Abstract 436: Over - Versus Under-Treatment of Older Hypertensives in Canada
Bibliographic record
Abstract
In a re-analysis of data collected during the 2006 Ontario Survey on the Prevalence and Control of Hypertension (Leenen et al, CMAJ 2008), we focussed on the actual blood pressures in treated and untreated older and middle-aged hypertensives. In the older (60-79 years of age) population of 1,426,752 subjects, using traditional definitions the prevalence of hypertension was 49% compared to 21% in the middle-aged (40-59 years of age) population. Hypertension treatment and control rates were similarly high in middle-aged and older hypertensives at 67% and 64% respectively. 39% of older hypertensives were treated with a single antihypertensive drug, and of these 54% had a systolic BP level of < 130 mmHg, and 23% had a systolic BP < 120 mmHg. Of the 61% treated with combination therapy, 44% had a systolic BP < 120 mmHg. 13% of older hypertensives were untreated, and out of those approximately 90% had Stage 1 hypertension, with ~70% without additional risk factors. Considering that monotherapy may lower systolic BP by < 10 mmHg, these findings suggest that there may be a major problem of over-diagnosis and/or over-treatment of hypertension in older adults overestimating substantially the actual prevalence of hypertension, creating an unnecessary burden on the health care system and exposing many older subjects to unnecessary risks of drug therapy.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.000 |
| 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".