Persistent lowering of arterial pressure after continuous and intermittent therapy
Bibliographic record
Abstract
OBJECTIVE: The present study investigates the impact of antihypertensive treatment on persistent reduction of arterial pressure after cessation of drug treatment. DESIGN AND METHODS: Specifically, adult spontaneously hypertensive rats (SHR) were treated for 6 weeks with inhibitors of the renin-angiotensin system (RAS), or combination therapy (hydralazine, nifedipine, hydrochlorothiazide) and following a 14-week 'drug holiday', were re-treated for 4 weeks. Mean arterial pressure (MAP) was continuously monitored via radiotelemetry. RESULTS: Comparison in the first off-treatment period revealed that RAS inhibitor drugs produced a 16-18% persistent lowering of arterial pressure, whereas the triple therapy induced a 10% lowering of MAP relative to untreated SHR. The drug re-challenge induced a further 9% reduction in the 'off'-treatment level of MAP such that in all treatment groups MAP was reduced by more than 30 mmHg compared with controls. CONCLUSIONS: This study provides new evidence that combination therapy, not directly targeting the RAS, can be efficacious in persistently reducing MAP off-treatment. Furthermore, we demonstrated that the 6-week treatment with RAS inhibitors induced equivalent persistent changes as a 10-week treatment. That is, the additional 4 weeks of continuous therapy was ineffective in further altering the off-treatment MAP. In contrast, with the intermittent treatment protocol (the 14-week 'drug holiday') a further effect on persistent lowering of MAP was regained. These findings suggest continuous long-term treatment with antihypertensive drugs may not be the most effective means of reversing underlying circulatory abnormalities and that the introduction of a drug holiday may be beneficial.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".