The Canadian effort to prevent and control hypertension: can other countries adopt Canadian strategies?
Bibliographic record
Abstract
PURPOSE OF REVIEW: To indicate the key elements of current Canadian programs to treat and control hypertension. RECENT FINDINGS: In the early 1990s Canada had a hypertension treatment and control rate of 13%. A Canadian strategy to prevent and control hypertension was developed and a coalition of national organizations and volunteers formed to develop increasingly extensive programs. The Canadian effort was largely based on annually updated hypertension management recommendations, an integrated and extensive hypertension knowledge translation program and an increasingly comprehensive outcomes assessment program. After the start of the annual process in 1999, there were very large increases in diagnosis and hypertension treatment coupled with dropping rates of cardiovascular disease. More recent initiatives include an extensive education program for the public and people with hypertension, a program to reduce dietary salt and a funded leadership position. The treatment and control rate increased to 66% when last assessed (2007-2009). SUMMARY: The study describes important aspects of the Canadian hypertension management programs to aid those wishing to develop similar programs. Many of the programs could be fully or partially implemented by other countries.
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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".