Optimizing Abdominoplasty Surgical Site Morbidity Profiling Through an Effective and Nationally Validated Risk Scoring System.

Massada, Karen E; Baltodano, Pablo A; Webster, Theresa K; Elmer, Nicholas A; Zhao, Huaqing; Lu, Xiaoning; Kaplunov, Briana S; Araya, Sthefano et al. · Ann Plast Surg · 2022

retrospective_cohort · Level III

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Abstract

Abdominoplasty complication rates are among the highest for cosmetic surgery. We sought to create a validated scoring system to predict the likelihood of wound complications after abdominoplasty using a national multi-institutional database. Patients who underwent abdominoplasty in the American College of Surgeons National Surgical Quality Improvement Program 2007-2019 database were analyzed for surgical site complications, a composite outcome of wound disruption, and surgical site infections. The cohort was randomly divided into a 60% testing and a 40% validation sample. Multivariable logistic regression analysis was performed to identify independent predictors of complications using the testing sample (n = 11,294). The predictors were weighted according to β coefficients to develop an integer-based clinical risk score. This system was validated using receiver operating characteristic analysis of the validation sample (n = 7528). A total of 18,822 abdominoplasty procedures were identified. The proportion of patients who developed a composite surgical site complication was 6.8%. Independent risk factors for composite surgical site complication included inpatient procedure (P < 0.01), smoking (P < 0.01), American Society of Anesthesiologists class ≥3 (P < 0.01), and body mass index ≥25.0 and ≤18.0 kg/m2 (P < 0.01). African American race was a protective factor against surgical site complications (P < 0.01). The factors were integrated into a scoring system, ranging from -5 to 42, and the receiver operating characteristic analysis revealed an area under the curve of 0.71. We present a validated scoring system for postoperative 30-day surgical site morbidity after abdominoplasty. This system will enable surgeons to optimize patient selection to decrease morbidity and unnecessary healthcare expenditure.

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