CHARACTERIZATION OF CHRONIC PAIN IN WOMEN SUBMITTED TO BREAST CANCER TREATMENT
Bibliographic record
Abstract
Objective: The aim of this study was to characterize chronic pain in women undergoing surgical treatment for breast cancer. Methods: This is a cross-sectional, retrospective, hospital-based study. All breast cancer patients undergoing clinical follow-up at a referral hospital in central Brazil were screened. Women with chronic pain after surgical treatment of breast cancer, defined by the presence of pain after 3 months of surgery, were included in the study. The questionnaires were applied by the responsible researcher in the form of an interview, which took place in a dedicated office. The McGill Pain Questionnaire (MPQ) and the visual analog scale (VAS) were used. Results: In all, 99 patients were interviewed, of which 46 were included in the study. Most patients were between 50 and 59 years old (39.1%), were married (45.7%), were housewives (58.7%), and had completed high school (45.7%). Arterial hypertension was the most prevalent clinical comorbidity (41.3%), followed by diabetes mellitus (13.0%). A total of 45 (97.8%) patients underwent sentinel lymph node biopsy, but 22 (47.8%) required axillary lymphadenectomy for some oncological reason; 35 (76.0%) patients underwent chemotherapy (neoadjuvant or adjuvant), and 40 underwent radiotherapy (87.0%). According to the VAS, the mean pain intensity was 5.5 (±2.6). Most patients reported worsening pain with movement, with 26 (52.2%) “sometimes”, and another 14 (30.4%) “always”. In the MPQ, there was a predominance of the sensory domain among the characteristics of chronic pain. Relaxation techniques (52.2%), stretching (50.0%) and deep breathing (47.8%) were the most mentioned therapeutic measures. Drug treatment was reported by 21 (45.7%) women and acupuncture by only one. Conclusion: In the analyzed population, chronic pain was observed with moderate intensity and with a predominance of sensitive characteristics according to the MPQ. The development of strategies for prevention, early diagnosis, and multidisciplinary treatment can help reduce chronic pain in breast cancer survivors.
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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".