0688 Nocturnal pain and its association with quality of life in women: data from the Epidemiologic Sleep Study (EPISONO)
Bibliographic record
Abstract
Abstract Introduction It is known that poor sleep is related to pain, even though this relationship is not fully understood. Women with pain present alterations in sleep pattern and reduced quality of life, but little is known about the negative effects of nocturnal pain on these outcomes. This study aimed to evaluate and compare the levels of anxiety, depression, and fatigue in women with pain during the night with those without pain. We hypothesize that pain perception is associated with worsening fatigue and mood outcomes. Methods This cross-sectional study used data from the 2007’s Epidemiological Study of Sleep (EPISONO). A total of 574 women aged 20-80 years participated in the EPISONO, and 244 women met the inclusion criteria of our study, 85 in the pain group and 171 in the control group. Participants were categorized into the pain group if they responded positively to the following questions: i) they generally had pain, according to the Pre-Sleep Questionnaire (PSQ), and ii) pain usually interfered with sleep 3 or more times a week, according to the Pittsburg Sleep Quality Index (PSQI). Participants who responded negatively to these questions were allocated to the control group. All of them underwent a full night laboratory polysomnography, and answered questionnaires related to fatigue, depression, anxiety, and quality of life. Results Significantly higher levels of fatigue (5.4 times), anxiety and depression were observed in the pain group, as well as significantly lower values in all domains of quality of life, compared to the control group. The presence of pain at night was also correlated with levels of anxiety and depression in the psychological (Rs=-0.463, -0.607, respectively) and social (Rs=-0.423, -0.438, respectively) domains of quality of life. Conclusion The presence of pain at night in women is related to a decrease in quality of life and can lead to worsening mood disorders and fatigue. Our results show the importance of investigating pain and its consequences, as well as the interference in women's sleep patterns. Support (if any) Associação Fundo de Incentivo à Pesquisa (AFIP), Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) - Finance Code 001, and Conselho Nacional de Pesquisa (CNPq).
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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 | 0.002 |
| 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) | 0.001 | 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".