Non-dipping nocturnal blood pressure correlates with obstructive sleep apnoea severity in normotensive subjects and may reverse with therapy
Bibliographic record
Abstract
BACKGROUND: Obstructive sleep apnoea (OSA) is strongly associated with systemic hypertension, but there are limited data on the relationship with blood pressure (BP) in normotensive subjects. Here, we examined the relationship of OSA with nocturnal BP in a documented diurnal normotensive cohort, explored potential intermediate pathways and assessed the effects on BP of continuous positive airways pressure (CPAP) therapy. METHODS: , apnoea-hypopnoea index (AHI) 14 (interquartile range 5-26)). Urine and serum were assessed for markers of sympathetic activation, renin-angiotensin-aldosterone system activity, oxidative stress, endothelial function and systemic inflammation. In a subset of patients, 24-hour BP monitoring was repeated after CPAP therapy. RESULTS: Within this normotensive cohort, night-time systolic and diastolic BP and nocturnal BP dip were highest in the fourth OSA severity quartile (p<0.05). Nocturnal BP dip correlated with AHI (r=-0.327, p<0.05) and oxygen desaturation index (ODI) (r=-0.371, p<0.05), but only ODI was an independent predictor of BP dip (B=-0.351, p<0.01) and non-dipping status (B=0.046, p<0.05). Overnight urinary norepinephrine correlated with nocturnal systolic BP (r=0.387, p<0.01) with a trend towards correlation with systolic dipping (p=0.087). In 20 CPAP-treated patients, night-time systolic BP decreased (p<0.05) and mean nocturnal BP dip increased (p≤0.05). CONCLUSION: In this normotensive cohort, OSA severity was associated with higher nocturnal BP, which improved following CPAP therapy, and intermittent hypoxia was the most important OSA-related variable in this relationship.
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 | 0.000 | 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".