Effect of Intercostal Nerve Coaptation on Postoperative Pain in Implant-Based Breast Reconstruction: A Double-Blind, Randomized Controlled Pilot Study
Bibliographic record
Abstract
PURPOSE: Patients undergoing breast surgery may experience chronic postoperative pain in the breasts, upper extremities, and axillary regions, and no established methods for preventing this pain are available at present. This study aimed to investigate whether coaptation of the transected intercostal nerve can prevent the development of neuropathic and chronic breast pain after mastectomy in implant-based breast reconstruction. METHODS: A prospective, double-blind, randomized controlled trial was conducted by dividing patients who underwent implant-based breast reconstruction after mastectomy into a control group without nerve coaptation and an experimental group with nerve coaptation. Patient clinical information was collected, and a survey using the pain and quality of life scale was conducted at 6 and 12 months after surgery. RESULTS: Fifteen patients completed the study, including seven in the control group and eight in the experimental group. The two groups showed no significant differences in terms of clinical factors. The experimental group exhibited lower Short-Form McGill Pain Questionnaire scores than the control group at 6 and 12 months postoperatively, with a statistically significant difference at 6 months. Numerical Rating Scale and Present Pain Intensity scores for both groups were in the "no to mild" range throughout the study period, with no statistically significant differences between the groups. Although the difference in the BREAST-Q™ results did not reach statistical significance, the experimental group showed an improvement in the quality of life. CONCLUSION: Intercostal nerve coaptation after mastectomy in implant-based breast reconstruction may facilitate initial nerve recovery. Although trial results are needed to fully determine the clinical impact, our findings support the ongoing scientific and clinical efforts to use this technique.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".