Development of a nomogram for postoperative surgical site infections in patients undergoing bowel resection for Crohn's disease.

Autor: Lu B; Department of Anesthesiology, Nanjing Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, PR China., Zhang M; Department of Anesthesiology, Nanjing Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, PR China., Wang Z; Department of Anesthesiology, Nanjing Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, PR China., Zhang W; Department of Anesthesiology, Nanjing Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, PR China., Lu Y; Department of Anesthesiology, Nanjing Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, PR China., Gong J; Department of General Surgery, Nanjing Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, PR China., Wu Z; Department of Anesthesiology, Nanjing Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, PR China. Electronic address: wuzhifang1984@163.com., Ji Q; Department of Anesthesiology, Nanjing Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, PR China. Electronic address: qing_ji@nju.edu.cn.
Jazyk: angličtina
Zdroj: Clinics and research in hepatology and gastroenterology [Clin Res Hepatol Gastroenterol] 2024 Oct; Vol. 48 (8), pp. 102462. Date of Electronic Publication: 2024 Sep 12.
DOI: 10.1016/j.clinre.2024.102462
Abstrakt: Background: Surgical site infection (SSI) is a significant concern due to its potential to cause delayed wound healing and prolonged hospital stays. This study aims to develop a predictive model in patients with Crohn's disease.
Methods: We conducted single-factor and multi-factor logistic regression analyses to identify risk factors, resulting in the development of a logistic regression model and the creation of a nomogram. The model's effect was validated by employing enhanced bootstrap resampling techniques, calibration curves, and DCA curves. Finally, we investigated the risk factors for wall and intra-abdominal infections separately.
Results: 90 of 675 patients (13.3 %) developed SSI. Several independent risk factors for SSI were identified, including higher postoperative day one neutrophil count (p = 0.033), higher relative blood loss (p = 0.018), female gender (p = 0.021), preoperative corticosteroid use (p = 0.007), Montreal classification A1 and L2 (p < 0.05), previous intestinal resection (p = 0.017), and remaining lesions (p = 0.015). Additionally, undergoing strictureplasty (p = 0.041) is a protective factor against SSI. These nine variables were used to develop an SSI prediction model presented as a nomogram. The model demonstrated strong discrimination (adjusted C-statistic=0.709, 95 % CI: 0.659∼0.757) and precise calibration. The decision curve showed that the nomogram was clinically effective within a probability threshold range of 3 % to 54 %. Further subgroup analysis revealed distinct risk factors for wall infections and intra-abdominal infections.
Conclusion: We established a new predictive model, which can guide the prevention and postoperative care of SSI after Crohn's disease bowel resection surgery to minimize its occurrence rate.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2024 Elsevier Masson SAS. All rights reserved.)
Databáze: MEDLINE
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