Large Increases in Hypertension Diagnosis and Treatment in Canada After a Healthcare Professional Education Program
Bibliographic record
Abstract
This study was conducted to compare the self-reported prevalence and treatment of hypertension in adult Canadians before and subsequent to the implementation of the Canadian Hypertension Education Program in 1999. Data were obtained from 5 cycles of the Canadian Health Surveys between 1994 and 2003 on respondents aged > or = 20 years. Piecewise linear regression was used to calculate the average annual increase in rates, before and after 1999. Between 1994 and 2003, the percentage of adult Canadians aware of being diagnosed with hypertension increased by 51% (from 12.37% to 18.74%; P<0.001), and the percentage prescribed antihypertensive drugs increased by 66% (from 9.57% to 15.86%; P<0.001). After 1999, there was approximately a doubling of the annual rate of increase in the diagnosis of hypertension (from 0.52% of the population per year before 1999 to 1.03% per year after 1999; P<0.001) and the percentage prescribed antihypertensive drugs (from 0.54% of the population per year before 1999 versus 0.98% per year after 1999; P<0.001). The proportion of those aware of the diagnosis of hypertension but not being treated with drugs was reduced by half between 1994 and 2003 (from 31.47% untreated to 15.34% untreated; P<0.001). There was a greater increase in awareness of hypertension and use of antihypertensive drugs among men compared with women after 1999. The large increase in the diagnosis and treatment of hypertension in Canada between 1994 and 2003 is consistent with an overall beneficial effect of the Canadian Hypertension Education Program, including a reduced gender gap in hypertension care.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".