Cognitive impairment in patients with Idiopathic Pulmonary Fibrosis - Obstructive Sleep Apnea Overlap
Bibliographic record
Abstract
Idiopathic pulmonary fibrosis (IPF) is a specific form of chronic, progressive fibrosing interstitial pneumonia of unknown cause, occurring primarily in older adults, and limited to the lungs. It is commonly associated with various comorbidities, obstructive sleep apnea (OSA) being one of the most frequent. The overlap between IPF and OSA could lead to cognitive deficit. A simple tool like Montreal Cognitive Assessment (MoCA) can detect mild cognitive impairment. The aim of our study was to evaluate the cognitive function in stable IPF patients and to identify clinical risk factors for cognition impairment. Methods: We enrolled 23 patients with IPF, 30 with COPD and 17 age-matched healthy subjects. Patients completed MoCa questionnaire and were screened for OSA trough Epworth questionnaire and polygraphy. They were also evaluated for depression and anxiety with 3 specific scales. Results: Compared with control group, MoCA score was lower in IPF patients, but not as significantly decreased as in COPD group (MoCA score 27 pts. vs 24 pts. vs 21 pts., p=0, 003). 82.6% IPF patients were diagnosed with OSA and 63.15% exhibited a moderate-severe form of OSA. Furthermore, patients with MoCA scores <23 pts. also associated severe forms of OSA (AHI: 33, Epworth: 7) while patients with MoCA> 23 pts associated moderate OSA forms (AHI: 12, Epworth: 4). According to MoCA questionnaire, the most affected areas were working memory, language and visuospatial abilities. Conclusions: All patients with IPF should be screened for OSA. Mild cognitive impairment has a high prevalence among IPF patients. OSA could be an important risk factor for cognitive deficiency in this population.
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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) | 0.001 | 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".