Correlation between oxidative stress and cognitive impairment in patients with obstructive sleep apnea hypopnea syndrome
Bibliographic record
Abstract
Background/Aim. It is necessary to find relevant oxidative stress markers for predicting the severity of obstructive sleep apnea-hypopnea syndrome (OSAHS), a sleep disorder-related respiratory disease. The aim of the study was to investigate if there is a correlation between oxidative stress and cognitive impairment in OSAHS patients. Methods. A total of 220 patients were divided into the group of snoring patients, the group with mild to moderate OSAHS, and the group with severe OSAHS according to polysomnography (PSG). Apnea-hypopnea index (AHI), oxygen desaturation index (ODI), and baseline data were monitored. Oxidative stress indices were measured by colorimetry from blood samples taken early in the morning. The patients were then divided into the group with normal cognition and cognitive impairment group based on minimental state examination (MMSE) and Montreal cognitive assessment (MoCA). Independent risk factors for cognitive impairment were analyzed by multi-variate logistic regression. The correlation between oxidative stress and cognitive impairment was analyzed by Pearson?s method. Receiver operating characteristic (ROC) curves made it possible to analyze the efficiency of oxidative stress combined with detection for assessing cognitive impairment in OSAHS patients. Results. The snoring group, mild to moderate OSAHS group, and severe OSAHS group had significantly different snoring loudness, body mass index (BMI), AHI, ODI, MoCA, and MMSE scores, and levels of malondialdehyde (MDA), glutathione peroxidase (GSH-Px), and superoxide dismutase (SOD) (p < 0.05). The cognitive impairment group and group with normal cognition had different BMI, GSH-Px, MDA, SOD, neuroglobin, hypoxia-inducible factor, AHI, and lowest nocturnal oxygen saturation (p < 0.05 or p < 0.01) levels. BMI, GSH-Px, MDA, SOD, neuroglobin, hypoxia-inducible factor, AHI, and lowest nocturnal oxygen saturation were independent risk factors for cognitive impairment. The MoCA and MMSE scores of cognitive impairment had positive correlations with GSH-Px and SOD but negative correlations with MDA (p < 0.05). The area under the ROC curve of GSH-Px, MDA, and SOD and their combination for prediction of cognitive impairment were 0.670, 0.702, 0.705, and 0.836, respectively. Conclusion. Oxidative stress may be the biochemical basis of cognitive impairment in OSAHS patients.
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 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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".