita of the study country. Visual inspection of the funnel plot and a significant Egger test (z=2.8, P<0.01) suggested possible publication bias. CONCLUSIONS: Incidence of CVT in Canadian data increased over time but remained lower than in other population-based studies. Significant heterogeneity exists in the literature, which may be subject to publication bias.
Subject(s)
COVID-19 , Intracranial Thrombosis , Venous Thrombosis , Male , Adult , Humans , Female , Middle Aged , Incidence , Intracranial Thrombosis/epidemiology , Venous Thrombosis/epidemiology , Venous Thrombosis/diagnosis , British Columbia/epidemiologyABSTRACT
BACKGROUND: Pregnancy-associated stroke carries high short-term morbidity and mortality, but data on subsequent maternal outcomes are limited. We evaluated long-term maternal health outcomes after pregnancy-associated stroke. METHODS: In this retrospective cohort study, we used administrative data to identify pregnant adults aged ≤49 years with stroke between 2002-2020 in Ontario, Canada and 2 comparison groups: (1) non-pregnant female patients with stroke and (2) pregnant patients without stroke. Patients who survived the index admission were followed until 2021. After propensity score matching, we used Cox regression with a robust variance estimator to compare pregnant patients with stroke and the 2 comparison groups for the composite outcome of death and all-cause non-pregnancy readmission. Where proportional hazard assumption was not met, we reported time-varying hazard ratios (HR) with 95% CIs by modeling the log-hazard ratio as a function of time using restricted cubic splines. RESULTS: We identified 217 pregnant patients with stroke, 7604 non-pregnant patients with stroke, and 1 496 256 pregnant patients without stroke. Of the 202 pregnant patients with stroke who survived the index stroke admission, 41.6% (6.8 per 100 person-years) subsequently died or were readmitted during follow-up. Median follow-up times were 5 years (pregnancy-associated stroke), 3 years (non-pregnant stroke), and 8 years (pregnant without stroke). Pregnant patients with stroke had a lower hazard of death and all-cause readmission compared with non-pregnant patients with stroke at 1-year follow-up (HR, 0.64 [95% CI, 0.44-0.94]), but this association did not persist during longer-term follow-up. Conversely, pregnant patients with stroke had higher hazard of death and readmission compared with pregnant patients without stroke at 1-year follow-up (HR, 5.70 [95% CI, 3.04-10.66]), and this association persisted for a decade. CONCLUSIONS: Stroke during pregnancy is associated with long-term health consequences. It is essential to transition care postpartum to primary or specialty care to optimize vascular health.
Subject(s)
Stroke , Adult , Humans , Female , Retrospective Studies , Follow-Up Studies , Stroke/etiology , Ontario , Outcome Assessment, Health CareABSTRACT
BACKGROUND: Adjustment for baseline stroke severity is necessary for accurate assessment of hospital performance. We evaluated whether adjusting for the Passive Surveillance Stroke SeVerity (PaSSV) score, a measure of stroke severity derived using administrative data, changed hospital-specific estimated 30-day risk-standardized mortality rate (RSMR) after stroke. METHODS: We used linked administrative data to identify adults who were hospitalized with ischemic stroke or intracerebral hemorrhage across 157 hospitals in Ontario, Canada between 2014 and 2019. We fitted a random effects logistic regression model using Markov Chain Monte Carlo methods to estimate hospital-specific 30-day RSMR and 95% credible intervals with adjustment for age, sex, Charlson comorbidity index, and stroke type. In a separate model, we additionally adjusted for stroke severity using PaSSV. Hospitals were defined as low-performing, average-performing, or high-performing depending on whether the RSMR and 95% credible interval were above, overlapping, or below the cohort's crude mortality rate. RESULTS: We identified 65,082 patients [48.0% were female, the median age (25th,75th percentiles) was 76 years (65,84), and 86.4% had an ischemic stroke]. The crude 30-day all-cause mortality rate was 14.1%. The inclusion of PaSSV in the model reclassified 18.5% (n=29) of the hospitals. Of the 143 hospitals initially classified as average-performing, after adjustment for PaSSV, 20 were reclassified as high-performing and 8 were reclassified as low-performing. Of the 4 hospitals initially classified as low-performing, 1 was reclassified as high-performing. All 10 hospitals initially classified as high-performing remained unchanged. CONCLUSION: PaSSV may be useful for risk-adjusting mortality when comparing hospital performance. External validation of our findings in other jurisdictions is needed.
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We provide an updated estimate of adult stroke event rates by age group, sex, and stroke type using Canadian administrative data. In the 2017-2018 fiscal year, there were an estimated 81,781 hospital or emergency department visits for stroke events in Canada, excluding Quebec. Our findings show that overall, the event rate of stroke is similar between women and men. There were slight differences in stroke event rate at various ages by sex and stroke type and emerging patterns warrant attention in future studies. Our findings emphasize the importance of continuous surveillance to monitor the epidemiology of stroke in Canada.
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BACKGROUND: Although age-standardized stroke occurrence has been decreasing, the absolute number of stroke events globally, and in Canada, is increasing. Stroke surveillance is necessary for health services planning, informing research design, and public health messaging. We used administrative data to estimate the number of stroke events resulting in hospital or emergency department presentation across Canada in the 2017-18 fiscal year. METHODS: Hospitalization data were obtained from the Canadian Institute for Health Information (CIHI) Discharge Abstract Database and the Ministry of Health and Social Services in Quebec. Emergency department data were obtained from the CIHI National Ambulatory Care Reporting System (Alberta and Ontario). Stroke events were identified using ICD-10 coding. Data were linked into episodes of care to account for readmissions and interfacility transfers. Projections for emergency department visits for provinces/territories outside of Alberta and Ontario were generated based upon age and sex-standardized estimates from Alberta and Ontario. RESULTS: In the 2017-18 fiscal year, there were 108,707 stroke events resulting in hospital or emergency department presentation across the country. This was made up of 54,357 events resulting in hospital admission and 54,350 events resulting in only emergency department presentation. The events resulting in only emergency department presentation consisted of 25,941 events observed in Alberta and Ontario and a projection of 28,409 events across the rest of the country. CONCLUSIONS: We estimate a stroke event resulting in hospital or emergency department presentation occurs every 5 minutes in Canada.
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BACKGROUND: The Passive Surveillance Stroke Severity (PaSSV) Indicator was derived to estimate stroke severity from variables in administrative datasets but has not been externally validated. METHODS: We used linked administrative datasets to identify patients with first hospitalization for acute stroke between 2007-2018 in Alberta, Canada. We used the PaSSV indicator to estimate stroke severity. We used Cox proportional hazard models and evaluated the change in hazard ratios and model discrimination for 30-day and 1-year case fatality with and without PaSSV. Similar comparisons were made for 90-day home time thresholds using logistic regression. We also linked with a clinical registry to obtain National Institutes of Health Stroke Scale (NIHSS) and compared estimates from models without stroke severity, with PaSSV, and with NIHSS. RESULTS: There were 28,672 patients with acute stroke in the full sample. In comparison to no stroke severity, addition of PaSSV to the 30-day case fatality models resulted in improvement in model discrimination (C-statistic 0.72 [95%CI 0.71-0.73] to 0.80 [0.79-0.80]). After adjustment for PaSSV, admission to a comprehensive stroke center was associated with lower 30-day case fatality (adjusted hazard ratio changed from 1.03 [0.96-1.10] to 0.72 [0.67-0.77]). In the registry sample (N = 1328), model discrimination for 30-day case fatality improved with the inclusion of stroke severity. Results were similar for 1-year case fatality and home time outcomes. CONCLUSION: Addition of PaSSV improved model discrimination for case fatality and home time outcomes. The validity of PASSV in two Canadian provinces suggests that it is a useful tool for baseline risk adjustment in acute stroke.
Subject(s)
Stroke , Humans , Stroke/diagnosis , Stroke/epidemiology , Logistic Models , Hospitalization , Alberta/epidemiologyABSTRACT
OBJECTIVE: To examine whether the association of co-morbidity with mortality after acute stroke is influenced by stroke type, age, sex, or time since stroke. MATERIALS AND METHODS: We conducted a province-wide population-based study using linked administrative databases to identify all admissions for acute stroke between 2007-2018 in Alberta, Canada. We used Cox proportional hazard models to determine the association of severe co-morbidity based on the Charlson Co-morbidity Index with 1-year mortality after stroke, assessing for effect modification by stroke type, age, and sex, and with adjustment for estimated stroke severity, comprehensive stroke centre care, hypertension, atrial fibrillation, and year of study. We used a piecewise model to analyze the impact of co-morbidity across four time periods. RESULTS: We had 28,672 patients in our final cohort (87.8% ischemic stroke). The hazard of mortality with severe co-morbidity was higher for individuals with ischemic stroke (adjusted hazard ratio [aHR] 2.20, 95% CI 2.07-2.32) compared to those with intracerebral hemorrhage (aHR 1.70, 95% CI 1.51-1.92; pint<0.001), and higher in individuals under age 75 (aHR 3.20, 95% CI 2.90-3.53) compared to age ≥75 (aHR 1.93, 95% CI 1.82-2.05, pint<0.001). There was no interaction by sex. The hazard ratio increased in a graded fashion at younger ages and was higher after the first 30 days of acute stroke. CONCLUSION: There was a stronger association between co-morbidity and mortality at younger age and in the subacute phase of stroke. Further research is needed to determine the reason for these findings and identify ways to improve outcomes among those with stroke and co-morbid conditions at young age.
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Knowledge about stroke and its management is growing rapidly and stroke systems of care must adapt to deliver evidence-based care. Quality improvement initiatives are essential for translating knowledge from clinical trials and recommendations in guidelines into routine clinical practice. This review focuses on issues central to the measurement of the quality of stroke care, including selection and definition of quality measures, identification of the eligible patient cohorts, optimization of data quality, and considerations for data analysis and interpretation.
Subject(s)
Quality Indicators, Health Care , Stroke , Humans , Quality Improvement , Stroke/drug therapy , Stroke/therapyABSTRACT
BACKGROUND: The frequency of readmissions after COVID-19 hospitalizations is uncertain, as is whether current readmission prediction equations are useful for discharge risk stratification of COVID-19 survivors or for comparing among hospitals. We sought to determine the frequency and predictors of death or unplanned readmission after a COVID-19 hospital discharge. METHODS: We conducted a retrospective cohort study of all adults (≥ 18 yr) who were discharged alive from hospital after a nonpsychiatric, nonobstetric, acute care admission for COVID-19 between Jan. 1, 2020, and Sept. 30, 2021, in Alberta and Ontario. RESULTS: Of 843 737 individuals who tested positive for SARS-CoV-2 by reverse transcription polymerase chain reaction during the study period, 46 412 (5.5%) were adults admitted to hospital within 14 days of their positive test. Of these, 8496 died in hospital and 34 846 were discharged alive (30 336 discharged after an index admission of ≤ 30 d and 4510 discharged after an admission > 30 d). One in 9 discharged patients died or were readmitted within 30 days after discharge (3173 [10.5%] of those with stay ≤ 30 d and 579 [12.8%] of those with stay > 30 d). The LACE score (length of stay, acuity, Charlson Comorbidity Index and number of emergency visits in previous 6 months) for predicting urgent readmission or death within 30 days had a c-statistic of 0.60 in Alberta and 0.61 in Ontario; inclusion of sex, discharge locale, deprivation index and teaching hospital status in the model improved the c-statistic to 0.73. INTERPRETATION: Death or readmission after discharge from a COVID-19 hospitalization is common and had a similar frequency in Alberta and Ontario. Risk stratification and interinstitutional comparisons of outcomes after hospital admission for COVID-19 should include sex, discharge locale and socioeconomic measures, in addition to the LACE variables.
Subject(s)
COVID-19 , Patient Readmission , Adult , Alberta/epidemiology , COVID-19/epidemiology , COVID-19/therapy , Comorbidity , Emergency Service, Hospital , Hospitalization , Humans , Length of Stay , Ontario/epidemiology , Patient Discharge , Retrospective Studies , Risk Factors , SARS-CoV-2ABSTRACT
PURPOSE: Data extraction from radiology free-text reports is time consuming when performed manually. Recently, more automated extraction methods using natural language processing (NLP) are proposed. A previously developed rule-based NLP algorithm showed promise in its ability to extract stroke-related data from radiology reports. We aimed to externally validate the accuracy of CHARTextract, a rule-based NLP algorithm, to extract stroke-related data from free-text radiology reports. METHODS: Free-text reports of CT angiography (CTA) and perfusion (CTP) studies of consecutive patients with acute ischemic stroke admitted to a regional stroke center for endovascular thrombectomy were analyzed from January 2015 to 2021. Stroke-related variables were manually extracted as reference standard from clinical reports, including proximal and distal anterior circulation occlusion, posterior circulation occlusion, presence of ischemia or hemorrhage, Alberta stroke program early CT score (ASPECTS), and collateral status. These variables were simultaneously extracted using a rule-based NLP algorithm. The NLP algorithm's accuracy, specificity, sensitivity, positive predictive value (PPV), and negative predictive value (NPV) were assessed. RESULTS: The NLP algorithm's accuracy was > 90% for identifying distal anterior occlusion, posterior circulation occlusion, hemorrhage, and ASPECTS. Accuracy was 85%, 74%, and 79% for proximal anterior circulation occlusion, presence of ischemia, and collateral status respectively. The algorithm confirmed the absence of variables from radiology reports with an 87-100% accuracy. CONCLUSIONS: Rule-based NLP has a moderate to good performance for stroke-related data extraction from free-text imaging reports. The algorithm's accuracy was affected by inconsistent report styles and lexicon among reporting radiologists.
Subject(s)
Ischemic Stroke , Stroke , Humans , Natural Language Processing , Stroke/diagnostic imaging , Algorithms , AutomationABSTRACT
We examined the accuracy of International Classification of Disease 10th iteration (ICD-10) diagnosis codes within Canadian administrative data in identifying cerebral venous thrombosis (CVT). Of 289 confirmed cases of CVT admitted to our comprehensive stroke center between 2008 and 2018, 239/289 were new diagnoses and 204/239 were acute events with only 75/204 representing symptomatic CVTs not provoked by trauma or structural processes. Using ICD-10 codes in any position, sensitivity was 39.1% and positive predictive value was 94.2% for patients with a current or history of CVT and 84.0% and 52.5% for acute and symptomatic CVTs not provoked by trauma or structural processes.
Subject(s)
Intracranial Thrombosis , Venous Thrombosis , Humans , International Classification of Diseases , Canada/epidemiology , Intracranial Thrombosis/diagnosis , Predictive Value of Tests , Venous Thrombosis/diagnosisABSTRACT
BACKGROUND AND PURPOSE: Studies of carotid endarterectomy (CEA) require stratification by symptomatic vs asymptomatic status because of marked differences in benefits and harms. In administrative datasets, this classification has been done using hospital discharge diagnosis codes of uncertain accuracy. This study aims to develop and evaluate algorithms for classifying symptomatic status using hospital discharge and physician claims data. METHODS: A single center's administrative database was used to assemble a retrospective cohort of participants with CEA. Symptomatic status was ascertained by chart review prior to linkage with physician claims and hospital discharge data. Accuracy of rule-based classification by discharge diagnosis codes was measured by sensitivity and specificity. Elastic net logistic regression and random forest models combining physician claims and discharge data were generated from the training set and assessed in a test set of final year participants. Models were compared to rule-based classification using sensitivity at fixed specificity. RESULTS: We identified 971 participants undergoing CEA at the Vancouver General Hospital (Vancouver, Canada) between January 1, 2008 and December 31, 2016. Of these, 729 met inclusion/exclusion criteria (n = 615 training, n = 114 test). Classification of symptomatic status using hospital discharge diagnosis codes was 32.8% (95% CI 29-37%) sensitive and 98.6% specific (96-100%). At matched 98.6% specificity, models that incorporated physician claims data were significantly more sensitive: elastic net 69.4% (59-82%) and random forest 78.8% (69-88%). CONCLUSION: Discharge diagnoses were specific but insensitive for the classification of CEA symptomatic status. Elastic net and random forest machine learning algorithms that included physician claims data were sensitive and specific, and are likely an improvement over current state of classification by discharge diagnosis alone.