Abstract W P348: Evaluating Gaps in the Continuum of Stroke Care
Bibliographic record
Abstract
Background and Purpose: Medication adherence is an important factor for secondary stroke prevention in ambulatory care. We aimed to evaluate short-term adherence to antihypertensive and lipid-lowering agents after a new ischemic stroke as a predictor of adherence at one and two years after discharge. Methods: A five-year cohort (2003-2008) of patients from eleven institutions participating in the Registry of the Canadian Stroke Network (RCSN) was linked to population-based administrative health records. Patients with a diagnosis of an acute ischemic stroke who were discharged home were included in the study. Medication adherence was assessed through documentation of a filled prescription at seven days, one year and two years from hospital discharge. Results: From 2003 to 2008, 6,437 ischemic stroke patients were discharged home from hospital. A total of 1126 patients filled a prescription for antihypertensive and lipid-lowering agents within 7 days of hospital discharge. Patients provided with a prescription at discharge were more likely to be adherent to antihypertensive and lipid-lowering agents at seven days than patients who did not receive a prescription . Adherence at one year (X% vs Y%, p-value=?) was higher in patients who demonstrated adherence at seven days from discharge for antihypertensive (93.8% vs 87.7%, p<0.0001), lipid-lowering agents (88% vs 81.9%, p<0.0001), or both (85.8% vs 79.9%, p<0.0001). Similar findings are noted at two years for antihypertensives (92.2% vs 87.7%, p=0.0003), lipid-lowering agents (82.6% vs 79.0%, p=0.0394), or both (81.1% vs 77.0%, p=0.0099). Conclusion: Filling prescriptions within one week of discharge from hospital for acute ischemic stroke predicts adherence for secondary preventive therapies at one and two years. Provision of a prescription at the time of discharge to both prior and new users of anti-hypertensive and lipid-lowering drugs is a simple and effective intervention to improve adherence to secondary preventive medications at seven days, one year and two years after ischemic stroke.
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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".