Assessment of Pain and Associated Factors in Female Patients Undergoing Surgical Treatment for Breast Cancer: Cross-Sectional Study
Bibliographic record
Abstract
Introduction: Pain is a common complication following surgical treatment for breast cancer. This symptom may result from a combination of biological, psychological, and social factors, thereby requiring a comprehensive, multidimensional approach to assessment and management. The functional impact of postoperative pain is considerable, as it can interfere with activities of daily living and compromise limb mobility. Objective: To verify the prevalence of pain, characterize it and analyze the factors associated with its intensity in patients undergoing breast cancer surgical treatment. Method: Cross-sectional study conducted between March 2021 and March 2022, in Belém, Pará, Brazil. A structured questionnaire was used to collect sociodemographic, clinical, and lifestyle data from patients in the postoperative period of breast cancer surgery. Pain was qualitatively assessed using the McGill Pain Questionnaire. Multiple linear regression was performed to identify factors associated with pain intensity, using the general pain index from the McGill instrument as the dependent variable. A 5% significance level was adopted for all statistics. Results: Forty-eight patients post-breast cancer surgery were included, the mean age was 53.64±11.64 years, 85% had undergone chemotherapy, 58.3%, mastectomy and 62.5% were feeling pain at the time of the evaluation. Pain intensity was negatively associated with alcohol consumption (p = 0.04) and positively associated with physical inactivity (p = 0.02), presence of comorbidities (p = 0.02), lymph node positivity (p = 0.03), and postoperative duration (p = 0.03). Conclusion: It was observed that most patients presented acute and moderate pain in the postoperative period and its intensity was associated with lifestyle, clinical and surgical characteristics.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".