Caracterização dos padrões de dor, sono e alexitimia em pacientes com fibromialgia atendidos em um centro terciário brasileiro
Bibliographic record
Abstract
OBJECTIVES: Fibromyalgia (FM) is a complex syndrome that is characterized by lasting and diffuse chronic musculoskeletal pain, derived from non-inflammatory causes and classically associated with the presence of specific tender points. However, studies have highlighted other important symptoms associated with a lower quality of life (QOL) in FM, such as sleep disturbances and alexithymia. This study aimed to investigate the pain, sleep and alexithymia patterns of FM patients treated in a Brazilian tertiary center. METHODS: 20 patients with FM who were followed-up in the Rheumatology outpatient clinic of a Brazilian tertiary center (Faculdade de Medicina de São José do Rio Preto - FAMERP, São Paulo, Brazil) and 20 patients without FM from other outpatient services of the FAMERP completed a clinical and socio-demographic questionnaire, the Fibromyalgia Impact Questionnaire (FIQ), the Pittsburgh Sleep Quality Index (PSQI), the Toronto Alexithymia Scale (TAS-20) and the SF-36 (WHOQOL). RESULTS: The patients with FM presented worse performances in all QOL dimensions of the SF-36 and higher scores on the PSQI (p=0.01), and the TAS-20 (p=0.02). Patients with FM also scored significantly higher in all specific domains of PSQI and TAS-20. DISCUSSION: The present data were in accordance with literature, disclosing a worse performance of patients with FM on pain impact, sleep complains and more presence of alexithymia. CONCLUSION: Studies have disclosed the presence of important and frequently underdiagnosed symptoms beyond pain complaints in FM, such as sleep complaints and alexithymia, and a better knowledge of such disturbances might improve FM patients' approach and treatment.
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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 | 0.003 |
| 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) | 0.002 | 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".