Investigating Post-treatment Breast Pain Severity in Breast Cancer Patients and Its Correlation with Serum Vitamin D and hs-CRP Levels
Bibliographic record
Abstract
Background: Current data indicate that serum vitamin D and susceptible C-reactive protein (hs-CRP) levels, both indicative of the inflammatory state, have the potential to predict the onset and severity of chronic pain. Therefore, the objective was to assess the intensity of pain experienced after breast cancer treatment and its relationship with these two parameters. Method: In this cross-sectional study between 2019 and 2021, 201 patients were enrolled. The McGill Pain Questionnaire was employed to evaluate localized pain intensity at the site six months after the conclusion of cancer treatments. Patients were stratified based on the type of breast surgery, with or without a tissue expander, axillary region surgery, chemotherapy treatment, radiotherapy treatment, serum vitamin D levels, serum hs-CRP levels, and pain intensity. Data analysis was performed using SPSS 21 software with a significance level set at 0.05. Results: Among the patients, 67.6% (136 individuals) reported mild pain, 31.3% (63 individuals) reported moderate pain, and 1% (2 individuals) reported severe pain. The results of this study demonstrated a positive correlation between high serum hs-CRP levels and increased pain intensity, with serum marker levels being higher in patients experiencing more severe pain compared with those with milder pain. However, no statistically significant association was observed between various serum concentrations of vitamin D and pain intensity (P = 0.12). Conclusion: Elevated levels of inflammatory factors, such as hs-CRP, are linked to a higher likelihood of developing chronic post-surgical pain.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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 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".