29 External validation of the ACS NSQIP calculator for predicting SSI and its association with incisional hernia in post-midline laparotomy patients

Introduction Incisional hernia (IH) is a significant complication following midline laparotomy, with a global incidence ranging from 12.8 to 23.8% within 23.8 months of follow-up. This complication not only impacts patient morbidity and quality of life but also imposes a substantial economic burden, with annual costs in the United States reaching $4 billion. Surgical site infection (SSI) has been identified as a key risk factor for IH, as it compromises wound integrity and delays healing. Despite the availability of several predictive scales for IH, few incorporate SSI as a variable. The ACS NSQIP Surgical Risk Calculator, a tool designed to estimate postoperative complications, including SSI, has shown promise in various surgical contexts. This study aims to externally validate the ACS NSQIP calculator for predicting SSI and explore its association with IH in patients undergoing midline laparotomy. Methods A retrospective longitudinal diagnostic test study was conducted, adhering to the TRIPOD-IA guidelines. The study included patients over 18 years old who underwent midline laparotomy, either emergently or electively, between January 2015 and November 2022. Patients with incomplete records or those participating in other research protocols were excluded. The ACS NSQIP Surgical Risk Calculator, which incorporates 21 variables, was used to predict SSI risk. The primary outcome was the occurrence of SSI within 30 days post-surgery or up to 12 months for prosthetic implant surgeries. The secondary outcome was the association between SSI and IH, diagnosed clinically or via imaging with a minimum follow-up of two years. The study population was divided into risk groups based on predicted SSI risk, and calibration and discrimination analyses were performed to evaluate the calculator’s performance. Results A total of 1083 patients were analyzed, with 104 (13.21%) developing SSI. The ACS NSQIP calculator demonstrated good discrimination, with an area under the curve (AUC) of 0.88, and excellent calibration, as indicated by a Brier score of 0.072. The optimal cutoff for predicting SSI was 6.6, with a sensitivity of 78% and specificity of 92%. Patients with SSI had a significantly higher risk of developing IH, with an odds ratio of 5.9 (95% c.i.: 3.4–10.3). The calculator performed well in identifying high-risk patients, particularly in intermediate and low-risk groups, though it slightly overestimated SSI risk in high-risk patients. Conclusion The ACS NSQIP Surgical Risk Calculator is a reliable tool for predicting SSI in patients undergoing midline laparotomy, with good discrimination and calibration. The study identified an optimal risk cutoff of 6.6, which can help stratify patients into low- and high-risk categories for SSI. Furthermore, SSI was strongly associated with an increased risk of IH, highlighting the importance of SSI prevention in reducing IH incidence. These findings support the use of the ACS NSQIP calculator in clinical practice to improve patient outcomes and guide preventive strategies.