Does hypoxic burden predict cognitive impairment in obstructive sleep apnea?
Bibliographic record
Abstract
Introduction: Intermittent nocturnal hypoxemia is the underlying mechanism presumed to explain the pathophysiological link between obstructive sleep apnea (OSA) and cognitive impairment. As evidence supporting this hypothesis is scarce, we aimed to assess relationship between cognitive function in OSA and hypoxic burden, a novel and accurate parameter of nocturnal hypoxemia. Methods: Thirty consecutive patients, diagnosed with obstructive sleep apnea based on ambulatory polygraphy, underwent three different cognitive evaluation tests: Montreal Cognitive Assessment (MoCA)Test, Stroop Color and Word Test (SCWT) and Dysexecutive Questionnaire (DEX). After manual scoring, Somnolyzer-CReSS algorithm was used to assess hypoxic burden. A model of multiple linear regression was created, using age, education, AHI and hypoxemic indices as independent variables. Results: Mean age was 57.27±17.5 years, 43.3% were females, 20% had high degree education and 33.3% had familiar history of dementia. A half of population (n 16, 53.3%) had severe OSA (mean AHI was 41.18±24.8), mean CT90 was 22.26±21.8 % and mean hypoxic charge was 139.16±155.5 %. Mean MoCA was 22.34±4.6 and 80% of patients had cognitive impairment, defined as MoCA less than 26. In the regression model, a mild influence of OSA severity on BADS was observed (p 0.04, R2 0.14), mostly driven by disinhibition domain, and age slightly affected the performance in the C condition of SCWT (p 0.03, R2 0,16), whereas none of the hypoxic parameters had significant effect on cognitive function. Conclusions: cognitive impairment affects a significant proportion of patients with OSA; severity of OSA only partly explains this association, whereas our results do not support the theoretical influence of nocturnal hypoxemia on cognitive function.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".