Risk Factors for Surgical Site Infections After Single-Level Anterior Lumbar Interbody Fusion.
Academic Article
Overview
abstract
AbstractBackground: Anterior lumbar interbody fusion (ALIF) has become an increasingly popular and effective treatment modality for various conditions of the lumbar spine. However, complications after this procedure can be costly. Surgical site infections (SSIs) are one of these types of complications. The present study identifies independent risk factors for SSI after single-level ALIF to identify high-risk patients better. Patients and Methods: The American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database was queried to identify single-level ALIF patients from 2005 to 2016. Multilevel fusions and non-anterior approach procedures were excluded. Mann-Pearson χ2 tests analyzed categorical variables, whereas one-way analysis of variance (ANOVA) and independent t-tests analyzed differences in mean values of continuous variables. Risk factors for SSI were identified via a multivariable logistic regression model. A receiver operating characteristic (ROC) curve was generated utilizing the predicted probabilities. Results: A total of 10,017 patients met inclusion criteria; 80 (0.80%) had developed SSI and 9,937 (99.20%) had not. On multivariable logistic regression models, class 3 obesity (p = 0.014), dialysis (p = 0.025), long-term steroid use (p = 0.010), and wound classification 4 (dirty/infected) (p = 0.002) all independently increased the risk for SSI in single-level ALIF. The area under the receiver operating characteristic curve (AUROC; C-statistic) was 0.728 (p < 0.001), indicating relatively strong reliability of the final model. Conclusions: Several independent risk factors including obesity, dialysis, long-term steroid use, and dirty wound classification all increased risk for SSI after single-level ALIF. By identifying these high-risk patients, surgeons and patients can have more informed pre-operative discussions. In addition, identifying and optimizing these patients prior to operative intervention may help to minimize infection risk.
