Addressing the Gray Zone in Affirmative Mastectomy

Kelsi Krakauer, Darius Balumuka, Ana Meza-Rochin, Katrina Rapp,Elizabeth White,Juliana E. Hansen

Annals of Plastic Surgery(2023)

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摘要
Background Surgical decision making in gender-affirming mastectomy (GAM) is based on a patient's classification using the Fischer scale. Fischer 1 patients are excellent candidates for periareolar (PA) approach and Fischer 3 patients almost exclusively undergo double incision with free nipple grafting (DIFNG). Fischer 2 patients are in a gray zone in which decision making is more challenging. In this patient population, periareolar approaches can lead to increased complication and revision rates but free grafting procedures seem excessive. We have created a treatment algorithm to address Fischer 2 patients and additionally developed a novel technique, the batwing, to provide patients with more options. Methods A retrospective chart review was undertaken to analyze the Fischer classification of all patients undergoing top surgery by a single surgeon at an academic institution from 2014 to 2021. The choice of surgical technique used as well as the outcomes of GAM among Fischer 2 patients was analyzed. Results Four hundred four patients underwent GAM, and 51 (11%) had Fischer 2 classification. The surgical techniques used were PA (27%), batwing (39%), nipple-sparing double incision (NSDI, 24%), and DIFNG (10%). Of those, 10% had major complications and 20% requested revision for contour irregularities. Major complication rates for PA, batwing, NSDI, and DIFNG were as follows: 2 of 14 patients (14%), 1 of 20 patients (5%), 1 of 12 patients (8%), and 1 of 5 patients (20%), respectively. The revision rate by technique was PA (36%), batwing (15%), NSDI (17%), and DIFNG (0%). Conclusions For Fischer 2 patients, batwing and NSDI techniques avoid the need for free nipple graft while providing better exposure, improved control of nipple-areolar complex position, and decreased rate of revision as compared with the PA technique. The complication rate was not significantly different. We present an algorithm accounting for Fischer grade, unique patient characteristics, and patient desires.
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gray zone
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