Yan Maria, Bustos Samyd S, Kuruoglu Doga, Manrique Oscar J, Tran Nho V, Sharaf Basel A, Harless Christin A, Martinez-Jorge Jorys, Forte Antonio J, Nguyen Minh-Doan T
From the Divisions of Plastic and Reconstructive Surgery, Mayo Clinic Rochester and Mayo Clinic Jacksonville.
Plast Reconstr Surg. 2022 Oct 1;150(4):723e-730e. doi: 10.1097/PRS.0000000000009536. Epub 2022 Jul 22.
Many insurance companies in the United States rely on the Schnur sliding scale to predict resection weights to determine medical necessity for breast reduction surgery. Accurate methods to predict resection weights are needed to avoid insurance denials. The authors compared the accuracy of formulas such as the Schnur, Appel, Descamps, and Galveston scales in predicting resection weights, and assessed whether they influence insurance coverage decision.
A retrospective review of bilateral reduction mammaplasty procedures from June of 2017 to June of 2019 was performed at the Mayo Clinic, Rochester. Oncoplastic reduction operations were excluded. The accuracy of each formula-based estimate was evaluated with linear regression analysis.
One hundred fifty-four patients (308 breasts) were reviewed. The Schnur scale had low correlation with actual resection weight ( r2 = 0.381; b1 = 1.153; p < 0.001). The Appel scale was the most accurate ( r2 = 0.642; b1 = 1.01; p < 0.001), followed by the Descamps ( r2 = 0.572, b1 = 0.934, p < 0.001) and Galveston ( r2 = 0.672; b 1 = 0.654; p < 0.001) scales. The Appel, Descamps, and Galveston scales were more accurate for resection weights of 500 g or greater, body mass index greater than 30 kg/m², and patients younger than 50 years. For resection weights of 500 g or greater, the median difference between the estimated and actual resection weight for the Schnur, Appel, Descamps, and Galveston scales was -211.4 ± 272.3, -17.5 ± 272.3, -9.6 ± 229.5, and -99.2 ± 238.5 g, respectively. No scale was accurate for resection weights less than 500 g. Insurance reimbursement was denied in 15.56 percent of patients; of these, 23 percent had resection weights less than 500 g. The Schnur scale overestimated the resection weights in 28.9 percent of patients.
The Schnur scale is a poor predictor of breast resection weight. The Appel scale is the most accurate estimator, especially in the young and obese population with larger resections.
CLINICAL QUESTION/LEVEL OF EVIDENCE: Diagnostic, I.
美国许多保险公司依靠施努尔（Schnur）量表来预测切除重量，以确定乳房缩小手术的医疗必要性。需要准确的方法来预测切除重量，以避免保险拒赔。作者比较了施努尔、阿佩尔（Appel）、德康普斯（Descamps）和加尔维斯顿（Galveston）等量表在预测切除重量方面的准确性，并评估它们是否会影响保险覆盖范围的决定。
对罗切斯特梅奥诊所2017年6月至2019年6月的双侧乳房缩小整形手术进行回顾性研究。排除肿瘤整形手术。通过线性回归分析评估每个基于公式的估计的准确性。
共回顾了154例患者（308侧乳房）。施努尔量表与实际切除重量的相关性较低（r2 = 0.381；b1 = 1.153；p < 0.001）。阿佩尔量表最准确（r2 = 0.642；b1 = 1.01；p < 0.001），其次是德康普斯量表（r2 = 0.572，b1 = 0.934，p < 0.001）和加尔维斯顿量表（r2 = 0.672；b1 = 0.654；p < 0.001）。阿佩尔、德康普斯和加尔维斯顿量表在预测切除重量500克或以上、体重指数大于30kg/m²以及年龄小于50岁的患者时更准确。对于切除重量500克或以上的情况，施努尔、阿佩尔、德康普斯和加尔维斯顿量表估计的切除重量与实际切除重量的中位数差异分别为-211.4±272.3、-17.5±272.3、-9.6±229.5和-99.2±238.5克。对于切除重量小于500克的情况，没有一个量表是准确的。15.56%的患者被拒绝保险赔付；其中，23%的患者切除重量小于500克。施努尔量表在28.9%的患者中高估了切除重量。
施努尔量表对乳房切除重量的预测效果不佳。阿佩尔量表是最准确的估计方法，尤其是在切除量较大的年轻和肥胖人群中。
临床问题/证据水平：诊断性，I级
