Impact of obstructive sleep apnea on cognition, mood, and fatigue: an MRI-based study
Bibliographic record
Abstract
Abstract Background Obstructive sleep apnea disrupts the normal sleep cycle and is associated with many adverse consequences such as cardiovascular disease, DM, psychological problems, depression, decreased cognitive function, reduced quality of life, structural brain changes, and fatigue. Purpose This work aimed to study the MRI structural brain changes and to assess the neurocognitive function, depression, and fatigue using multiple questionnaires (MoCA score, BDI-П, and FSS, respectively) in OSA patients. Methods We enrolled 30 patients > 18 years with moderate (severity groups І), severe (severity groups П), very severe or extremely severe OSA (severity groups Ш), and 10 control subjects that were matched. All patients and control subjects underwent full-night PSG. Patients underwent neuropsychological tests including the Montreal Cognitive Assessment, Beck’s Depression Inventory-II, and Fatigue Severity Scale (FSS) in addition to an MRI brain without contrast. Results The mean AHI among patients (56.7% were females and 43.3% were males) was 39.97 ± 20.26 event/h. Severity groups І (40% of studied patients), П (46.7%), and Ш (13.3%). Abnormal MRI findings (WMCs) were detected in 18 patients (60%), versus 4 subjects (40%) in the control group, showing no statistically significant difference, p = 0.300. Among different severity groups, the prevalence of abnormal MRI findings was 4 (33.3%), 11 (78.6%), and 3 (75%) patients in severity groups І, П, and Ш, respectively. There was a statistically significant difference between patients and control regarding affection of subcortical and corpus callosal regions, p = 0.007 and 0.38, respectively, but not periventricular or deep white matter hyperintensities. Montreal Cognitive Assessment, Beck’s Depression Inventory-II score, and Fatigue Severity Scale, all showed statistically significant differences between patient and control groups. There was a significant negative correlation between AHI and MoCA score and a significant positive correlation between AHI and BDI-П, and also between AHI and FSS, p = 0.005, 0.016, and 0.008, respectively. The Frontal lobe was the most affected lobe among our patients followed by the parietal lobe. The mean value of AHI in the group of patients with abnormal MRI findings was statistically significantly higher than that in the group with normal MRI findings (45.42 ± 19.29 versus 32.06 ± 19.82 event/h, respectively), p = 0.010. Comparing both groups showed: that the mean value of MoCA score in the group of patients with abnormal MRI findings was significantly lower than that in the group with normal MRI findings (17.89 ± 3.64 versus 24.08 ± 4.44, respectively), p < 0.001. Regarding both BDI-П and FSS, it was noted that the mean value in the group of patients with abnormal MRI findings was higher than that in the group with normal MRI findings (33.83 ± 7.94 versus 32 ± 7.39, and (58.39 ± 4.82 versus 55.17 ± 7.12 respectively), but this difference was not statistically significant, p = 0.529, p = 1.000, respectively. Conclusion There was no significant difference between patients and the control group regarding WMCs in general, but there was a significant difference regarding the presence of subcortical and corpus callosal white matter hyperintensities. The Frontal lobe was the most affected. Neurocognitive function, depression, and fatigue were significantly affected in OSA patients in comparison to the control group. OSA patients with WMCs had a significantly higher AHI and a significantly lower MoCA score.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".