Abnormal Spontaneous Brain Activity and Cognitive Impairment in Obstructive Sleep Apnea
Bibliographic record
Abstract
Purpose: This study aimed to explore the alterations in spontaneous brain activity in obstructive sleep apnea (OSA) using percent amplitude of fluctuation (PerAF) and investigate the relationship between abnormal spontaneous brain activity and cognitive impairment in OSA. Patients and Methods: Overall, 52 patients with moderate to severe OSA and 61 healthy controls (HCs) were eventually enrolled in this study. All participants underwent resting-state functional magnetic resonance (rs-fMRI) and T1-weighted imaging. The PerAF was calculated and compared between patients with OSA and HCs, with voxel level P < 0.001 and cluster level P < 0.05 corrected with Gaussian Random Field was be considered statistically different. A partial correlation analysis was used to assess the relationship between altered PerAF and clinical assessments in patients with OSA. Results: Compared to HCs, patients with OSA had significantly lower PerAF values in the right rectal gyrus and left superior frontal gyrus, but higher PerAF values in the right cerebellum posterior lobe and left middle frontal gyrus. The PerAF values of some specific regions in patients with OSA correlated with sleep efficiency and Montreal Cognitive Assessment scores. Additionally, support vector machine analysis showed that PerAF values in all differential brain regions could differentiate patients with OSA from HCs with good accuracy. Conclusion: Specific brain areas in OSA patients may exhibit aberrant neuronal activity, and these anomalies may be linked to decreased cognitive performance. This discovery offers fresh perspectives on these patients' neurocognition.
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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".