Clinical Trial Design Principles and Outcomes Definitions for Device-Based Therapies for Hypertension: A Consensus Document From the Hypertension Academic Research Consortium
Bibliographic record
Abstract
The clinical implications of hypertension in addition to a high prevalence of both uncontrolled blood pressure and medication nonadherence promote interest in developing device-based approaches to hypertension treatment. The expansion of device-based therapies and ongoing clinical trials underscores the need for consistency in trial design, conduct, and definitions of clinical study elements to permit trial comparability and data poolability. Standardizing methods of blood pressure assessment, effectiveness measures beyond blood pressure alone, and safety outcomes are paramount. The Hypertension Academic Research Consortium (HARC) document represents an integration of evolving evidence and consensus opinion among leading experts in cardiovascular medicine and hypertension research with regulatory perspectives on clinical trial design and methodology. The HARC document integrates the collective information among device-based therapies for hypertension to better address existing challenges and identify unmet needs for technologies proposed to treat the world's leading cause of death and disability. Consistent with the Academic Research Consortium charter, this document proposes pragmatic consensus clinical design principles and outcomes definitions for studies aimed at evaluating device-based hypertension therapies.
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 | 0.705 | 0.601 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.010 | 0.014 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.008 | 0.017 |
| Scholarly communication | 0.026 | 0.009 |
| Open science | 0.015 | 0.014 |
| Research integrity | 0.038 | 0.056 |
| Insufficient payload (model declined to judge) | 0.003 | 0.005 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".