Characterizing Hypertension Specialist Care in Canada: A National Survey
Bibliographic record
Abstract
Background: The hypertension specialist often receives referrals of patients with young-onset, severe, difficult-to-control hypertension, patients with hypertensive emergencies, and patients with secondary causes of hypertension. Specialist hypertension care compliments primary care for these complex patients and contributes to an overall hypertension control strategy. The objective of this study was to characterize hypertension centres and the practice patterns of Canadian hypertension specialists. Methods: Adult hypertension specialists across Canada were surveyed to describe hypertension centres and specialist practice in Canada, including the following: the patient population managed by hypertension specialists; details on how care is provided; practice pattern variations; and differences in access to specialized hypertension resources across the country. Results: The survey response rate was 73.5% from 25 hypertension centres. Most respondents were nephrologists and general internal medicine specialists. Hypertension centres saw between 50 and 2500 patients yearly. A mean of 17% (± 15%) of patients were referred from the emergency department and a mean of 52% (± 24%) were referred from primary care. Most centres had access to specialized testing (adrenal vein sampling, level 1 sleep studies, autonomic testing) and advanced therapies for resistant hypertension (renal denervation). Considerable heterogeneity was present in the target blood pressure in young people with low cardiovascular risk and in the diagnostic algorithms for investigating secondary causes of hypertension. Conclusions: These results summarize the current state of hypertension specialist care and highlight opportunities for further collaboration among hypertension specialists, including standardization of the approach to specialist care for patients with hypertension.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| 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) | 0.001 | 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".