High-Intensity Aphasia Therapy Is Cost-Effective in People With Poststroke Aphasia: Evidence From the COMPARE Trial.

BACKGROUND: Evidence from systematic reviews confirms that speech and language interventions for people with aphasia during the chronic phase after stroke (>6 months) improve word retrieval, functional communication, and communication-related quality of life. However, there is limited evidence of their cost-effectiveness. We aimed to estimate the cost per quality-adjusted life year gained from 2 speech and language therapies compared with usual care in people with aphasia during the chronic phase (median, 2.9 years) after stroke. METHODS: A 3-arm, randomized controlled trial compared constraint-induced aphasia therapy plus (CIAT-Plus) and multimodality aphasia therapy (M-MAT) with usual care in 216 people with chronic aphasia. Participants were administered a standardized questionnaire before intervention and at 12 weeks after the 2-week intervention/control period to ascertain health service utilization, employment changes, and informal caregiver burden. Unit prices from Australian sources were used to estimate costs in 2020. Quality-adjusted life years were estimated using responses to the EuroQol-5 Dimension-3 Level questionnaire. To test uncertainty around the differences in costs and outcomes between groups, bootstrapping was used with the cohorts resampled 1000 times. RESULTS: Overall 201/216 participants were included (mean age, 63 years, 29% moderate or severe aphasia, 61 usual care, 70 CIAT-Plus, 70 M-MAT). There were no statistically significant differences in mean total costs ($13 797 usual care, $17 478 CIAT-Plus, $11 113 M-MAT) and quality-adjusted life years (0.19 usual care, 0.20 CIAT-Plus, 0.20 M-MAT) between groups. In bootstrapped analysis of CIAT-Plus, 21.5% of iterations were likely to result in better outcomes and be cost saving (dominant) compared with usual care. In contrast, 72.4% of iterations were more favorable for M-MAT than usual care. CONCLUSIONS: We observed that both treatments, but especially M-MAT, may result in better outcomes at an acceptable additional cost, or potentially with cost savings. These findings are relevant in advocating for the use of these therapies for chronic aphasia after stroke.

High-Intensity Aphasia Intervention Is Minimally Fatiguing in Chronic Aphasia: An Analysis of Participant Self-Ratings From a Large Randomized Controlled Trial.

BACKGROUND: High-intensity therapy is recommended in current treatment guidelines for chronic poststroke aphasia. Yet, little is known about fatigue levels induced by treatment, which could interfere with rehabilitation outcomes. We analyzed fatigue experienced by people with chronic aphasia (>6 months) during high-dose interventions at 2 intensities. METHODS: A retrospective observational analysis was conducted on self-rated fatigue levels of people with chronic aphasia (N=173) collected during a previously published large randomized controlled trial of 2 treatments: constraint-induced aphasia therapy plus and multi-modality aphasia therapy. Interventions were administered at a higher intensity (30 hours over 2 weeks) or lower intensity (30 hours over 5 weeks). Participants rated their fatigue on an 11-point scale before and after each day of therapy. Data were analyzed using Bayesian ordinal multilevel models. Specifically, we considered changes in self-rated participant fatigue across a therapy day and over the intervention period. RESULTS: Data from 144 participants was analyzed. Participants were English speakers from Australia or New Zealand (mean age, 62 [range, 18-88] years) with 102 men and 42 women. Most had mild (n=115) or moderate (n=52) poststroke aphasia. Median ratings of the level of fatigue by people with aphasia were low (1 on a 0-10-point scale) at the beginning of the day. Ratings increased slightly (+1.0) each day after intervention, with marginally lower increases in the lower intensity schedule. There was no evidence of accumulating fatigue over the 2- or 5-week interventions. CONCLUSIONS: Findings suggest that intensive intervention was not associated with large increases in fatigue for people with chronic aphasia enrolled in the COMPARE trial (Constraint-Induced or Multimodality Personalised Aphasia Rehabilitation). Fatigue did not change across the course of the intervention. This study provides evidence that intensive treatment was minimally fatiguing for stroke survivors with chronic aphasia, suggesting that fatigue is not a barrier to high-intensity treatment.

Cost-Effectiveness of a Government Policy to Incentivise Chronic Disease Management following Stroke: A Modelling Study.

INTRODUCTION: Little is known about the cost-effectiveness of government policies that support primary care physicians to provide comprehensive chronic disease management (CDM). This paper aimed to estimate the potential cost-effectiveness of CDM policies over a lifetime for long-time survivors of stroke. METHODS: A Markov model, using three health states (stable, hospitalised, dead), was developed to simulate the costs and benefits of CDM policies over 30 years (with 1-year cycles). Transition probabilities and costs from a health system perspective were obtained from the linkage of data between the Australian Stroke Clinical Registry (cohort n = 12,368, 42% female, median age 70 years, 45% had CDM claims) and government-held hospital, Medicare, and pharmaceutical claims datasets. Quality-adjusted life years (QALYs) were obtained from a comparable cohort (n = 512, 34% female, median age 69.6 years, 52% had CDM claims) linked with Medicare claims and death data. A 3% discount rate was applied to costs in Australian dollars (AUD, 2016) and QALYs beyond 12 months. Probabilistic sensitivity analyses were used to understand uncertainty. RESULTS: Per-person average total lifetime costs were AUD 142,939 and 8.97 QALYs for those with a claim, and AUD 103,889 and 8.98 QALYs for those without a claim. This indicates that these CDM policies were costlier without improving QALYs. The probability of cost-effectiveness of CDM policies was 26.1%, at a willingness-to-pay threshold of AUD 50,000/QALY. CONCLUSION: CDM policies, designed to encourage comprehensive care, are unlikely to be cost-effective for stroke compared to care without CDM. Further research to understand how to deliver such care cost-effectively is needed.

Cost-Effectiveness of an Individualised Management Program after Stroke: A Trial-Based Economic Evaluation.

INTRODUCTION: Evidence on the cost-effectiveness of comprehensive post-stroke programs is limited. We assessed the cost-effectiveness of an individualised management program (IMP) for stroke or transient ischaemic attack (TIA). METHODS: A cost-utility analysis alongside a randomised controlled trial with a 24-month follow-up, from both societal and health system perspectives, was conducted. Adults with stroke/TIA discharged from hospitals were randomised by primary care practice to receive either usual care (UC) or an IMP in addition to UC (intervention). An IMP included stroke-specific nurse-led education and a specialist review of care plans at baseline, 3 months, and 12 months, and telephone reviews by nurses at 6 months and 18 months. Costs were expressed in 2021 Australian dollars (AUD). Costs and quality-adjusted life years (QALYs) beyond 12 months were discounted by 5%. The probability of cost-effectiveness of the intervention was determined by quantifying 10,000 bootstrapped iterations of incremental costs and QALYs below the threshold of AUD 50,000/QALY. RESULTS: Among the 502 participants (65% male, median age 69 years), 251 (50%) were in the intervention group. From a health system perspective, the incremental cost per QALY gained was AUD 53,175 in the intervention compared to the UC group, and the intervention was cost-effective in 46.7% of iterations. From a societal perspective, the intervention was dominant in 52.7% of iterations, with mean per-person costs of AUD 49,045 and 1.352 QALYs compared to mean per-person costs of AUD 51,394 and 1.324 QALYs in the UC group. The probability of the cost-effectiveness of the intervention, from a societal perspective, was 60.5%. CONCLUSIONS: Care for people with stroke/TIA using an IMP was cost-effective from a societal perspective over 24 months. Economic evaluations of prevention programs need sufficient time horizons and consideration of costs beyond direct healthcare utilisation to demonstrate their value to society.

Age and sex disparities in cardiovascular risk factor management prior to stroke: Linked registry and general practice data.

INTRODUCTION: There is limited evidence about the management of cardiovascular risk factors within 12 months before stroke/transient ischaemic attack (TIA) in Australian general practices. We evaluated whether age and sex disparities in cardiovascular risk factor management for primary prevention exist in general practice. METHODS: A retrospective cohort study using data from the Australian Stroke Clinical Registry (2014-2018) linked with general practice data from three primary health networks in Victoria, Australia. We included adults who had ≥2 encounters with a general practitioner within 12 months immediately before the first stroke/TIA. Cardiovascular risk factor management within 12 months before stroke/TIA was evaluated in terms of: assessment of risk factors (blood pressure [BP], serum lipids, blood glucose, body weight); prescription of prevention medications (BP, lipid-, glucose-lowering, antithrombotic agents); and attainment of risk factor targets. RESULTS: Of 2,880 patients included (median age 76.5 years, 48.4% women), 80.9% were assessed for BP, 49.9% serum lipids, 46.8% blood glucose, and 39.3% body weight. Compared to patients aged 65-84 years, those aged <65 or ≥85 years were less often assessed for risk factors, with women aged ≥85 years assessed for significantly fewer risk factors than their male counterparts. The most prescribed prevention medications were BP-lowering (64.9%) and lipid-lowering agents (42.0%). There were significant sex differences among those aged <65 years (34.7% women vs. 40.2% men) and ≥85 years (34.0% women vs. 44.3% men) for lipid-lowering agents. Risk factor target attainment was generally poorer in men than women, especially among those aged <65 years. CONCLUSION: Age-sex disparity exists in risk factor management for primary prevention in general practice, and this was more pronounced among younger patients and older women.

Risk Factors Associated with Major Adverse Cardiovascular Events after Ischemic Stroke: A Linked Registry Study.

INTRODUCTION: Survivors of stroke are at risk of experiencing subsequent major adverse cardiovascular events (MACE). We aimed to determine the incidence of, and risk factors for, MACE after first-ever ischemic stroke, by age group (18-64 years vs. ≥65 years). METHODS: Observational cohort study using patient-level data from the Australian Stroke Clinical Registry (2009-2013), linked with hospital administrative data. We included adults with first-ever ischemic stroke who had no previous acute cardiovascular admissions and followed these patients for 2 years post-discharge, or until the first post-stroke MACE event. A Fine-Gray sub-distribution hazard model, accounting for the competing risk of non-cardiovascular death, was used to determine factors for incident post-stroke MACE. RESULTS: Among 5,994 patients with a first-ever ischemic stroke (median age 73 years, 45% female), 17% were admitted for MACE within 2 years (129 events per 1,000 person-years). The median time to first post-stroke MACE was 117 days (89 days if aged <65 years vs. 126 days if aged ≥65 years; p = 0.025). Among patients aged 18-64 years, receiving intravenous thrombolysis (sub-distribution hazard ratio [SHR] 0.51 [95% CI, 0.28-0.92]) or being discharged to inpatient rehabilitation (SHR 0.65 [95% CI, 0.46-0.92]) were associated with a reduced incidence of post-stroke MACE. In those aged ≥65 years, being unable to walk on admission (SHR 1.33 [95% CI 1.15-1.54]), and history of smoking (SHR 1.40 [95% CI 1.14-1.71]) or atrial fibrillation (SHR 1.31 [95% CI 1.14-1.51]) were associated with an increased incidence of post-stroke MACE. Acute management in a large hospital (>300 beds) for the initial stroke event was associated with reduced incidence of post-stroke MACE, irrespective of age group. CONCLUSIONS: MACE is common within 2 years of stroke, with most events occurring within the first year. We have identified important factors to consider when designing interventions to prevent MACE after stroke, particularly among those aged <65 years.

Receipt of Mental Health Treatment in People Living With Stroke: Associated Factors and Long-Term Outcomes.

BACKGROUND: Untreated poststroke mood problems may influence long-term outcomes. We aimed to investigate factors associated with receiving mental health treatment following stroke and impacts on long-term outcomes. METHODS: Observational cohort study derived from the Australian Stroke Clinical Registry (AuSCR; Queensland and Victorian registrants: 2012-2016) linked with hospital, primary care billing and pharmaceutical dispensing claims data. Data from registrants who completed the AuSCR 3 to 6 month follow-up survey containing a question on anxiety/depression were analyzed. We assessed exposures at 6 to 18 months and outcomes at 18 to 30 months. Factors associated with receiving treatment were determined using staged multivariable multilevel logistic regression models. Cox proportional hazards regression models were used to assess the impact of treatment on outcomes. RESULTS: Among 7214 eligible individuals, 39% reported anxiety/depression at 3 to 6 months following stroke. Of these, 54% received treatment (88% antidepressant medication). Notable factors associated with any mental health treatment receipt included prestroke psychological support (odds ratio [OR], 1.80 [95% CI, 1.37-2.38]) or medication (OR, 17.58 [95% CI, 15.05-20.55]), self-reported anxiety/depression (OR, 2.55 [95% CI, 2.24-2.90]), younger age (OR, 0.98 [95% CI, 0.97-0.98]), and being female (OR, 1.30 [95% CI, 1.13-1.48]). Those who required interpreter services (OR, 0.49 [95% CI, 0.25-0.95]) used a health benefits card (OR, 0.73 [95% CI, 0.59-0.92]) or had continuity of primary care visits (ie, with a consistent physician; OR, 0.78 [95% CI, 0.62-0.99]) were less likely to access mental health services. Among those who reported anxiety/depression, those who received mental health treatment had an increased risk of presenting to hospital (hazard ratio, 1.06 [95% CI, 1.01-1.11]) but no difference in survival (hazard ratio, 0.86 [95% CI, 0.58-1.27]). CONCLUSIONS: Nearly half of the people living with mood problems following stroke did not receive mental health treatment. We have highlighted subgroups who may benefit from targeted mood screening and factors that may improve treatment access.

Comparison of Stroke Care Costs in Urban and Nonurban Hospitals and Its Association With Outcomes in New Zealand: A Nationwide Economic Evaluation.

BACKGROUND: Although geographical differences in treatment and outcomes after stroke have been described, we lack evidence on differences in the costs of treatment between urban and nonurban regions. Additionally, it is unclear whether greater costs in one setting are justified given the outcomes achieved. We aimed to compare costs and quality-adjusted life years in people with stroke admitted to urban and nonurban hospitals in New Zealand. METHODS: Observational study of patients with stroke admitted to the 28 New Zealand acute stroke hospitals (10 in urban areas) recruited between May and October 2018. Data were collected up to 12 months poststroke including treatments in hospital, inpatient rehabilitation, other health service utilization, aged residential care, productivity, and health-related quality of life. Costs in New Zealand dollars were estimated from a societal perspective and assigned to the initial hospital that patients presented to. Unit prices for 2018 were obtained from government and hospital sources. Multivariable regression analyses were conducted when assessing differences between groups. RESULTS: Of 1510 patients (median age 78 years, 48% female), 607 presented to nonurban and 903 to urban hospitals. Mean hospital costs were greater in urban than nonurban hospitals ($13 191 versus $11 635, P=0.002), as were total costs to 12 months ($22 381 versus $17 217, P<0.001) and quality-adjusted life years to 12 months (0.54 versus 0.46, P<0.001). Differences in costs and quality-adjusted life years remained between groups after adjustment. Depending on the covariates included, costs per additional quality-adjusted life year in the urban hospitals compared to the nonurban hospitals ranged from $65 038 (unadjusted) to $136 125 (covariates: age, sex, prestroke disability, stroke type, severity, and ethnicity). CONCLUSIONS: Better outcomes following initial presentation to urban hospitals were associated with greater costs compared to nonurban hospitals. These findings may inform greater targeted expenditure in some nonurban hospitals to improve access to treatment and optimize outcomes.

The Excess Costs of Hospitalization for Acute Stroke in People With Communication Impairment: A Stroke123 Data Linkage Substudy.

OBJECTIVE: To describe the costs of hospital care for acute stroke for patients with aphasia or dysarthria. DESIGN: Observational study from the Stroke123 project. SETTING: Data from patients admitted with stroke (2009-2013) from 22 hospitals in Queensland participating in the Australian Stroke Clinical Registry (AuSCR) were linked to administrative datasets. PARTICIPANTS: Communication impairments were identified using International Classification of Diseases, 10th Revision, Australian Modification codes. Overall, 1043 of 4195 (25%) patients were identified with aphasia (49% were women; median age 78 years; 83% with ischemic stroke), and 1005 (24%) with dysarthria (42% were women; median age 76 years; 85% with ischemic stroke). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Linked patient-level, hospital clinical costing related to the stroke, were adjusted to 2013/2014 Australian dollars (AU$, US$ conversion x 0.691) using recommended national price indices and multivariable regression analysis with clustering by hospital performed. RESULTS: Compared with patients without aphasia, the median hospital costs/patient were greater for those with aphasia for medical (aphasia AU$2273 vs AU$1727, P<.001), nursing (aphasia AU$3829 vs AU$2748, P<.001) and allied health services (aphasia AU$1138 vs AU$720, P<.001). Similarly, costs were greater for patients with dysarthria compared with those without dysarthria. Adjusted median total costs were AU$2882 greater for patients with aphasia compared with patients without aphasia (95% confidence interval, AU$1880-3884), and AU$843 greater for patients with dysarthria compared with those without dysarthria (95% confidence interval, AU$-301 to 1987). CONCLUSIONS: People with communication impairment after stroke incur greater hospital costs, in particular for medical, allied health, and nursing resources.

Does a History of Cancer Influence the Effectiveness of Statins on Outcomes After Stroke?

BACKGROUND: Evidence is growing on anticancer effects of statins. We investigated whether the effectiveness of treatment with statins after ischemic stroke on mortality is influenced by a history of cancer. METHODS: Analyses of 90-day survivors of ischemic stroke (2012-2016; 45 hospitals) using linked registry and administrative data. Dispense of statins within 90 days postdischarge was determined from pharmaceutical records. Participants were followed from 91 days postdischarge until death or June 30, 2018. History of cancer was determined from hospital data. Propensity score-adjusted Cox proportional hazards regression model was used to determine the association between being dispensed statins and survival. The influence of history of cancer on this association was assessed based on the concepts of (1) statistical interaction and (2) biological interaction using 3 indices: relative excess risk due to interaction>0, attributable proportion due to interaction >0, or synergy index >1. RESULTS: Among 9948 eligible participants (median age=72 years, 42% female), there were 1463 deaths. In adjusted analyses, there was no statistical interaction between being dispensed statins and history of cancer on mortality (P=0.156). However, being dispensed statins had a significant positive biological interaction with having a history of cancer on mortality: relative excess risk due to interaction, 2.80 (95% CI, 1.56-5.05), attributable proportion due to interaction, 0.45 (95% CI, 0.23-0.66), and synergy index, 2.14 (95% CI, 1.32-3.49). CONCLUSIONS: Treatment with statins after ischemic stroke may confer additional survival benefits for people who also have had cancer.

Results of the COMPARE trial of Constraint-induced or Multimodality Aphasia Therapy compared with usual care in chronic post-stroke aphasia.

BACKGROUND: While meta-analyses confirm treatment for chronic post-stroke aphasia is effective, a lack of comparative evidence for different interventions limits prescription accuracy. We investigated whether Constraint-Induced Aphasia Therapy Plus (CIAT-plus) and/or Multimodality Aphasia Therapy (M-MAT) provided greater therapeutic benefit compared with usual community care and were differentially effective according to baseline aphasia severity. METHODS: We conducted a three-arm, multicentre, parallel group, open-label, blinded endpoint, phase III, randomised-controlled trial. We stratified eligible participants by baseline aphasia on the Western Aphasia Battery-Revised Aphasia Quotient (WAB-R-AQ). Groups of three participants were randomly assigned (1:1:1) to 30 hours of CIAT-Plus or M-MAT or to usual care (UC). Primary outcome was change in aphasia severity (WAB-R-AQ) from baseline to therapy completion analysed in the intention-to-treat population. Secondary outcomes included word retrieval, connected speech, functional communication, multimodal communication, quality of life and costs. RESULTS: We analysed 201 participants (70 in CIAT-Plus, 70 in M-MAT and 61 in UC). Aphasia severity was not significantly different between groups at postintervention: 1.05 points (95% CI -0.78 to 2.88; p=0.36) UC group vs CIAT-Plus; 1.06 points (95% CI -0.78 to 2.89; p=0.36) UC group vs M-MAT; 0.004 points (95% CI -1.76 to 1.77; p=1.00) CIAT-Plus vs M-MAT. Word retrieval, functional communication and communication-related quality of life were significantly improved following CIAT-Plus and M-MAT. Word retrieval benefits were maintained at 12-week follow-up. CONCLUSIONS: CIAT-Plus and M-MAT were effective for word retrieval, functional communication, and quality of life, while UC was not. Future studies should explore predictive characteristics of responders and impacts of maintenance doses. TRIAL REGISTRATION NUMBER: ACTRN 2615000618550.

Real-World Effectiveness of Lipid-Lowering Medications on Outcomes after Stroke: Potential Implications of the New-User Design.

INTRODUCTION: Observational studies are increasingly being used to provide evidence on the real-world effectiveness of medications for preventing vascular diseases, such as stroke. We investigated whether the real-world effectiveness of treatment with lipid-lowering medications after ischemic stroke is affected by prevalent-user bias. METHODS: An observational cohort study of 90-day survivors of ischemic stroke using person-level data from the Australian Stroke Clinical Registry (2012-2016; 45 hospitals) linked to administrative (pharmaceutical, hospital, death) records. The use of, and adherence to (proportion of days covered <80% [poor adherence] vs. ≥80% [good adherence]), lipid-lowering medications within 90 days post-discharge was determined from pharmaceutical records. Users were further classified as prevalent (continuing) or new users, based on dispensing within 90 days prior to stroke. A propensity score-adjusted Cox regression was used to evaluate the effectiveness of lipid-lowering medications on outcomes (all-cause mortality, all-cause and cardiovascular disease readmission) within the subsequent year. Analyses were undertaken using prevalent-user (all users vs. nonusers) and new-user designs (new users vs. nonusers). RESULTS: Of 11,217 eligible patients (median age 72 years, 42% female), 9,294 (83%) used lipid-lowering medications within 90 days post-discharge, including 5,479 new users. In both prevalent-user and new-user designs, nonusers (vs. users) had significantly greater rates of mortality (hazard ratio [HR] 2.35, 95% CI: 1.89-2.92) or all-cause readmissions (HR 1.22, 95% CI: 1.05-1.40) but not cardiovascular disease readmission. In contrast, associations between having poor (vs. good) adherence on outcomes were stronger among new users than all users. Among new users, having poor adherence was associated with greater rates of mortality (HR 1.48, 95% CI: 1.12-1.96), all-cause readmission (HR 1.14, 95% CI: 1.02-1.27), and cardiovascular disease readmission (HR 1.20, 95% CI: 1.01-1.42). CONCLUSIONS: The real-world effectiveness of treatment with lipid-lowering medications after stroke is attenuated when evaluated based on prevalent-user rather than new-user design. These findings may have implications for designing studies on the real-world effectiveness of secondary prevention medications.

Treatment with Multiple Therapeutic Classes of Medication Is Associated with Survival after Stroke.

INTRODUCTION: Treatment with several therapeutic classes of medication is recommended for secondary prevention of stroke. We analyzed the associations between the number of classes of prevention medications supplied within 90 days after discharge for ischemic stroke (IS)/transient ischemic attack (TIA) and survival. METHODS: This is a retrospective cohort study of adults with first-ever IS/TIA (2010-2014) from the Australian Stroke Clinical Registry individually linked with data from national pharmaceutical and Medicare claims. Exposure was the number of classes of recommended medications, i.e., blood pressure-lowering, antithrombotic, or lipid-lowering agents, supplied to patients within 90 days after discharge for IS/TIA. The longitudinal association between the number of classes of medications and survival was evaluated with Cox proportional hazards regression models using the landmark approach. A landmark date of 90 days after hospital discharge was used to separate exposure and outcome periods, and only patients who survived until this date were included. RESULTS: Of 8,429 patients (43% female, median age 74 years, 80% IS), 607 (7%) died in the year following 90 days after discharge. Overall, 56% of patients were supplied all 3 classes of medications, 28% 2 classes of medications, 11% 1 class of medications, and 5% no class of medications. Compared to patients supplied all 3 medication classes, adjusted hazard ratios for all-cause mortality ranged from 1.43 (95% confidence interval [CI]: 1.18-1.72) in those supplied 2 medication classes to 2.04 (95% CI: 1.44-2.88) in those supplied with no medication class. DISCUSSION/CONCLUSION: Treatment with all 3 classes of guideline-recommended medications within 90 days after discharge was associated with better survival. Ongoing efforts are required to ensure optimal pharmacological intervention for secondary prevention of stroke.

Towards better reporting of the proportion of days covered method in cardiovascular medication adherence: A scoping review and new tool TEN-SPIDERS.

Although medication adherence is commonly measured in electronic datasets using the proportion of days covered (PDC), no standardized approach is used to calculate and report this measure. We conducted a scoping review to understand the approaches taken to calculate and report the PDC for cardiovascular medicines to develop improved guidance for researchers using this measure. After prespecifying methods in a registered protocol, we searched Ovid Medline, Embase, Scopus, CINAHL Plus and grey literature (1 July 2012 to 14 December 2020) for articles containing the terms "proportion of days covered" and "cardiovascular medicine", or synonyms and subject headings. Of the 523 articles identified, 316 were reviewed in full and 76 were included (93% observational studies; 47% from the USA; 2 grey literature articles). In 45 articles (59%), the PDC was measured from the first dispensing/claim date. Good adherence was defined as 80% PDC in 61 articles, 56% of which contained a rationale for selecting this threshold. The following parameters, important for deriving the PDC, were often not reported/unclear: switching (53%), early refills (45%), in-hospital supplies (45%), presupply (28%) and survival (7%). Of the 46 articles where dosing information was unavailable, 59% reported how doses were imputed. To improve the transparent and systematic reporting of the PDC, we propose the TEN-SPIDERS tool, covering the following PDC parameters: Threshold, Eligibility criteria, Numerator and denominator, Survival, Presupply, In-hospital supplies, Dosing, Early Refills, and Switching. Use of this tool will standardize reporting of the PDC to facilitate reliable comparisons of medication adherence estimates between studies.

The Allure of Big Data to Improve Stroke Outcomes: Review of Current Literature.

PURPOSE OF REVIEW: To critically appraise literature on recent advances and methods using "big data" to evaluate stroke outcomes and associated factors. RECENT FINDINGS: Recent big data studies provided new evidence on the incidence of stroke outcomes, and important emerging predictors of these outcomes. Main highlights included the identification of COVID-19 infection and exposure to a low-dose particulate matter as emerging predictors of mortality post-stroke. Demographic (age, sex) and geographical (rural vs. urban) disparities in outcomes were also identified. There was a surge in methodological (e.g., machine learning and validation) studies aimed at maximizing the efficiency of big data for improving the prediction of stroke outcomes. However, considerable delays remain between data generation and publication. Big data are driving rapid innovations in research of stroke outcomes, generating novel evidence for bridging practice gaps. Opportunity exists to harness big data to drive real-time improvements in stroke outcomes.

Quality of life after stroke: a longitudinal analysis of a cluster randomized trial.

PURPOSE: Health-related quality of life (QoL) is poor after stroke, but may be improved with comprehensive care plans. We aimed to determine the effects of an individualized management program on QoL in people with stroke or transient ischemic attack (TIA), describe changes in QoL over time, and identify variables associated with QoL. METHODS: This was a multicenter, cluster randomized controlled trial with blinded assessment of outcomes and intention-to-treat analysis. Patients with stroke or TIA aged ≥ 18 years were randomized by general practice to receive usual care or an intervention comprising a tailored chronic disease management plan and education. QoL was assessed at baseline and 3, 12, and 24 months after baseline using the Assessment of Quality of Life instrument. Patient responses were converted to utility scores ranging from - 0.04 (worse than death) to 1.00 (good health). Mixed-effects models were used for analyses. RESULTS: Among 563 participants recruited (mean age 68.4 years, 64.5% male), median utility scores ranged from 0.700 to 0.772 at different time points, with no difference observed between intervention and usual care groups. QoL improved significantly from baseline to 3 months (ß = 0.019; P = 0.015) and 12 months (ß = 0.033; P < 0.001), but not from baseline to 24 months (ß = 0.013; P = 0.140) in both groups combined. Older age, females, lower educational attainment, greater handicap, anxiety and depression were longitudinally associated with poor QoL. CONCLUSION: An individualized management program did not improve QoL over 24 months. Those who are older, female, with lower educational attainment, greater anxiety, depression and handicap may require greater support. CLINICAL TRIAL REGISTRATION: https://www.anzctr.org.au . Unique identifier: ACTRN12608000166370.

Utility of the Hospital Frailty Risk Score Derived From Administrative Data and the Association With Stroke Outcomes.

Background and Purpose: Conditions associated with frailty are common in people experiencing stroke and may explain differences in outcomes. We assessed associations between a published, generic frailty risk score, derived from administrative data, and patient outcomes following stroke/transient ischemic attack; and its accuracy for stroke in predicting mortality compared with other measures of clinical status using coded data. Methods: Patient-level data from the Australian Stroke Clinical Registry (2009­2013) were linked with hospital admissions data. We used International Statistical Classification of Diseases and Related Health Problems, Tenth Revision codes with a 5-year look-back period to calculate the Hospital Frailty Risk Score (termed Frailty Score hereafter) and summarized results into 4 groups: no-risk (0), low-risk (1­5), intermediate-risk (5­15), and high-risk (>15). Multilevel models, accounting for hospital clustering, were used to assess associations between the Frailty Score and outcomes, including mortality (Cox regression) and readmissions up to 90 days, prolonged acute length of stay (>20 days; logistic regression), and health-related quality of life at 90 to 180 days (quantile regression). The performance of the Frailty Score was then compared with the Charlson and Elixhauser Indices using multiple tests (eg, C statistics) for predicting 30-day mortality. Models were adjusted for covariates including sociodemographics and stroke-related factors. Results: Among 15 468 adult patients, 15% died ≤90 days. The frailty scores were 9% no risk; 23% low, 45% intermediate, and 22% high. A 1-point increase in frailty (continuous variable) was associated with greater length of stay (ORadjusted, 1.05 [95% CI, 1.04 to 1.06), 90-day mortality (HRadjusted, 1.04 [95% CI, 1.03 to 1.05]), readmissions (ORadjusted, 1.02 [95% CI, 1.02 to 1.03]; and worse health-related quality of life (median difference, −0.010 [95% CI −0.012 to −0.010]). Adjusting for the Frailty Score provided a slightly better explanation of 30-day mortality (eg, larger C statistics) compared with other indices. Conclusions: Greater frailty was associated with worse outcomes following stroke/transient ischemic attack. The Frailty Score provides equivalent precision compared with the Charlson and Elixhauser indices for assessing risk-adjusted outcomes following stroke/transient ischemic attack.

Greater Adherence to Secondary Prevention Medications Improves Survival After Stroke or Transient Ischemic Attack: A Linked Registry Study.

Background and Purpose: Although a target of 80% medication adherence is commonly cited, it is unclear whether greater adherence improves survival after stroke or transient ischemic attack (TIA). We investigated associations between medication adherence during the first year postdischarge, and mortality up to 3 years, to provide evidence-based targets for medication adherence. Methods: Retrospective cohort study of 1-year survivors of first-ever stroke or TIA, aged ≥18 years, from the Australian Stroke Clinical Registry (July 2010­June 2014) linked with nationwide prescription refill and mortality data (until August 2017). Adherence to antihypertensive agents, statins, and nonaspirin antithrombotic medications was based on the proportion of days covered from discharge until 1 year. Cox regression with restricted cubic splines was used to investigate nonlinear relationships between medication adherence and all-cause mortality (to 3 years postdischarge). Models were adjusted for age, sex, socioeconomic position, stroke factors, primary care factors, and concomitant medication use. Results: Among 8363 one-year survivors of first-ever stroke or TIA (44% aged ≥75 years, 44% female, 18% TIA), 75% were supplied antihypertensive agents. In patients without intracerebral hemorrhage (N=7446), 84% were supplied statins, and 65% were supplied nonaspirin antithrombotic medications. Median adherence was ≈90% for each medication group. Between 1% and 100% adherence, greater adherence to statins or antihypertensive agents, but not nonaspirin antithrombotic agents, was associated with improved survival. When restricted to linear regions above 60% adherence, each 10% increase in adherence was associated with a reduction in all-cause mortality of 13% for antihypertensive agents (hazard ratio, 0.87 [95% CI, 0.81­0.95]), 13% for statins (hazard ratio, 0.87 [95% CI, 0.80­0.95]), and 15% for nonaspirin antithrombotic agents (hazard ratio, 0.85 [95% CI, 0.79­0.93]). Conclusions: Greater levels of medication adherence after stroke or TIA are associated with improved survival, even among patients with near-perfect adherence. Interventions to improve medication adherence are needed to maximize survival poststroke.

Stroke systems of care in high-income countries: what is optimal?

Stroke is a complex, time-sensitive, medical emergency that requires well functioning systems of care to optimise treatment and improve patient outcomes. Education and training campaigns are needed to improve both the recognition of stroke among the general public and the response of emergency medical services. Specialised stroke ambulances (mobile stroke units) have been piloted in many cities to speed up the diagnosis, triage, and emergency treatment of people with acute stroke symptoms. Hospital-based interdisciplinary stroke units remain the central feature of a modern stroke service. Many have now developed a role in the very early phase (hyperacute units) plus outreach for patients who return home (early supported discharge services). Different levels (comprehensive and primary) of stroke centre and telemedicine networks have been developed to coordinate the various service components with specialist investigations and interventions including rehabilitation. Major challenges include the harmonisation of resources for stroke across the whole patient journey (including the rapid, accurate triage of patients who require highly specialised treatment in comprehensive stroke centres) and the development of technology to improve communication across different parts of a service.

Assuming one dose per day yields a similar estimate of medication adherence in patients with stroke: An exploratory analysis using linked registry data.

PURPOSE: Prescribed daily dose (PDD), the number of doses prescribed to be taken per day, is used to calculate medication adherence using pharmacy claims data. PDD can be substituted by (i) one dose per day (1DD), (ii) an estimate based on the 75th percentile of days taken by patients to refill a script (PDD75 ) or (iii) the World Health Organization's defined daily dose (DDD). We aimed to compare these approaches for estimating the duration covered by medications and whether this affects calculated 1-year adherence to antihypertensive medications post-stroke. METHODS: We conducted a retrospective review of prospective cohort data from the ongoing Australian Stroke Clinical Registry linked with pharmacy claims data. Adherence was calculated as the proportion of days covered (PDC) for 1DD, PDD75 and DDD. Differences were assessed using Wilcoxon rank-sum tests. RESULTS: Among 12 628 eligible patients with stroke, 10 057 (80%) were prescribed antihypertensive medications in the year after hospital discharge (78.2% aged ≥65 years, 45.2% female). Overall, the 75th percentile of patient time until next medication refill was 39 days. The greatest variations in dose regimens, estimated using person- and dose-level refill times, were for beta blockers (11.4% taking two tablets/day). There were comparable levels of adherence between 1DD and the PDD75 (median PDC 91.0% vs 91.2%; P = 0.70), but adherence was slightly higher using DDD (92.3%; both P < 0.001). However, this would represent a clinically nonsignificant difference. CONCLUSION: Adherence to antihypertensive medications shows similar estimates across standard measures of dosage in patients during the first year after an acute stroke.