Bibliographic record
Abstract
The latest evidence indicates that 50,000 Canadians will experience a stroke in 2013. The hospital care, rehabilitation, and long term care associated with a stroke places a significant burden on our health care system. Lost productivity and premature death have an immeasurable impact on communities in our province as well as the rest of the country. Small, less populated regions such as Saskatchewan may be underrepresented in national data utilized in the development of national prevention and treatment strategies across the country. The absence of local research has necessitated the use of national information to guide prevention, treatment education and programming in Saskatchewan. The goals of this study was to provide a descriptive profile of stroke and transient ischemic attack cases admitted to Royal University Hospital over the period of April 1, 2009 to March 31st, 2010 and to assess the acute management of these cases as defined in the Canadian Best Practice Recommendations for Stroke Care (Strategy, 2010). A randomized sample of 200 cases 55 years and older was selected for a retrospective descriptive study involving review of adult stroke case records. Personal demographics and healthcare performance through the use of measures provided in The Canadian Best Practice Recommendations for Stroke Care (Canadian Stroke Network (CSN) and Heart and Stroke Foundation of Canada (HSFC), 2010) were evaluated. The results indicated many similarities to available national information on type of stroke, risk factors, gender, and age. Hospital adherence to national guidelines comparing selected indicators was exceeded in some areas, and met in most. The remaining indicators provide an opportunity for improvement and possibly more research. This regional information supplements the available Canadian information and could be used to guide planning and care strategically targeting Saskatchewan residents and increasing their potential for success.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".