[PP.28.06] DAY AND NIGHT PULSE PRESSURE AMPLIFICATION IN NORMOTENSIVE, HYPERTENSIVE DIPPER AND HYPERTENSIVE NON-DIPPER PATIENTS
Bibliographic record
Abstract
Objective: Several studies have shown that office central blood pressure (cBP) might better predict cardiovascular events than standard peripheral pressure. Recent ambulatory monitoring technologies such as the BPLab monitor equipped with Vasotens software (OOO Petr Telegin, Russia) allows to estimate cBP over 24 h. However to date, it is unknown if 24 h monitoring of cBP have added value to office cBP measurements. Design and method: We looked at the average day and night pulse pressure amplification (PPamp = peripheral pulse pressure/ central pulse pressure), cBP and pulse wave velocity (PWV) in 120 (60 M/60F) normotensives (NT), 120 (60 M/60F) hypertensive dippers (DI) and 120 (60 M/60F) hypertensive non-dippers (ND) matched for age, sex and day brachial SBP for the hypertensive subjects. Results: Between day and night, peripheral systolic blood pressure fell from 122 ± 8 to 103 ± 7 mmHg in NT, from 140 ± 11 to 117 ± 11 mmHg in DI and from 140 ± 12 to 137 ± 14 mmHg in ND. Heart rate fell from 70 ± 8 to 59 ± 7 bpm, 77 ± 10 to 63 ± 8 bpm and from 73 ± 12 to 65 ± 11 bpm in NT, DI and ND respectively. DI patients tended to have higher day PPamp value than other groups (132 ± 7%, 135 ± 8%, 131 ± 9% in NT, DI and ND respectively, p < 0.001 ANOVA). Night PPamp was similar in each group and lower than day PPamp (123 ± 7%, 124 ± 6% and 123 ± 7%, p = 0,11). However PPamp was correlated with heart rate (R2 = 0,36, p < 0.001). After adjustement for heart rate changes, PPamp did not differ during day and night in the 3 groups. Conclusions: After heart rate correction, cBP seems to vary in parallel to peripheral blood pressure during the day in normotensive, dipper hypertensive and non-dipper hypertensive.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.104 | 0.030 |
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".