Cognitive evolution of Alzheimer’s disease patients according to the serverity of obstructive sleep apnea
Bibliographic record
Abstract
Abstract Background To investigate the effect of OSA on the cognitive evolution of patients with AD. Method In this prospective, single‐center study (NCT02814045), patients with mild‐moderate AD with and without untreated OSA were evaluated at the baseline and after 12, 24 and 36 months of follow‐up. OSA was defined as an apnea‐hypopnea index (AHI) >15/h. The primary outcome was measured by the cognitive scores on the Alzheimer’s Disease Assessment Scale‐Cognitive subscale (ADAS‐cog) and Mini‐Mental State Examination (MMSE). Result The cohort included 146 patients with 125 validated PSGs, from which 40 patients were diagnosed as non‐OSA (32%) and 85 as OSA (68%). The median [IQR] age of the eligible individuals was 75.0 [72.0;80.0] years and the majority was composed of women (57.25%). In addition, the mean (SD) MMSE score at the baseline was 23.53 (2.23). In the ADAS‐cog score, the mean (SD) change at the 12 months of follow‐up was 2.97 (5.73) and 0.29 (5.65) for the non‐OSA and OSA group, respectively. The estimated mean (95%) difference between the groups was ‐2.76 (0.12 to 0.16) (p=0.033). No cognitive changes were observed at several cognitive domains evaluated. There was a cognitive decline along the 3 years of follow‐up according to the MMSE score (p<0.001) (Figure 1), but no differences between the groups were observed. Conclusion OSA was not associated with a worse cognitive evolution after 36 months of follow‐up. Further studies will be necessary to improve the understanding of the OSA impact on the cognitive evolution of AD patients.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".