Spectral analysis of blood pressure variability before and after exercise during angiotensin antagonism
Bibliographic record
Abstract
We evaluated the effects of tasosartan (TASO), a specific antagonist of AT1 receptors, on blood pressure (BP) variability before and after exercise. Twenty hypertensive patients (48 ± 2 years, 78 ± 3 kg, 28 ± 1 kg/m2, mean ± SEM) participated in this randomized, double-blind crossover, placebo-controlled study. Each patient received TASO (100 mg/d) or placebo (PLAC) during two periods of two weeks separated by two weeks of wash out. Beat by beat systolic (SBP) and diastolic blood pressures (DBP) were measured by a photoplethysmographic device (Finapress) and recorded on a computer during 10 minutes before and after an exercise period of 30 minutes on a stationary bicycle at 50% of VO2max. Autonomic nervous system activity was evaluated by spectral analysis of SBP and DBP variability using the low frequency band (0.05–0.15 Hz, LF power, in ms2/Hz), to assess sympathetic activity and the high frequency band (0.15–0.4 Hz, HF power, ms2/Hz) to assess parasympathetic activity. The LF/HF ratio was taken as an index of sympathovagal balance. (See Table) P < 0.05, p < 0.001 vs PLAC; <0.05; <0.001 vs same treatment during pre-exercise evaluation (ANOVA). These results suggest that sympathetic and parasympathetic activity are decreased to different extents after exercise with TASO leading to an increased sympathovagal balance whereas no such change was found with placebo. A shift toward higher sympathetic vs parasympathetic balance may occur as a result of baroreflex activation due to greater reduction in BP after exercise with TASO compared to PLAC.
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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 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".