Correlation between degree of hypoxia and cognitive function,quality of life in brainwork patients with OSAHS
Bibliographic record
Abstract
Objective To investigate damage of cognitive function and quality of life( QOL) in brainwork patients with obstructive sleep apnea syndrome( OSAHS),and to analyze the relationship between degree of hypoxia and patients’ cognitive function and QOL. Methods 174 cases underwent polysomnography( PSG). According to the lowest degree of hypoxemia( LSa O2),the patients were divided into mild,moderate,severe and control group. Epworth sleepiness assessment scale( ESS),mini-mental state examination( MMSE) and Calgary sleep apnea quality of life questionnaire were adopted for evaluation. Results The degree of LSa O2 was significantly correlated with patients’ neck circumference and body mass index( BMI)( P 0. 05). The differences of ESS among these groups were statistically significant( all P < 0. 05); in the OSAHS groups,the heavier degree of hypoxia was,the higher the ESS scores were. The differences of MMSE scores of five dimensions and total MMSE scores among groups were statistically significant( all P < 0. 05). Among them,the differences in attention,computing power and language ability were the highest. Calgary sleep apnea QOL survey showed that the differences of SAQLI scores of four dimensions and total SAQLI scores among groups were statistically significant( all P < 0. 05),and those in social communication,emotional activities were the highest. Conclusion Hypoxia is the main reason affecting cognitive function and QOL in patients with OSAHS. Improving nocturnal hypoxia can improve their cognitive function and QOL.
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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 | 0.000 |
| 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".