Alterations in upper airway cross-sectional area in response to lower body positive pressure in healthy subjects
Bibliographic record
Abstract
BACKGROUND: Fluid accumulation in the neck during recumbency might narrow the upper airway (UA) and thereby contribute to its collapse in patients with obstructive sleep apnoea (OSA). It is hypothesised that acute fluid shifts from the legs to the upper body in healthy subjects would increase neck circumference and reduce the cross-sectional area of the UA (UA-XSA). METHODS: In 27 healthy non-obese subjects of mean (SE) age 39 (3) years and body mass index 23.2 (0.6) kg/m2 studied while supine, leg fluid volume was measured using bioelectrical impedance, neck circumference using a mercury strain gauge and mean UA-XSA between the velum and the glottis using acoustic pharyngometry at end expiration. Measurements were made at baseline after which subjects were randomly assigned to a 5 min time control period or to a 5 min application of lower body positive pressure (LBPP) at 40 mm Hg by anti-shock trousers, separated by a 15 min washout period. Subjects then crossed over to the opposite arm of the study. RESULTS: Compared with control, application of LBPP significantly reduced leg fluid volume (p<0.001) and increased neck circumference (p<0.001), both at 1 min and 5 min, and reduced UA-XSA after both 1 min (-0.15 cm2; 95% CI -0.23 to -0.09, p<0.001) and 5 min (-0.20 cm2; 95% CI -0.33 to -0.09, p<0.001). CONCLUSION: In healthy subjects, displacement of fluid from the legs by LBPP causes distension of the neck and narrowing of the UA lumen. Fluid displacement from the lower to the upper body while recumbent may contribute to pharyngeal narrowing and obstruction to airflow in patients with OSA. This may have particular pathological significance in oedematous states such as heart and renal failure.
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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) | 0.000 | 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".