Contribution of Obstructive Sleep Apnoea to Cognitive Functioning of Males With Coronary Artery Disease: A Relationship With Endocrine and Inflammatory Biomarkers
Bibliographic record
Abstract
Introduction Our exploratory study aimed to determine whether obstructive sleep apnoea (OSA) could affect cognitive functioning in males with coronary artery disease (CAD), and whether such impact could be associated with changes in thyroid hormones and inflammatory marker regulation on cognitive functioning. Method We evaluated different endocrine and inflammatory biomarkers, including free triiodothyronine [fT3], free tetraiodothyronine [fT4], N-terminal pro-B-type natriuretic peptide [NT-pro-BNP], and high-sensitivity C-reactive protein [hs-CRP] serum levels in 328 males ( x¯ = 57 ± 10 years), undergoing cardiac rehabilitation after an acute coronary event. Participants underwent full-night polysomnography and were classified in mild/non-OSA (n = 253) and OSA (n = 75) according to an apnoea-hypopnoea index ≥ 15 event/h. Cognitive functioning testing included the Digit Span Test, Digit Symbol Test (DSST), and Trail Making Test. Analyses of variance assessed the impact of OSA on cognitive functioning and possible relationships of fT3/fT4, NT-pro-BNP and with hs-CRP on cognitive measures. Results Significant group (OSA, mild/non-OSA) × NT-pro-BNP (<157.0 vs. ≥157.0, ng/L) interactions were found for the DSST raw score (F(2,324) = 3.58, p = 0.014). Decomposition of interactions showed that the DSST scores of the OSA group with NT-pro-BNP ≥ 157.0 ng/L (M = 33.2; SD = 8.1) were significantly lower, p = 0.031, than those of the mild/non-OSA with NT-pro-BNP < 157.0 ng/L (M = 37.7; SD = 8.9). Conclusion These findings indicate that males with OSA and clinically elevated NT-pro-BNP levels experienced inferior psychomotor performance compared to those without OSA and reduced NT-pro-BNP levels.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".