Update on trials examining effects of night-time blood pressure lowering drug treatment on prevention of cardiovascular disease
Bibliographic record
Abstract
Current evidence on benefits of night-time blood pressure (BP) lowering drug treatment on cardiovascular disease (CVD) prevention attributable to the Ambulatory Blood Pressure Monitoring in the Prediction of Cardiovascular Events and Effects of Chronotherapy (MAPEC) trial and Bedtime hypertension treatment improves cardiovascular risk reduction (Hygia) trials has raised concern on their validity and methodology. In this commentary, the authors have updated the progress of the ongoing trials that were planned to examine the effect of night-time BP lowering drug treatment on CVD prevention. As compared to MAPEC and Hygia trials, three pragmatic trials the Blood Pressure Medication Timing (BPMedtime) trial (US), the Treatment In Morning versus Evening (TIME) trial (UK), Bedmed and Bedmed-frail (Canada) were planned without ambulatory BP monitoring. The BPMedtime trial was stopped after the pilot phase due to underestimated sample size and insufficient funds. TIME trial (UK) had a similar issue when changing the sample size from 10,269 to more than 20,000 participants. The TIME trial was completed and the initial results showing that protection against heart attack, stroke and vascular death is not affected by whether antihypertensive medications are taken in the morning or evening. The full study of the TIME trial is published in December 2022. Bedmed and Bedmed-frail trials are ongoing and will be completed in 2023. Time of taking BP lowering drug should be determined by patients at their convenience to improve the adherence. There was no difference in adverse effects of taking BP lowering drugs at night or morning. Evidence on the effect of night-time treatment on CVD events is inconsistent. The results from ongoing trials in Canada will contribute evidence to the use of BP lowering drug treatment for the prevention of CVD.
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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 | 0.032 | 0.138 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".