乳房再造术
患者满意度
医学
植入
外科
乳腺癌
内科学
癌症
作者
Minji Kim,Perri Vingan,Lillian Boe,Babak J. Mehrara,Carrie S. Stern,Robert J. Allen,Jonas A. Nelson
标识
DOI:10.1097/prs.0000000000011571
摘要
Background: Autologous breast reconstruction (ABR) may confer higher patient reported outcomes than implant breast reconstruction, but an in-depth examination of factors associated with satisfaction after ABR is lacking. We aimed to determine independent predictors of 1-year Satisfaction with Breasts after ABR and assess the importance of elective procedures on satisfaction. Methods: A retrospective analysis of patients who underwent abdominal-based ABR between 2010 and 2021 and completed the BREAST-Q Satisfaction with Breasts module at 1-year was performed. Elective procedures comprised of breast revision and nipple areolar complex (NAC) reconstruction. Results: 959 patients were included. Satisfaction with Breasts score improved from 53 (IQR: 44 to 64) preoperatively to 64 (53 to 78) at 1-year postoperatively (p<0.001). Factors significantly associated with decreased postoperative score included lower preoperative scores (β=0.19 [95% CI: 0.08, 0.31], p=0.001), older age (β=-0.17 [-0.34, -0.01], p=0.042), Asian race (versus White, β=-6.7 [-12, -1.7], p=0.008), and a history of psychiatric diagnoses (β=-3.4 [-6.2, -0.66], p=0.015). Patients who received radiation (β=-5.6 [-9.0, -2.3], p=0.001) or had mastectomy skin flap/nipple necrosis (β=-3.8 [-7.6, -0.06], p=0.046) also had significantly decreased scores. Satisfaction with Breasts significantly improved after breast revision procedures (54 [42 to 65] to 65 [54 to 78], p<0.001) and NAC reconstruction (58 [47 to 71] to 67 [57 to 82], p<0.001). Conclusion: Multiple independent patient and treatment level factors are associated with lower 1-year Satisfaction with Breasts following ABR. Elective procedures have the potential to improve satisfaction. Understanding these findings is imperative for optimizing clinical decision making and managing expectations.
科研通智能强力驱动
Strongly Powered by AbleSci AI