Abdominal subcutaneous fat thickness as a substitute for BMI in predicting complications in abdominally‐based autologous breast reconstruction. Issue 4 (15th March 2021)

• Record Type: Journal Article
• Authors: Dinis, Jacob; Junn, Alexandra; Shah, Rema; Allam, Omar; Mehta, Sumarth; Mozaffari, Mohammad Ali; Avraham, Tomer; Alperovich, Michael
• Is Part Of: Microsurgery. Volume 41:Issue 4(2021)
• Page Start: 341
• Page End: 347
• Publication Date: 2021-03-15
• Subjects: Microsurgery -- Periodicals; 617.05
• DOI: 10.1002/micr.30732
• Languages: English
• ISSNs: 0738-1085

Abstract

Abstract: Introduction: Patient selection for autologous tissue transfer for postmastectomy breast reconstruction often utilizes body mass index (BMI) to risk stratify patients, though it only estimates fat content and does not address fat distribution. This study aims to identify a measurement of abdominal subcutaneous fat thickness (ASFT) from preoperative computed tomography (CT) angiography imaging to better predict complications. Methods: A retrospective review of patients who underwent an abdominal microvascular free flap breast reconstruction was performed. The average of the bilateral distances from the lateral border of the rectus abdominus to the most proximal point of the dermis at the L4–L5 space was measured on preoperative imaging to estimate ASFT. This measurement was compared to BMI in regards to correlation with any complication, major or minor complications, and donor or recipient site complications. Statistical analysis utilized point‐biserial correlations and multivariable logistic regression analyses. Results: Three hundred and nine cases comprising a total of 496 breast reconstructions were identified. BMI did not correlate with any of the grouped complications, while ASFT correlated with occurrence of any complication ( p = .003), minor complications ( p = .001), and recipient site complications ( p = .001). Further analysis revealed ASFT is specifically correlated with fat necrosis ( p = .005). In independent multivariable regression models, both BMI ( p = .011) and ASFT ( p = .001) were significant predictors of fat necrosis. The ASFT model had a BIC of 335.42 compared to the BMI model with a value of 340.89, with smaller numbers representing more predictive models. Conclusion: Estimation of ASFT is easily performed and is a significantly better predictor of flap fat necrosis than BMI.