Bibliographic record
Abstract
What Is the Issue? It is estimated that 23% of adults in Canada have hypertension. About 1/3 of this population have uncontrolled hypertension, a condition in which (BP) blood pressure levels continue to remain high despite treatment. People with high BP despite being prescribed 3 or more blood pressure-lowering (antihypertensive) medicines are considered to have uncontrolled resistant hypertension. Renal denervation is a therapy that involves disrupting activity in the sympathetic nerves in the renal artery using a minimally invasive catheter-based procedure to treat high BP. We wanted to know if renal denervation would effectively and safely reduce BP in people with uncontrolled hypertension. What Did We Do? We identified and summarized the literature comparing the clinical effectiveness and safety of renal denervation in individuals with uncontrolled hypertension to help guide decisions on the use of this intervention. An information specialist searched for peer-reviewed and grey literature sources published between January 1, 2019, and February 5, 2024. The search was limited to English-language documents. One reviewer screened articles for inclusion based on predefined criteria, critically appraised the included studies, and narratively summarized the findings. What Did We Find? The evidence for this report was based on 2 systematic reviews and 3 randomized controlled trials (RCTs). Renal denervation could lead to a reduction in BP compared to sham in adults with uncontrolled nonresistant hypertension. It is uncertain if renal denervation is an effective treatment for resistant hypertension and suspected hypertensive heart disease due to the methodological limitations of the included studies. Serious side effects of renal denervation were rare. What Does This Mean? Our findings agree with evidence-based guidelines and real-world evidence that suggest renal denervation can be considered a treatment option for patients with uncontrolled nonresistant hypertension. Other factors, including costs and resources, equity, acceptability, and patient selection, should be considered when implementing renal denervation in Canada, where it remains an emerging medical technology. Future research should assess important patient outcomes, such as quality of life.
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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 | 0.009 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 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".