Prevalence and Severity of Chronic Pain in Patients Receiving Mastectomy with Alloplastic Immediate Breast Reconstruction: A Survey Study
Bibliographic record
Abstract
Introduction: Breast cancer is the most frequently diagnosed cancer worldwide. For those undergoing mastectomy, the choice of alloplastic immediate breast reconstruction (IBR) is increasingly favored. Post-operative chronic pain is an important consideration in this decision, but there is a paucity of data for those undergoing alloplastic IBR. We sought to examine the prevalence, severity, and risk factors for the development of chronic pain in this cohort using validated patient-reported outcome measures. Methods: A cross-sectional survey study was conducted among patients receiving mastectomy with alloplastic IBR. Participants completed 3 surveys querying chronic pain, specifically the Breast Cancer Pain Questionnaire (BCPQ), Brief Pain Inventory (BPI), and BREAST-Q. Participant medical records were reviewed for demographic and surgical variables. Results: A total of 118 patients participated in the study—a response rate of 33.6%. Chronic pain prevalence was high (52.5%), and only 29.0% of these patients had consulted a physician regarding their pain. Among those reporting chronic pain ( n = 62), the median severity of pain was 3.1 on an 11-point scale. Chronic pain was associated with radiation ( p = .018), bilateral reconstruction ( p = .05), worse emotional health ( p = .0003), less self ( p = .022), and sexual confidence ( p = .044). Inter-tool reliability was high, with no significant difference in responses between the 3 surveys. Conclusion: In this cohort, chronic pain is supported as a significant concern among patients who have undergone mastectomy with alloplastic IBR. Given the burden of chronic pain, there is an opportunity to intervene with preventative measures and support for its management.
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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 | 0.003 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".