Sleep apnea syndrome, inflammation and oxidative stress in hemodialysis patients
Bibliographic record
Abstract
Abstract Introduction: Sleep apnea syndrome (SAS) is an established cardiovascular risk factor in the general population related to inflammation and oxidative stress and is very common among hemodialysis patients. Cardiovascular disease and its complications is the main cause of death among hemodialysis patients. The aim of the present study was to investigate the role of SAS in the promotion of inflammation and oxidative stress and thus in the augmentation of cardiovascular risk in hemodialysis patients. Methods: Thirty‐seven hemodialysis patients underwent an overnight full polysomnography study. The following morning blood samples were obtained and TNF‐α (tumor necrosis factor‐α), IL‐6 (interleukin‐6), MPO (myeloperoxidase), and oxLDL (oxidized low density lipoprotein) were measured. Findings: We investigated the correlation of patients' markers of inflammation and oxidative stress with their sleep parameters (total sleep time, AHI, apnea/hypopnea index; RDI, respiratory disturbance index; DI, desaturation index, mean and minimum SpO2 and percentage of sleep time with SpO2 < 90%). TNF‐α correlated positively with BMI (r = 0.510, P < 0.0001) and total sleep time (r = 0.370, P = 0.027). IL‐6 correlated positively with age (r = 0.363, P = 0.027), AHI (r = 0.385, P = 0.018), DI (r = 0.336, P = 0.042) and percentage of sleep time with SpO2 < 90% (r = 0.415, P = 0.012) and negatively with mean SpO2 (r = −0.364, P = 0.027). Myeloperoxidase correlated positively with AHI (r = 0.385, P = 0.018), DI (r = 0.380, P = 0.02) and percentage of sleep time with SpO2 < 90% (r = 0.388, P = 0.019). Finally, oxLDL correlated positively with BMI (r = 0.443, P = 0.007), AHI (r = 0.395, P = 0.015), RDI (r = 0.328, P = 0.048) and total sleep time with SpO2<90% (r = 0.389, P = 0.019). Conclusions: These results indicate that, in hemodialysis patients, the severity of SAS and nocturnal hypoxia correlated positively with markers of inflammation and oxidative stress.
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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 | 0.000 | 0.001 |
| 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".