0499 Identifications of symptoms clusters by the Quebec Sleep Questionnaire in sleep apnea patients
Bibliographic record
Abstract
Abstract Introduction Sleep apnea (SA) patients may present different symptom clusters. The clinical importance of such clustering is supported by the differences in the incidence of cardiovascular diseases between hypersomnolent and non hypersomnolent patients. The Quebec Sleep Questionnaire (QSQ) has been elaborated 20 years ago that documents quality of life in SA patients by measuring the impact of the disease on five different domains (nocturnal and diurnal symptoms, hypersomnolence, emotions and social interactions). Previous cluster analyses took into account the frequency of typical SA symptoms. Many, but not all symptoms selected in these studies are addressed in the QSQ. The objective of this study is to determine if quality of life clusters can be identified using responses collected from the QSQ in SA patients. Methods A cluster analysis was completed in symptom scores collected from the QSQ+ Epworth scores in147 patients who filled in the questionnaire during its validation (75.5 % males, age: 53 ± 11 y, BMI: 30.4 ± 4.7 Kg.m2, AHI 31.3 ± 14.8 /h). For each item, patients were considered as symptomatic for scores ≤ 4 (the lowest the score the higher the impact) and for ESS > 10. Results Three clusters were identified: patients in cluster 1 (20.4 % of patients) can be identified as minimally symptomatic in each domain. In the cluster 2 (32.6 %), quality of life was mainly impacted by hypersomnolence with disturbed sleep. Patients in cluster 3 (46.9 %) reported important impacts on their quality of life in each domain of the QSQ. Gender, BMI and AHI did not differ between the three clusters. However, patients in cluster 1 were significantly younger than those of cluster 2 (50.5 ± 9.9 and 57.6 ± 11.9 years, respectively, p = 0.01). Conclusion Different clusters of quality of life can be identified by the QSQ in SA patients. These clusters seem to have close similarities with previously reported symptom frequency driven clusters. The relationship between quality of life symptom clusters and long-term clinical outcomes should be explored in a large prospective cohort of sleep apnea patients. Support (if any)
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".