Effect of CPAP therapy on kidney function in patients with obstructive sleep apnoea and chronic kidney disease: a protocol for a randomised controlled clinical trial
Bibliographic record
Abstract
INTRODUCTION: Obstructive sleep apnoea (OSA) is common in patients with chronic kidney disease (CKD) and may contribute to the progression of kidney disease either through direct effects of hypoxia on the kidney or indirectly through hypoxaemia-induced oxidative stress, endothelial dysfunction, inflammation, activation of the renin-angiotensin and sympathetic nervous systems, and hypertension. Treatment of OSA with continuous positive airway pressure (CPAP) improves many of these physiological abnormalities in patients with normal renal function, though to date there are no trials evaluating the effect of OSA treatment on kidney function in patients with CKD. The purpose of this study is to test the feasibility and efficacy of CPAP therapy in CKD patients with OSA. METHODS AND ANALYSIS: The study is a randomised, controlled, non-blinded, parallel clinical trial in which patients with established CKD are screened for OSA. Patients with OSA are randomised to either conventional medical therapy (control group) or medical therapy and CPAP (CPAP group) and followed for 1 year. The primary outcome is the change in estimated glomerular filtration rate. Secondary outcomes are the change in the urinary albumin/creatinine ratio, the Epworth Sleepiness Scale , Pittsburgh Sleep Quality Index and Kidney Disease Quality of Life questionnaire. ETHICS AND DISSEMINATION: Ethics approval has been obtained from the Conjoint Health Research Ethics Board (ID: REB15-0055). Results from this study will be disseminated through presentations at scientific conferences and publication in peer-reviewed journals. TRIAL REGISTRATION NUMBER: NCT02420184; Pre-results.
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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 | 0.052 | 0.051 |
| Meta-epidemiology (narrow) | 0.007 | 0.003 |
| Meta-epidemiology (broad) | 0.015 | 0.009 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.010 | 0.008 |
| Insufficient payload (model declined to judge) | 0.065 | 0.011 |
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".