Effects of 3-month CPAP therapy on brain structure in obstructive sleep apnea: A diffusion tensor imaging study
Bibliographic record
Abstract
White matter (WM) fiber alterations in patients with obstructive sleep apnea (OSA) is associated with cognitive impairment, which can be alleviated by continuous positive airway pressure (CPAP). In this study, we aimed to investigate the changes in WM in patients with OSA at baseline (pre-CPAP) and 3 months after CPAP adherence treatment (post-CPAP), and to provide a basis for understanding the reversible changes after WM alteration in this disease. Magnetic resonance imaging (MRI) was performed on 20 severely untreated patients with OSA and 20 good sleepers. Tract-based spatial statistics was used to evaluate the fractional anisotropy (FA), mean diffusion coefficient, axial diffusion coefficient, and radial diffusion coefficient (RD) of WM. To assess the efficacy of treatment, 20 patients with pre-CPAP OSA underwent MRI again 3 months later. A correlation analysis was conducted to evaluate the relationship between WM injury and clinical evaluation. Compared with good sleepers, patients with OSA had decreased FA and increased RD in the anterior thalamic radiation, forceps major, inferior fronto-occipital tract, inferior longitudinal tract, and superior longitudinal tract, and decreased FA in the uncinate fasciculus, corticospinal tract, and cingulate gyrus ( P < 0.05). No significant change in WM in patients with post-CPAP OSA compared with those with pre-CPAP OSA. Abnormal changes in WM in untreated patients with OSA were associated with oxygen saturation, Montreal cognitive score, and the apnea hypoventilation index. WM fiber was extensively alteration in patients with severe OSA, which is associated with cognitive impairment. Meanwhile, cognitive recovery was not accompanied by reversible changes in WM microstructure after short-term CPAP therapy.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".