Predictors of Complications following Forehead Flaps for Nasal and Periorbital Reconstruction
Year: 2022
Type: article
Study design: Observational Study
Abstract: BACKGROUND: Forehead flaps are a workhorse for nasal reconstruction, but complications can occur in up to 30% of patients (1-2). Addressing complications can be challenging, and often necessitates revisionary procedures, which can cause significant burden to patients. Yet, there has been minimal research attempting to identify factors associated with complications and need for revisionary procedures (3). This study aimed to identify risk factors for complications, and provide clinicians a risk-stratification tool to facilitate shared decision-making. METHODS: This retrospective study included patients who underwent forehead flaps between 2007-2020. Patient-level and operative risk factors were compared between the cohorts with and without complications, and factors found to be associated with development of a complication with a p<0.10 were entered into a multivariate model as candidate variables (4). Multivariable logistic regression was conducted, with step-wise variable elimination to determine inclusion in the final model. Final model was tested with receiver operative characteristic (ROC) curve and validated using an internal bootstrapping approach (5). From the final regression, a risk-stratification scheme was developed, with creation of low, intermediate and high-risk groups. RESULTS: 197 patients underwent forehead flap reconstruction, with a mean age of 68.5 years. Mean follow-up time was 42 months. There were 50 (25.4%) patients who developed a complication, including impaired nasal function (18.8%), distal flap necrosis (5.1%), infection (2.5%), poor donor site healing (2.5%) wound dehiscence (2.0%), and flap congestion (1.5%). On univariate analysis, female sex, immunosuppression, prior radiotherapy, and larger resection area were associated with complications (p<0.05). On multivariable analysis, female sex (OR 3.89, p<0.001), hypoalbuminemia (OR 3.70, p=0.01), and prior wide local excision (OR 3.62, p=0.04) were predictors of complications. A clinical calculator was developed incorporating these risk factors, with a C-statistic of 0.85 after adjusting for optimism, indicating strong predictive value. When stratifying patients, there were 102 (51%) low-risk, 68 (35%) intermediate-risk, and 27 (14%) high-risk patients, corresponding with complication rates of 4.9%, 37%, and 74%, respectively (p<0.001) Intermediate-risk and high-risk categories increased the likelihood of any complication by 11-fold and 55-fold, respectively. Conclusion We conducted the most comprehensive review of risk factors for development of complications following forehead flap reconstruction. Among 197 patients undergoing forehead flaps, the overall complication rate was 25.4%, most commonly for impaired nasal function and distal flap necrosis. Female sex, preoperative hypoalbuminemia, prior excisions, and concomitant rib cartilage grafting were significant predictors of complications. Weighted variables were incorporated into a novel clinical calculator, which can be instantly implemented in the clinical setting to facilitate shared decision-making and preoperative planning. The present study findings will improve surgical expertise for forehead flap-based reconstruction for patients with facial cutaneous lesions. REFERENCES: 1. Paddack AC, Frank RW, Spencer HJ, Key JM, Vural E. Outcomes of paramedian forehead and nasolabial interpolation flaps in nasal reconstruction. Archives of Otolaryngology - Head and Neck Surgery. 2012;138(4):367-371. doi:10.1001/archoto.2012.69 2. Little SC, Hughley BB, Park SS. Complications with forehead flaps in nasal reconstruction. The Laryngoscope. 2009;119(6):1093-1099. doi:10.1002/lary.20243 3. Halani SH, Ma C, Pierce J, Sanniec K, Thornton JF. Nasal Reconstruction after Mohs Cancer Resection: Lessons Learned from 2553 Consecutive Cases. Plastic and reconstructive surgery. 2021;148(1):171-182. doi:10.1097/PRS.0000000000008098 4. Bursac Z, Gauss CH, Williams DK, Hosmer DW. Purposeful selection of variables in logistic regression. Source code for biology and medicine. 2008;3:17. doi:10.1186/1751-0473-3-17 5. Efron Tibshirani, Robert J., Bradley. An Introduction to the Bootstrap. Chapman & Hall; 1993.
Language: English
Subfield: Surgery
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,195
OpenAlex ID: W4320064167