Access to inpatient mood management services after stroke in Australian acute and rehabilitation hospitals.

OBJECTIVE: Post-stroke mental health impairments are common, but under-assessed and under-treated. We aim to describe trends in the provision of mood management to patients with stroke, and describe factors associated with adoption of national mood management recommendations for stroke within Australian hospitals. DESIGN: Secondary analysis of cross-sectional data from the biennial Stroke Foundation Audit Program. SETTING: Participating acute (2011-2021) and rehabilitation hospitals (2012-2020) in Australia. PARTICIPANTS: In the acute audit, 22,937 stroke cases were included from 133 hospitals. In the rehabilitation audit, 15,891 stroke cases were included from 127 hospitals. MAIN MEASURES: Hospital- and patient-level mood management processes. RESULTS: Among 133 acute hospitals (22,937 stroke episodes), improvements were made between 2011 and 2021 in utilization of mood screening (17% [2011], 33% [2021]; p < 0.001) and access to psychologists during hospital stay (18% [2011], 45% [2021]; p < 0.001). There was no change in access to a psychologist among those with a mood impairment (p = 0.34). Among 127 rehabilitation hospitals (15,891 stroke episodes) improvements were observed for mood screening (35% [2012], 61% [2020]; p < 0.001), and access to a psychologist during hospital stay (38% [2012], 68% [2020]; p < 0.001) and among those with a mood-impairment (30% [2012], 50% [2020]; p < 0.001). Factors associated with receiving mood management processes included: younger age, not requiring an interpreter and longer length of stay. CONCLUSIONS: Adherence to mood management recommendations has improved over 10 years within Australian hospitals. Those aged over 65, requiring an interpreter, or with shorter hospital stays are at risk of missing out on appropriate mood management.

Cost-effectiveness of a government policy to incentivise chronic disease management following stroke: a modelling study.

BACKGROUND: Little is known about the cost-effectiveness of government policies that support primary care physicians to provide comprehensive chronic disease management (CDM). AIMS: To estimate the potential cost-effectiveness of CDM policies, over a lifetime, in 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 a claim) 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 a claim) 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 AUD142,939 and 8.97 QALYs for those with a claim, and AUD103,889 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 was 26.1%, at a willingness-to-pay threshold of AUD50,000/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 in a cost-effective manner is needed.

In Search of a Gold Standard Tool for Assessing Knowledge of Stroke: A Systematic Review.

BACKGROUND: Knowledge of stroke is essential to empower people to reduce their risk of these events. However, valid tools are required for accurate and reliable measurement of stroke knowledge. We aimed to systematically review contemporary stroke knowledge assessment tools and appraise their content validity, feasibility, and measurement properties. METHODS: The protocol was registered in PROSPERO (CRD42023403566). Electronic databases (MEDLINE, PsycInfo, CINAHL, Embase, Scopus, Web of Science) were searched to identify published articles (1 January 2015-1 March 2023), in which stroke knowledge was assessed using a validated tool. Two reviewers independently screened titles and abstracts prior to undertaking full-text review. COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) methods guided the appraisal of content validity (relevance, comprehensiveness, comprehensibility), feasibility, and measurement properties. RESULTS: After removing duplicates, the titles and abstracts of 718 articles were screened; 323 reviewed in full; with 42 included (N = 23 unique stroke knowledge tools). For content validity, all tools were relevant, two were comprehensive, and seven were comprehensible. Validation metrics were reported for internal consistency (n = 20 tools), construct validity (n = 17 tools), cross-cultural validity (n = 15 tools), responsiveness (n = 9 tools), reliability (n = 7 tools), structural validity (n = 3 tools), and measurement error (n = 1 tool). The Stroke Knowledge Test met all content validity criteria, with validation data for six measurement properties (n = 3 rated "Sufficient"). CONCLUSION: Assessment of stroke knowledge is not standardised and many tools lacked validated content or measurement properties. The Stroke Knowledge Test was the most comprehensive but requires updating and further validation for endorsement as a gold standard.

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.

Factors Associated With Transition From Community to Permanent Residential Aged Care Following Stroke: A Linked Registry Data Study.

BACKGROUND: Understanding factors that influence the transition to permanent residential aged care following a stroke or transient ischemic attack may inform strategies to support people to live at home longer. We aimed to identify the demographic, clinical, and system factors that may influence the transition from living in the community to permanent residential care in the 6 to 18 months following stroke/transient ischemic attack. METHODS: Linked data cohort analysis of adults from Queensland and Victoria aged ≥65 years and registered in the Australian Stroke Clinical Registry (2012-2016) with a clinical diagnosis of stroke/transient ischemic attack and living in the community in the first 6 months post-hospital discharge. Participant data were linked with primary care, pharmaceutical, aged care, death, and hospital data. Multivariable survival analysis was performed to determine demographic, clinical, and system factors associated with the transition to permanent residential care in the 6 to 18 months following stroke, with death modeled as a competing risk. RESULTS: Of 11 176 included registrants (median age, 77.2 years; 44% female), 520 (5%) transitioned to permanent residential care between 6 and 18 months. Factors most associated with transition included the history of urinary tract infections (subhazard ratio [SHR], 1.41 [95% CI, 1.16-1.71]), dementia (SHR, 1.66 [95% CI, 1.14-2.42]), increasing age (65-74 versus 85+ years; SHR, 1.75 [95% CI, 1.31-2.34]), living in regional Australia (SHR, 31 [95% CI, 1.08-1.60]), and aged care service approvals: respite (SHR, 4.54 [95% CI, 3.51-5.85]) and high-level home support (SHR, 1.80 [95% CI, 1.30-2.48]). Protective factors included being dispensed antihypertensive medications (SHR, 0.68 [95% CI, 0.53-0.87]), seeing a cardiologist (SHR, 0.72 [95% CI, 0.57-0.91]) following stroke, and less severe stroke (SHR, 0.71 [95% CI, 0.58-0.88]). CONCLUSIONS: Our findings provide an improved understanding of factors that influence the transition from community to permanent residential care following stroke and can inform future strategies designed to delay this transition.

Fracture Risk Increases After Stroke or Transient Ischemic Attack and Is Associated With Reduced Quality of Life.

BACKGROUND: Fractures are a serious consequence following stroke, but it is unclear how these events influence health-related quality of life (HRQoL). We aimed to compare annualized rates of fractures before and after stroke or transient ischemic attack (TIA), identify associated factors, and examine the relationship with HRQoL after stroke/TIA. METHODS: Retrospective cohort study using data from the Australian Stroke Clinical Registry (2009-2013) linked with hospital administrative and mortality data. Rates of fractures were assessed in the 1-year period before and after stroke/TIA. Negative binomial regression, with censoring at death, was used to identify factors associated with fractures after stroke/TIA. Respondents provided HRQoL data once between 90 and 180 days after stroke/TIA using the EuroQoL 5-dimensional 3-level instrument. Adjusted logistic regression was used to assess differences in HRQoL at 90 to 180 days by previous fracture. RESULTS: Among 13 594 adult survivors of stroke/TIA (49.7% aged ≥75 years, 45.5% female, 47.9% unable to walk on admission), 618 fractures occurred in the year before stroke/TIA (45 fractures per 1000 person-years) compared with 888 fractures in the year after stroke/TIA (74 fractures per 1000 person-years). This represented a relative increase of 63% (95% CI, 47%-80%). Factors associated with poststroke fractures included being female (incidence rate ratio [IRR], 1.34 [95% CI, 1.05-1.72]), increased age (per 10-year increase, IRR, 1.35 [95% CI, 1.21-1.50]), history of prior fracture(s; IRR, 2.56 [95% CI, 1.77-3.70]), and higher Charlson Comorbidity Scores (per 1-point increase, IRR, 1.18 [95% CI, 1.10-1.27]). Receipt of stroke unit care was associated with fewer poststroke fractures (IRR, 0.67 [95% CI, 0.49-0.93]). HRQoL at 90 to 180 days was worse among patients with prior fracture across the domains of mobility, self-care, usual activities, and pain/discomfort. CONCLUSIONS: Fracture risk increases substantially after stroke/TIA, and a history of these events is associated with poorer HRQoL at 90 to 180 days after stroke/TIA.

The population effect of a national policy to incentivize chronic disease management in primary care in stroke: a population-based cohort study using an emulated target trial approach.

Background: Governments are investing in primary care policies that support chronic disease management. Large scale population-based evaluations are lacking. We aim to determine the effectiveness of government-funded chronic disease management policies to improve long-term outcomes (survival, hospital presentations, and preventive medication adherence) following stroke/Transient Ischemic Attack (TIA). Methods: Using a population-based cohort we utilized the target trial methodology. Participants were identified through the Australian Stroke Clinical Registry (January 2012-December 2016) from 42 hospitals in the states of Victoria and Queensland and linked with state and national hospital, primary care, pharmaceutical, aged care, and death datasets. Registrants living in the community, not receiving palliative care and who survived to 18 months following stroke/TIA were included. The comparison was a Medicare claim for policy-supported chronic disease management, 7-18 months following stroke/TIA versus usual care. Outcomes were modelled using multi-level, mixed-effects inverse probability of treatment weighted regression. Findings: 12,368 registrants were eligible (42% female, median age 70 years, 26% TIA), 45% had a chronic disease management claim. The difference in mean outcomes for participants with a claim, compared to those without, showed a 26% lesser mortality rate (adjusted hazard ratio [aHR]: 0.74, 95% confidence interval [CI]: 0.62, 0.87) and a greater adjusted Odds Ratio [aOR] of being adherent with preventive medications: antithrombotics (aOR: 1.16, 95% CI: 1.07, 1.26); lipid-lowering (aOR: 1.23, 95% CI: 1.13, 1.33). Impacts on hospital presentations were variable. Interpretation: Government policies that financially support primary care physicians to provide structured chronic disease management improve survival in the long-term following stroke/TIA. Funding: National Health and Medical Research Council Australia.

Twenty years of monitoring acute stroke care in Australia through the national stroke audit programme (1999-2019): A cross-sectional study.

BACKGROUND: National organisational surveys and clinical audits to monitor and guide improvements to the delivery of evidence-based acute stroke care have been undertaken in Australia since 1999. This study aimed to determine the association between repeated national audit cycles on stroke service provision and care delivery from 1999 to 2019. METHODS: Cross-sectional study using data from organisational surveys (1999, 2004, 2007-2019) and clinical data from the biennial National Stroke Acute Audit (2007-2019). Age-, sex-, and stroke severity-adjusted proportions were reported for adherence to guideline-recommended care processes. Multivariable, logistic regression models were performed to determine the association between repeated audit cycles and service provision (organisational) and care delivery (clinical). RESULTS: Overall, 197 hospitals provided organisational survey data (1999-2019), with 24,996 clinical cases from 136 hospitals (around 40 cases per audit) (2007-2019). We found significant improvements in service organisation between 1999 and 2019 for access to stroke units (1999: 42%, 2019: 81%), thrombolysis services (1999: 6%, 2019: 85%), and rapid assessment/management for patients with transient ischaemic attack (1999: 11%, 2019: 61%). Analyses of patient-level audits for 2007 to 2019 found the odds of receiving care processes per audit cycle to have significantly increased for thrombolysis (2007: 3%, 2019: 11%; OR 1.15, 95% CI 1.13, 1.17), stroke unit access (2007: 52%, 2019: 69%; OR 1.15, 95% CI 1.14, 1.17), risk factor advice (2007: 40%, 2019: 63%; OR 1.10, 95% CI 1.09, 1.12), and carer training (2007: 24%, 2019: 51%; OR 1.12, 95% CI 1.10, 1.15). CONCLUSIONS: Between 1999 and 2019, the quality of acute stroke care in Australia has improved in line with best practice evidence. Standardised monitoring of stroke care can inform targeted efforts to reduce identified gaps in best practice, and illustrate the evolution of the health system for stroke.

The relationship between social isolation, social support, and loneliness with cardiovascular disease and shared risk factors: A narrative review.

BACKGROUND: Cardiovascular disease (CVD) is the greatest contributor to global morbidity and mortality. Poor social health plays a critical role in CVD incidence. Additionally, the relationship between social health and CVD may be mediated through CVD risk factors. However, the underlying mechanisms between social health and CVD are poorly understood. Certain social health constructs (social isolation, low social support and loneliness) have complicated the characterisation of a causal relationship between social health and CVD. AIM: To provide an overview of the relationship between social health and CVD (and its shared risk factors). METHOD: In this narrative review, we examined published literature on the relationship between three social health constructs (social isolation, social support, and loneliness) and CVD. Evidence was synthesised in a narrative format, focusing on the potential ways in which social health affects CVD, including shared risk factors. RESULTS: The current literature highlights an established relationship between social health and CVD with a likelihood for bi-directionality. However, there is speculation and varied evidence regarding how these relationships may be mediated through CVD risk factors. CONCLUSIONS: Social health can be considered an established risk factor for CVD. However, the potential bi-directional pathways of social health with CVD risk factors are less established. Further research is needed to understand whether targeting certain constructs of social health may directly improve the management of CVD risk factors. Given the health and economic burdens of poor social health and CVD, improvements to addressing or preventing these interrelated health conditions would have societal benefits.

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.

Antihypertensive Medication Adherence and the Risk of Vascular Events and Falls After Stroke: A Real-World Effectiveness Study Using Linked Registry Data.

BACKGROUND: Real-world evidence is limited on whether antihypertensive medications help avert major adverse cardiovascular events (MACE) after stroke without increasing the risk of falls. We investigated the association of adherence to antihypertensive medications on the incidence of MACE and falls requiring hospitalization after stroke. METHODS: A retrospective cohort study of adults who were newly dispensed antihypertensive medications after an acute stroke (Australian Stroke Clinical Registry 2012-2016; Queensland and Victoria). Pharmaceutical dispensing records were used to determine medication adherence according to the proportion of days covered in the first 6 months poststroke. Outcomes between 6 and 18 months postdischarge included: (i) MACE, a composite outcome of all-cause death, recurrent stroke or acute coronary syndrome; and (ii) falls requiring hospitalization. Estimates were derived using Cox models, adjusted for >30 confounders using inverse probability treatment weights. RESULTS: Among 4076 eligible participants (median age 68 years; 37% women), 55% had a proportion of days covered ≥80% within 6 months postdischarge. In the subsequent 12 months, 360 (9%) participants experienced a MACE and 337 (8%) experienced a fall requiring hospitalization. After achieving balance between groups, participants with a proportion of days covered ≥80% had a reduced risk of MACE (hazard ratio: 0.68; 95% CI: 0.54-0.84) and falls requiring hospitalization (subdistribution hazard ratio: 0.78; 95% CI: 0.62-0.98) than those with a proportion of days covered <80%. CONCLUSIONS: High adherence to antihypertensive medications within 6 months poststroke was associated with reduced risks of both MACE and falls requiring hospitalization. Patients should be encouraged to adhere to their antihypertensive medications to maximize poststroke outcomes.

Factors associated with mental health service access among Australian community-dwelling survivors of stroke.

PURPOSE: To describe types of mental health treatment accessed by community-based stroke survivors and factors associated with access. METHODS: A sub-group of registrants from the Australian Stroke Clinical Registry completed a supplementary survey 2.5 years post-stroke. Self-reported information about depression/anxiety and treatment access were collected. Demographic and clinical data were obtained through linkages with registry and government data. Staged multivariable logistic regression was conducted to examine factors associated with treatment access. RESULTS: Among 623 registrants surveyed (37% female, median age 69 years), 26% self-reported a medical diagnosis of depression/anxiety at 2.5 years post-stroke. Of these, only 30% reported having accessed mental health services, mostly through government-funded Medicare schemes. Younger age (odds ratio (OR) 0.95, 95% CI 0.93, 0.98), history of mental health treatment (OR 3.38, 95% CI 1.35, 8.48), feeling socially isolated (OR 2.32, 95% CI 1.16, 4.66), self-reported medical diagnosis of depression/anxiety (OR 4.85, 95% CI 2.32, 10.14), and government-subsidised team care plan arrangement (OR 4.05, 95% CI 1.96, 8.37) were associated with receiving treatment. CONCLUSIONS: Many stroke survivors have untreated depression/anxiety. Primary care practitioners should be supported in undertaking effective detection and management. Older and newly diagnosed individuals should be educated about depression/anxiety and available supports.Implications for rehabilitationPrimary care providers play a pivotal role in the pathway to mental health care, and therefore should always screen for depression/anxiety and provide comprehensive assessment and referral to specialist services where necessary.Targeted psychoeducation should be provided to survivors of stroke who are older and newly diagnosed with depression/anxiety, to increase awareness about mood problems following stroke.Primary care providers should collaborate with other health professionals (e.g., through coordinating a team care arrangement plan), to address patients' multiple and complex rehabilitation needs.Rehabilitation professionals should remain informed about current evidence-based treatments for post-stroke depression/anxiety and pathways that enable their patients to access these services.

Comparison of comorbidities of stroke collected in administrative data, surveys, clinical trials and cohort studies.

BACKGROUND: Administrative data are used extensively for research purposes, but there remains limited information on the quality of these data for identifying comorbidities related to stroke. OBJECTIVE: To compare the prevalence of comorbidities of stroke identified using International Classification Diseases, Australian Modification (ICD-10-AM) or Anatomical Therapeutic Chemical codes, with those from (i) self-reported data and (ii) published studies. METHOD: The cohort included patients with stroke or transient ischaemic attack admitted to hospitals (2012-2016; Victoria and Queensland) in the Australian Stroke Clinical Registry (N = 26,111). Data were linked with hospital and pharmaceutical datasets to ascertain comorbidities using published algorithms. The sensitivity, specificity, and positive predictive value of these comorbidities were compared with survey responses from 623 patients (reference standard). An indirect comparison was also performed with clinical data from published stroke studies. RESULTS: The sensitivity of hospital ICD-10-AM data was poor for most comorbidities, except for diabetes (93.0%). Specificity was excellent for all comorbidities (87-96%), except for hypertension (70.5%). Compared to published stroke studies (3 clinical trials and 1 incidence study), the prevalence of diabetes and atrial fibrillation in our cohort was similar using ICD-10-AM codes, but lower for dyslipidaemia and anxiety/depression. Whereas in the pharmaceutical dispensing data, the sensitivity was excellent for dyslipidaemia (94%) and modest for anxiety/depression (77%). In the pharmaceutical data, specificity was modest for hypertension (78%) and anxiety or depression (76%), but specificity was poor for dyslipidaemia (19%) and heart disease (46%). CONCLUSION: Variation was observed in the reporting of comorbidities of stroke in administrative data, and consideration of multiple sources of data may be necessary for research. Further work is needed to improve coding and clinical documentation for reporting of comorbidities in administrative data.

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.

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.

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.

Understanding of medications and associations with adherence, unmet needs, and perceived control of risk factors at two years post-stroke.

BACKGROUND: It is unclear whether survivors of stroke or transient ischemic attack (TIA) routinely receive, and understand, education about secondary prevention medications. OBJECTIVES: To investigate whether survivors of stroke/TIA understand explanations about their prescribed prevention medications and associations with medication adherence, control of risk factors, and unmet needs. METHODS: A survey was administered among survivors of stroke/TIA (random sample N = 1500) from the Australian Stroke Clinical Registry (Victoria and Queensland, 2016). Participants reported whether they understood explanations about each prescribed medication, as well as their unmet needs, perceived control of risk factors, and 30-day medication adherence. Linked pharmacy claims data were also used to determine medication adherence in the previous two years (proportion of days covered ≥80%). Outcomes were analyzed using multivariable logistic regression or multivariable negative binomial regression for frequency of unmet needs. RESULTS: Overall, 630/1455 eligible survivors completed the survey at ≈2.5 years post-admission (median age 69 years; 37% female). Most participants reported using prevention medications (76% antihypertensive; 84% antithrombotic; 76% lipid-lowering) but only 66-75% reported they understood explanations about their medication (75% antihypertensive; 66% antithrombotic; 74% lipid-lowering). Participants who understood explanations about their medication more often reported 30-day adherence for antihypertensive (adjusted odds ratios [aOR]: 1.96; 95% CI: 1.20-3.19), antithrombotic (aOR: 2.03; 95% CI: 1.31-3.14) and lipid-lowering medications (aOR: 1.73; 95% CI: 1.08-2.76). Similar associations were observed for antihypertensive and antithrombotic medications when pharmacy claims data were used to infer 2-year medication adherence. Understanding explanations about medications was also associated with perceived control of risk factors (hypertension: aOR: 11.08; 95% CI: 6.04-20.34; cholesterol aOR: 8.26; 95% CI: 4.72-14.47) and up to 33% fewer unmet needs related to secondary prevention. CONCLUSIONS: Expanded efforts are needed to improve the delivery of information about prevention medications to promote medication adherence, control of risk factors, and potentially prevent unmet needs following stroke/TIA.

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.