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 (2009–2013) 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 (1–5), intermediate-risk (5–15), 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 (OR adjusted , 1.05 [95% CI, 1.04 to 1.06), 90-day mortality (HR adjusted , 1.04 [95% CI, 1.03 to 1.05]), readmissions (OR adjusted , 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.

Background and Purpose— Readmissions after stroke are common and appear to be associated with comorbidities or disability-related characteristics. In this study, we aimed to determine the patient and health-system level factors associated with all-cause and unplanned hospital readmission within 90 days after acute stroke or transient ischemic attack (TIA) in Australia. Methods— We used person-level linkages between data from the Australian Stroke Clinical Registry (2009–2013), hospital admissions data and national death registrations from 4 Australian states. Time to first readmission (all-cause or unplanned) for discharged patients was examined within 30, 90, and 365 days, using competing risks regression to account for deaths postdischarge. Covariates included age, stroke severity (ability to walk on admission), stroke type, admissions before stroke/TIA and the Charlson Comorbidity Index (derived from International Statistical Classification of Diseases and Related Health Problems, Tenth Revision , [Australian modified] coded hospital data in the preceding 5 years). Results— Among the 13 594 patients discharged following stroke/TIA (45% female; 65% ischemic stroke; 11% intracerebral hemorrhage; 4% undetermined stroke; and 20% TIA), 25% had an all-cause readmission and 15% had an unplanned readmission within 90 days. In multivariable analyses, the factors independently associated with a greater risk of unplanned readmission within 90 days were being female (subhazard ratio, 1.13 [95% CI, 1.03–1.24]), greater Charlson Comorbidity Index scores (subhazard ratio, 1.11 [95% CI, 1.09–1.12]) and having an admission ≤90 days before the index event (subhazard ratio, 1.85 [95% CI, 1.59–2.15]). Compared with being discharged to rehabilitation or aged care, those who were discharged directly home were more likely to have an unplanned readmission within 90 days (subhazard ratio, 1.44 [95% CI, 1.33–1.55]). These factors were similar for readmissions within 30 and 365 days. Conclusions— Apart from comorbidities and patient-level characteristics, readmissions after stroke/TIA were associated with discharge destination. Greater support for transition to home after stroke/TIA may be needed to reduce unplanned readmissions.

ObjectiveTo investigate whether certain patient, acute-care, or primary-care factors are associated with medication initiation and discontinuation in the community post-stroke or TIA.MethodsRetrospective cohort study using prospective data on adult patients with first-ever acute stroke/TIA from the Australian Stroke Clinical Registry (April 2010 to June 2014), linked with nationwide medication dispensing and Medicare claims data. Medication users were those with ≥1 dispensing in the year post-discharge. Discontinuation was assessed among medication users and defined as having no medication supply for ≥90 days in the year post-discharge. Multivariable competing risks regression, accounting for death during the observation period, was conducted to investigate factors associated with time to medication discontinuation.ResultsAmong 17,980 registry patients with stroke/TIA, 91.4% were linked to administrative datasets. Of these, 9,817 adults with first-ever stroke/TIA were included (45.4% female, 47.6% aged ≥75 years, and 11.4% intracerebral hemorrhage). While most patients received secondary prevention medications (79.3% antihypertensive, 81.8% antithrombotic, and 82.7% lipid-lowering medication), between one-fifth and one-third discontinued treatment over the subsequent year post-discharge (20.9% antihypertensive, 34.1% antithrombotic, and 28.5% lipid-lowering medications). Prescription at hospital discharge (sub-hazard ratio [SHR]: 0.70; 95% CI: 0.62–0.79), quarterly contact with a primary-care physician (SHR: 0.62; 95% CI: 0.57–0.67), and prescription by a specialist physician (SHR: 0.87; 95% CI: 0.77–0.98) were all inversely associated with antihypertensive discontinuation.ConclusionsPatterns of use of secondary prevention medications after stroke/TIA are not optimal, with many survivors discontinuing treatment within one-year post-discharge. Improving post-discharge care for patients with stroke/TIA is needed to minimize unwarranted discontinuation.

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 2010–June 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, 0.81–0.95]), 13% for statins (hazard ratio, 0.87 [95% CI, 0.80–0.95]), and 15% for nonaspirin antithrombotic agents (hazard ratio, 0.85 [95% CI, 0.79–0.93]). 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.