Neurocognitive impairment in Chinese patients with obstructive sleep apnoea hypopnoea syndrome
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Sleep-disordered breathing is known to be associated with impairment in cognitive function. The aim of this study was to characterize neurocognitive impairment in a cohort of Chinese patients with varying severities of obstructive sleep apnoea hypopnoea syndrome (OSAHS), and to develop a sensitive instrument for routine screening of cognitive impairment. METHODS: Eligible patients (n = 394) were categorized into a primary snoring group, and mild, moderate and severe OSAHS groups, based on assessment of AHI. The Montreal Cognitive Assessment (MoCA) and the Mini-Mental State Examination (MMSE) questionnaires were administered to assess cognitive function, and the correlations between questionnaire scores and clinical and polysomnographic parameters were further evaluated by stepwise multivariate regression. RESULTS: MoCA scores decreased progressively across the spectrum from primary snoring to severe OSAHS. Importantly, mild neurocognitive impairment as defined by a MoCA score <26 was more common in the moderate (38.6%) and severe (41.4%) OSAHS groups than in the mild OSAHS (25.0%) and primary snoring (15.2%) groups. In contrast, MMSE scores were largely normal and comparable among all four groups. Evaluation of MoCA subdomains further revealed selective reduction in memory/delayed recall, visuospatial and executive function, and attention span in the severe OSAHS group compared with the other groups. Stepwise multivariate regression analysis demonstrated that MoCA scores correlated significantly with lowest oxygen saturation (L-SaO(2) ) and years of education. CONCLUSIONS: Neurocognitive impairment is common in patients with OSAHS. The MoCA is a brief and sensitive tool for the assessment of cognitive impairment in OSAHS patients, whose performance on the MMSE is in the normal range.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".