Emotional Awareness Correlated With Number of Awakenings From Polysomnography in Patients With Myalgic Encephalomyelitis/Chronic Fatigue Syndrome—A Pilot Study
Bibliographic record
Abstract
INTRODUCTION: Unrefreshing sleep is one of the diagnostic criteria in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), which could be explained by sleep disorders, for example obstructive sleep apnea, reported in our previous study with polysomnography. Our previous findings also indicate difficulties in emotional regulation when measuring alexithymia by TAS-20 (Toronto Alexithymia Scale) and level of emotional awareness by LEAS (Level of Emotional Awareness Scale) in ME/CFS patients. However, the reasons for this are unknown. The purpose of this study was to investigate correlations between data from subjective emotional regulation and polysomnography. METHODS: Twenty-three ME/CFS patients (5 men and 18 women) of mean age 43, and 30 matched healthy controls (9 males and 21 women) of mean age 45, filled in TAS-20, LEAS, and Hospital Depression and Anxiety Scale (HADS). A polysomnography was performed on patients but not on healthy controls. Thus, values of normal population were used for sleep evaluation in ME/CFS patients. RESULT: There were significant differences between patients and controls in several aspects of emotional regulation, for example LEAS-self and LEAS-total. Seventy percent of the patients had increased numbers of awakenings (shifts from any sleep stage to awake), 22% had obstructive sleep apneas, and 27% had periodic limb movements. Correlation analysis showed that number of awakenings significantly correlated with LEAS-self and LEAS-total, p < 0.01, respectively. There were no other significant correlations. CONCLUSION: This pilot study demonstrated significant correlations between reduced emotional awareness and number of awakenings in polysomnography. Future studies with larger cohorts need to be conducted.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".