Adherence to Canadian Best Practice Recommendations for Stroke Care: Assessment and Management of Poststroke Depression in an Ontario Rehabilitation Facility
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Although Canadian best practice recommendations regarding assessment and management of poststroke depression (PSD) have been established, the degree to which these evidence-based guidelines have been translated into practice is not known. The objectives of the present study are to compare current and recommended best practice and examine possible reasons for identified care gaps. METHODS: Practice audit by chart review was performed to identify recorded screening, assessment, and treatment for PSD in patients discharged from a specialized inpatient rehabilitation program over a 6-month period. A questionnaire was administered to all clinical staff addressing current screening practices as well as opinions regarding the importance and feasibility of identification and treatment of PSD. RESULTS: Of 123 patients, 40 (32.5%) had been prescribed antidepressants at discharge. However, evidence of screening was found for 4.9% of patients; another 9.8% were referred for psychological consult. Treatment was associated with previous antidepressant use or history of depression, but not screening or assessment. Of the survey respondents, 56.2% were not aware of best practice recommendations. However, most felt screening and assessment to be important and treatment was regarded as both simple and effective. CONCLUSIONS: Despite potential benefit associated with identification and treatment of PSD and the availability of evidence-based best practice recommendations, PSD may remain unrecognized and undertreated. Given the juxtaposition of perceived importance with the lack of documented best practice, education regarding standardized screening and the development of consistent clinical protocols including roles and responsibilities in the identification, diagnosis, and treatment of PSD are underway.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".