Commentary: Examination of Sensory Recovery of Breasts Reconstructed With Silicone Breast Implants After Nipple-Sparing Mastectomy
Bibliographic record
Abstract
Loss of sensation is common after mastectomy and negatively impacts patient-reported outcomes and satisfaction in alloplastic breast reconstruction following mastectomy.1,2 In this prospective cohort study, Sasaki et al examined the sensory recovery of breasts reconstructed with silicone implants after nipple sparing mastectomy by evaluating 9 breast areas.They examined recovery of tactile, pain, and temperature sensation on 31 patients with a follow up of 4 years while comparing different mastectomy incision types.The authors find that mastectomy significantly decreases all sensation modalities for the implant-reconstructed breast.3 Comparing incision types, tactile and pain sensation recovery was significantly better with peri-areolar as compared to inframammary fold (IMF) and lateral incisions in multiple breast regions (P < .05).It is worth noting, however, the incision was selected based on tumor localization, and the peri-areolar incision was used for resection of centrally based tumors.This is associated with minimal lateral dissection and trauma to the third through sixth lateral intercostal nerves, which provide sensation to most breast areas, including the nipple areolar complex (NAC), and are frequently overlooked and transected in a mastectomy.3 Although the peri-areolar incision might be associated with higher rate of NAC necrosis secondary to circumferential disruption of the blood supply, 4 this is not necessarily true with sensation, as nerves have the ability to regenerate.Transection of nerves close to the peri-areolar incision site gives them a shorter distance to recover to reinnervate the NAC as compared to IMF or lateral incision.This article, similar to others, found medial breast sensibility to be better 3 and discussed that preservation of the internal mammary artery perforator branch could be an indicator of better sensation given the abundance of anterior intercostal nerve perforators accompanying it.This reinforces a very important concept that is usually overlooked by studies assessing breast sensation-the mastectomy flap thickness.Thicker and more perfused flaps theoretically preserve their structural innervation by also preserving the superficial fascial system and efforts of optimizing mastectomy flap thickness when oncologically safe ORCID iDs
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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 | 0.002 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.030 | 0.017 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".