Sleep-Related Disorders in Patients with CKD and Kidney Transplant Recipients
Bibliographic record
Abstract
Sleep disorders such as insomnia, restless legs syndrome (RLS), and sleep apnea (SA) are common in patients with CKD. These conditions tend to become more prevalent and more severe as kidney function deteriorates and when a patient reaches ESKD. The prevalence of insomnia in the general population ranges from 4% to 29% compared with ( 1 ) 30%-67%, ( 2 ) 39%-54%, ( 3 ) 41%-79%, and ( 4 ) 9%-49% in patients with CKD, on hemodialysis, on peritoneal dialysis (PD), or in kidney transplant recipients (KTRs), respectively. RLS occurs in approximately 1%-15% of the general population compared with ( 1 ) 5%-18%, ( 2 ) 24%-33%, ( 3 ) 23%-64%, and ( 4 ) 6%-8% in patients with CKD, on hemodialysis, on PD, or in KTRs, respectively. Obstructive SA has been reported in ( 1 ) 40%-69%, ( 2 ) 25%-47%, ( 3 ) 9%-52%, and ( 4 ) 25%-30% in patients with CKD, on hemodialysis, on PD, or in KTRs, respectively. Fatigue is a complex symptom that has been reported in patients with CKD, ESKD, and in KTRs and can be associated with sleep disorders. Fatigue and sleep disorders have been associated with negative outcomes such as progression of CKD, increased risk of morbidity, mortality, and lower health-related quality of life. In this review, we highlight nonpharmacologic and pharmacologic options for treatment of these sleep disorders. Specifically, the diagnosis and evaluation, epidemiology, risk factors and associations, outcomes (such as CKD progression, morbidity, and mortality), treatment, and post-transplant outcomes for sleep disorders (insomnia, RLS, and SA) and fatigue will be discussed.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".