The Interaction of Severe Obstructive Sleep Apnea Hypopnea Syndrome and Abdominal Obesity on Cognitive Function
Bibliographic record
Abstract
BACKGROUND: Both obstructive sleep apnea-hypopnea syndrome (OSAHS) and obesity are related to cognitive deficits, but the interaction effects of OSAHS and abdominal obesity on cognitive function are unclear. Thus, we performed this study to investigate this issue. METHODS: We recruited subjects who received polysomnography test, anthropometric measurements and cognitive function assessment and/or blood protein test. Correlations between apnea-hypopnea index (AHI) and cognitive function were assessed. Analysis of covariance was used to compare the differences in cognitive function between groups and detect the interactions of OSAHS and obesity on cognitive function. Multiple linear regression models were used to determine the associations between OSAHS and cognitive function. RESULTS: In total, 196 subjects with Montreal Cognitive Assessment (MoCA), 161 subjects with Symbol Digit Modalities Test (SDMT) and Trail making test, and 44 subjects with blood protein test were enrolled. Significant negative correlations between AHI and visuo-spatial and executive, language, delayed recall and total score of MoCA were observed. After adjusting for multiple confounding factors, subjects with severe OSAHS had significant lower delayed recall score and total score of MoCA, SDMT index, and Aβ40 protein level than those with non-severe OSAHS group. Severe OSAHS was independently negatively associated with delayed recall score and total score of MoCA, SDMT index, and Aβ40 protein level. An interactive effect of severe OSAHS and abdominal obesity on language score of MoCA was found. CONCLUSIONS: Severe OSAHS increased the risk of cognitive deficits. Interaction effect of severe OSAHS and abdominal obesity on language was seen.
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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 | 0.001 |
| 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".