Bedtime versus morning use of antihypertensives for cardiovascular risk reduction (BedMed): protocol for a prospective, randomised, open-label, blinded end-point pragmatic trial
Bibliographic record
Abstract
Introduction Sleep-time blood pressure correlates more strongly with adverse cardiovascular events than does daytime blood pressure. The BedMed trial evaluates whether bedtime antihypertensive administration, as compared with conventional morning use, reduces major adverse cardiovascular events. Methods and analysis Design Prospective randomised, open-label, blinded end-point trial. Participants Hypertensive primary care patients using blood pressure lowering medication and free from glaucoma. Setting Community primary care providers in 5 Canadian provinces (British Columbia, Alberta, Saskatchewan, Manitoba and Ontario) are mailing invitations to their eligible patients. Social media campaigns (Google, Facebook) are additionally running in the same provinces. Intervention Consenting participants are allocated via central randomisation to bedtime vs morning use of all antihypertensives. Follow-up (1) Telephone or email questionnaire at 1 week, 6 weeks, 6 months and every 6 months thereafter, and (2) accessing linked governmental healthcare databases tracking hospital and community medical services. Primary outcome Composite of all-cause death, or hospitalisation for myocardial infarction/acute-coronary syndrome, stroke or congestive heart failure. Secondary outcomes Each primary outcome element on its own, all-cause hospitalisation or emergency department visit, long-term care admission, non-vertebral fracture, new glaucoma diagnosis, 18-month cognitive decline from baseline (via Short Blessed Test). Select other outcomes Self-reported nocturia burden at 6 weeks and 6 months (no, minor or major burden), 1-year self-reported overall health score (EQ-5D-5L), self-reported falls, total cost of care (acute and community over study duration) and mean sleep-time systolic blood pressure after 6 months (via 24-hour monitor in a subset of 302 sequential participants). Primary outcome analysis Cox proportional hazards survival analysis. Sample size The trial will continue until a projected 254 primary outcome events have occurred. Current status Enrolment ongoing (3227 randomised to date). Ethics and dissemination BedMed has ethics approval from six research ethics review boards and will publish results in a peer-reviewed journal. Trial registration number NCT02990663 .
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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 | 0.035 | 0.030 |
| Meta-epidemiology (narrow) | 0.008 | 0.004 |
| Meta-epidemiology (broad) | 0.012 | 0.006 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.086 | 0.020 |
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".