The effect of fluid overload on sleep apnoea severity in haemodialysis patients
Bibliographic record
Abstract
As in heart failure, obstructive and central sleep apnoea (OSA and CSA, respectively) are common in end-stage renal disease. Fluid overload characterises end-stage renal disease and heart failure, and in heart failure plays a role in the pathogenesis of OSA and CSA. We postulated that in end-stage renal disease patients, those with sleep apnoea would have greater fluid volume overload than those without.End-stage renal disease patients on thrice-weekly haemodialysis underwent overnight polysomnography on a nondialysis day to determine their apnoea-hypopnoea index (AHI). Extracellular fluid volume of the total body, neck, thorax and right leg were measured using bioelectrical impedance.28 patients had an AHI ≥15 (sleep apnoea group; OSA:CSA 21:7) and 12 had an AHI <15 (no sleep apnoea group). Total body extracellular fluid volume was 2.6 L greater in the sleep apnoea group than in the no sleep apnoea group (p=0.006). Neck, thorax, and leg fluid volumes were also greater in the sleep apnoea than the no sleep apnoea group (p<0.05), despite no difference in body mass index (p=0.165).These findings support a role for fluid overload in the pathogenesis of both OSA and CSA in end-stage renal disease.
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 | 0.003 |
| 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".