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Breast Resection Weight Prediction In Reduction Mammoplasty: Is The Schnur Sliding Scale Reliable Or Can We Rely On Other Scales?
Maria Yan, MD, Samyd S. Bustos, MD, Doga Kuruoglu, MD, Antonio J. Forte, MD, PhD, MS, Minh-Doan T. Nguyen, MD, PhD, Christin A. Harless, MD, Nho V. Tran, MD, Jorys Martinez-Jorge, MD, Oscar J. Manrique, MD, FACS.
Mayo Clinic, Rochester, MN, USA.

PURPOSE:
Many insurance companies in the United States rely on the Schnur Sliding Scale (SSS) for predicting breast resection weight. The SSS value is compared with the pathologic reports to determine reimbursement of reduction mammoplasty. Surgeons may feel pressured to remove more tissue to meet the criteria for insurance coverage. There is a need to find an accurate estimation method for resection weight to avoid unforeseen coverage rejections.
The aim of this study is to compare the accuracy of predicted resection weight based on SSS as well as other formulas such as Galveston, Appel and Descamps.
METHODS:
A retrospective review of patients who underwent bilateral breast reduction surgery from July 2018 to June 2019 was performed at our institution. Oncoplastic surgeries were excluded. Linear regression models were used to compare formula-based prediction and actual resected weight.
RESULTS:
A total of 154 patients and 308 breasts were reviewed. Mean age was 44.8 17 years, mean BMI was 30.6 5 kg/m2. Grade 1 ptosis was present in 3.9% of patients, grade 2 in 64.5% and grade 3 in 30.9%. Mean nipple to sternal notch was 31 3.9 cm, and mean nipple to inframammary fold was 14.5 3 cm. SSS overestimated the resection weight in 24% (n=74). Only 42.9% of the variance in actual resection weight was explained by the SSS ((r2=0.43, b1=1.3 (1.12-1.46), p<0.0001). Galveston was the most accurate predictor for resection weight (r2=0.66, b1=0.6 (0.55-0.64, p<0.0001)), followed by Appel (r2=0.64, b1=1.01 (0.93-1.1, p<0.0001,)) and Descamps (r2=0.57, b1=0.94 (0.85-1.03), p<0.0001). These 3 formulas had better predictors for >500 gr breast resection. Galveston and Appel performed better in patients of age <50 years, whereas Descamps showed no statistical difference by age.
CONCLUSION:
SSS is a poor predictor of resection weight in breast mammoplasty as compared with the other scales. Estimates using published formulas such as Galveston, Apple and Descamps are more accurate predictors, particularly for larger resections. In addition, Galveston and Appel were better estimators for patients <50 years old. Inaccurate preoperative predictors of weight resection can potentially leave patients with uncovered bills especially when these weights are not achieved. Therefore, using an accurate method of predicting resection weight is required in order to prevent coverage challenges.


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