1042 Sleep Characteristics In Ehlers Danlos Patients With Hypermobile Type: A Polysomnographic Study
Bibliographic record
Abstract
Abstract Introduction Ehlers-Danlos syndrome (EDS) is an heritable collagen disorder with various multisystemic clinical manifestations affecting primarily skin, ligaments and joints, blood vessels and internal organs. The clinical spectrum is very large from mild skin and joint hypermobility to severe physical disability. Patients with Ehlers-Danlos syndrome often complain of poor sleep quality and fatigue with impaired quality of life. The purpose of this study was to assess any objective sleep disturbances in EDS by polysomnography. Methods In this case-control study, we included 47 patients EDS type III (hypermobile type) (29 F et 18 M) which were one to one strictly matched to 47(29 F et 18 M) controls according to sex, age, and BMI. Participants underwent level-1 polysomnography for a complete sleep study. Results The two group were strictly similar for age and BMI (mean age 29.3 ± 9.2 years, BMI 23.3 ± 4.4 kg/m²). Total Sleep time (TST) was significantly reduced in EDS (343.7 ± 69.3 min versus 395 ± 74.8 min; F= 11.9; p< 0.01). Sleep quality was significantly impaired, with a decreased Sleep efficiency (SE): 74.4 ± 10.5 versus 90.2 ± 7.8 F= 68.5; p< 0.001), an increased wake after sleep onset (WASO) time (116.5 ± 45.7 min versus 43.3 ± 36.8 min; F= 73.2; p <0.01) and micro arousal index (14.8 ±7.8 versus 6.5 ±4.3; F= 41.2; p<0.01). We also found a significant reduction of slow wave sleep length, but REM sleep was not affected. The apnea-hyponea index (IAH) and periodic leg movement index (PLMI) were higher in EDS patients (IAH: 10.8±4.8 versus 5.8±3.9; F= 30.4; p<0.01 et PLMI: 4.5 ±4.6 versus 2.6± 2.5; F= 6; p<0.01). In patients with EDS type III, the prevalence of OSA (AHI>10/hour) was 75% versus 7.1 % in the control group (OR 5.1 (95% CI 2.3 to 14.7); p<0.001). Conclusion PSG may help in better understanding the diagnosis and treatments of EDS patients. Support
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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 | 0.001 |
| 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) | 0.003 | 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".