Prevalence, Patient Awareness, Treatment, and Control of Hypertension in Canadian Adults With Common Comorbidities
Bibliographic record
Abstract
Background: Whether certain medical conditions are associated with blood pressure (BP) treatment and control is unclear. Methods: Using the Canadian Health Measures Survey (2007-2019), BP was assessed according to the presence of selected comorbidities, including prior heart attack or stroke, dyslipidemia, chronic kidney disease, diabetes mellitus, obstructive sleep apnea, and overweight or obesity. Results: A total of 5,841,453 people, representing 23.0% (95% confidence interval [CI] 21.7%-24.2%) of Canadian adults, were hypertensive. The adjusted odds ratio (aOR) of having hypertension treated and controlled was higher in people with the following conditions, as compared to people without these conditions: a prior heart attack or stroke (aOR 3.15; 95% CI 2.31-4.31); dyslipidemia (aOR 2.51; 95% CI 1.96-3.21); obstructive sleep apnea (aOR 1.95; 95% CI 1.19-3.21); overweight or obesity (aOR 1.51; 95% CI 1.18-1.94); chronic kidney disease (aOR 1.49; 95% CI 1.13-1.95); and diabetes (aOR 1.44; 95% CI 1.12-1.86). Individuals without any of these comorbidities were less likely to have BP that is treated and controlled (aOR 0.34; 95% CI 0.25-0.48). Moreover, the prevalence of BP treatment and control was low among many people without prior heart attack or stroke, even those with a moderate (aOR 0.25; 95% CI 0.17-0.37) or high (aOR 0.10; 95% CI 0.06-0.16) Framingham risk. Conclusions: Large differences in levels of BP control exist across comorbidity profiles, and the greatest gaps are seen in individuals without recognized comorbidities, even those who have a moderate-to-high Framingham risk. Efforts to optimize BP control and narrow care gaps, especially in individuals without recognized comorbidities, are necessary to reduce the burden of cardiovascular disease and premature death in Canada.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".