Preoperative scoring system for prediction of extended resection during emergency surgery for acute appendicitis

Author:

Kobayashi Toshimichi1,Hidaka Eiji1,Ando Akitoshi1,Koganezawa Itsuki1,Nakagawa Masashi1,Yokozuka Kei1,Ochiai Shigeto1,Gunji Takahiro1,Sano Toru1,Tomita Koichi1,Tabuchi Satoshi1,Chiba Naokazu1,Kawachi Shigeyuki1

Affiliation:

1. Tokyo Medical University Hachioji Medical Center

Abstract

Abstract Purpose: Appendectomy is the primary treatment for acute appendicitis. However, extended resection (ER) may be required in difficult cases. Preoperative prediction of ER may identify challenging cases but remains difficult. We aimed to establish a preoperative scoring system for ER prediction during emergency surgery for acute appendicitis. Methods: This single-center retrospective study included patients who underwent emergency surgery for acute appendicitis between January 2014 and December 2022 and were divided into ER and appendectomy groups. Independent variables associated with ER were identified using multivariate logistic regression analysis. A new scoring system was established based on these independent variables. The discrimination of the new scoring system was assessed using the area under the receiver operating characteristic curve (AUC). The risk categorization of the scoring system was also analyzed. Results: Of the 179 patients included in this study, 12 (6.7%) underwent ER. A time intervalfrom symptom onset to surgery ≥4 days, retrocecal or retrocolic appendix, and the presence of an abscess were identified as independent preoperative predictive factors for ER. A new scoring system was established based on these three variables, and scores ranged from 0 to 6. The AUC of the scoring system was 0.877, and the rates of ER among patients in the low- (score, 0–2), medium- (score, 4), and high- (score, 6) risk groups were estimated to be 2.5%, 28.6%, and 80%, respectively. Conclusions: Our scoring system may help surgeons identify patients with acute appendicitis requiring ER and facilitate treatment decision-making.

Publisher

Research Square Platform LLC

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