Bibliographic record
Abstract
Sleep apnea has been linked to excessive daytime sleepiness, depressed mood, hypertension, and cardiovascular disease in the general population. The prevalence of severe sleep apnea in the conventional thrice-weekly hemodialysis population has been estimated to be more than 50%. Sleep apnea leads to repetitive episodes of hypoxemia, hypercapnia, sleep disruption, and activation of the sympathetic nervous system. The hypoxemia, arousals, and intrathoracic pressure changes associated with sleep apnea lead to sympathetic activation, endothelial dysfunction, oxidative stress, and inflammation. Because sleep apnea has been shown to be widespread in the conventional dialysis population, it may be that sleep apnea contributes substantially to the sleepiness, poor quality of life, and cardiovascular disease found in this population. The causal links between conventional dialysis and sleep apnea remain speculative, but there are likely multiple factors related to volume status and azotemia that contribute to the high rate of severe sleep apnea in dialysis patients. Both nocturnal automated peritoneal dialysis and nocturnal hemodialysis have been associated with reduced severity of sleep apnea. Nocturnal dialysis modalities may provide tools to increase our understanding of the uremic sleep apnea and may also provide therapeutic alternatives for end-stage renal disease patients with severe sleep apnea. In conclusion, sleep apnea is an important, but overlooked, public health problem for the dialysis population. The impact of sleep apnea treatment in this high-risk population may include reduced sleepiness, better mood and blood pressure, and lowered risk of cardiovascular 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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".