Impact of kidney transplantation on sleep apnoea in patients with end-stage renal disease
Bibliographic record
Abstract
BACKGROUND: Sleep apnoea is common in patients with end-stage renal disease. Although individual case reports have described an improvement in sleep apnoea following kidney transplantation, there have been no longitudinal studies of a case series to determine what proportion of patients with sleep apnoea improve. METHODS: Dialysis-dependent patients awaiting kidney transplantation and pre-dialysis patients with an identified living donor kidney had overnight polysomnography, which was repeated several months after successful kidney transplantation. Patients were divided into apnoeic and non-apnoeic groups based on an apneoa-hypopnoea index (AHI) > 10/h during pre-transplant polysomnography and, following transplantation, apnoeic patients were further divided into responders and non-responders based on >50% reduction in AHI and/or AHI < 10/h. RESULTS: Eighteen patients (11 men, 7 women), aged 27-65, were studied. Pre-transplant sleep apnoea was present in 11 of 18 (61%) patients. Although transplantation was associated with a significant reduction in blood urea nitrogen and serum creatinine, there were no significant changes in AHI (pre vs post: 20.2 +/- 15.1 vs 23.5 +/- 21.3). Among the 11 apnoeic patients, only three met the criteria for a significant improvement ('responder'). There were no patient characteristics, sleep apnoea indices or renal function changes that distinguished responders from non-responders. CONCLUSIONS: Sleep apnoea improves in a minority of patients with end-stage renal disease following successful kidney transplantation. Specific determinants of improvement were not identified.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".