Relationship of pharyngeal water content and jugular volume with severity of obstructive sleep apnea in renal failure
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: In patients with end-stage renal disease (ESRD), fluid overload may contribute to their high prevalence of obstructive sleep apnea (OSA) by increasing the amount of fluid displaced from the legs into the neck overnight, and possibly compressing the upper airway (UA). Indeed, in ESRD patients, the amount of overnight rostral fluid displacement from the legs is related to the frequency of apneas and hypopneas per hour of sleep (apnea-hypopnea index, AHI). We, therefore, hypothesized that in ESRD patients, the greater the UA-mucosal water content (UA-MWC) and internal jugular vein volume (IJVVol), the higher the AHI. METHODS: We studied 20 patients with ESRD on thrice weekly hemodialysis who had undergone diagnostic polysomnography (age 41.0 ± 12.3 years, with a body mass index (BMI) of 25.8 ± 6.3 kg/m(2) and an AHI of 20.2 ± 26.8). The leg fluid volume (LFV) was measured by bioelectric impedance. The IJVVol and MWC were measured by UA magnetic resonance imaging (MRI). RESULTS: The only significant independent correlates of the AHI were IJVVol (r = 0.801, P < 0.0001) and UA-MWC (r = 0.720, P = 0.0005) which together explained 72% of its variability. CONCLUSIONS: These data suggest that fluid overload via increased IJVVol, and UA-MWC, contributes to the pathogenesis of OSA in patients with ESRD. These findings help us to explain the high prevalence of OSA in ESRD patients, and attenuation of OSA in association with nocturnal dialysis. They also suggest the need for randomized trials to determine whether more aggressive fluid removal in ESRD patients will alleviate OSA.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 it