Association Between Schizophrenia and Adherence to Medications for Secondary Stroke Prevention
Bibliographic record
Abstract
BACKGROUND: Schizophrenia is associated with an increased risk of stroke and under-treatment of vascular risk factors, but less is known about adherence to medications for secondary stroke prevention. We sought to understand current rates of adherence to secondary stroke prevention therapies among elderly ischemic stroke survivors with and without schizophrenia. METHODS: In a population-based cohort study, we used administrative databases to identify all patients aged ≥65 years who were hospitalized with ischemic stroke in the province of Ontario, Canada, between 2004 and 2018, and a validated algorithm to identify those with schizophrenia. Among patients who filled a prescription for antihypertensive, lipid-lowering, or anticoagulant medications within 3 months and were alive 1 year after discharge, we compared the proportion with low adherence (defined as an annual proportion of days covered of <0.4) in those with and without schizophrenia. We used multivariable logistic regression to estimate the association between schizophrenia and low adherence adjusting for age, sex, comorbid conditions, area of residence, and socioeconomic status. RESULTS: Of the 55 842 patients included, the mean age was 79.5 years, 53.3% were women, and 1.0% had schizophrenia. Among those who survived to 1 year after discharge, individuals with schizophrenia were more likely than those without to have low adherence to antihypertensive (28.0% versus 18.8%; adjusted odds ratio, 1.60 [95% CI, 1.28-2.01]), lipid-lowering (38.6% versus 29.8%; adjusted odds ratio, 1.60 [95% CI, 1.31-1.96]), or anticoagulant medications (41.1% versus 32.0%; adjusted odds ratio, 1.61 [95% CI, 1.00-2.58]), even after adjustment for age, sex, comorbid illness, rurality, and neighborhood income quintile. CONCLUSIONS: Schizophrenia is associated with poor adherence to medications for secondary stroke prevention. Future work should focus on developing individual- and system-level interventions to improve vascular risk factor management in this population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".