In:
Langenbeck's Archives of Surgery, Springer Science and Business Media LLC, Vol. 406, No. 1 ( 2021-02), p. 141-152
Abstract:
The management of patients with suspected appendicitis remains a challenge in daily clinical practice, and the optimal management algorithm is still being debated. Negative appendectomy rates (NAR) continue to range between 10 and 15%. This prospective study evaluated the accuracy of a diagnostic pathway in acute appendicitis using clinical risk stratification (Alvarado score), routine ultrasonography, gynecology consult for females, and selected CT after clinical reassessment. Methods Patients presenting with suspected appendicitis between November 2015 and September 2017 from age 18 years and above were included. Decision-making followed a clear management pathway. Patients were followed up for 6 months after discharge. The hypothesis was that the algorithm can reduce the NAR to a value of under 10%. Results A total of 183 patients were included. In 65 of 69 appendectomies, acute appendicitis was confirmed by histopathology, corresponding to a NAR of 5.8%. Notably, all 4 NAR appendectomies had other pathologies of the appendix. The perforation rate was 24.6%. Only 36 patients (19.7%) received a CT scan. The follow-up rate after 30 days achieved 69%, including no patients with missed appendicitis. The sensitivity and specificity of the diagnostic pathway was 100% and 96.6%, respectively. The potential saving in costs can be as much as 19.8 million €/100,000 cases presenting with the suspicion of appendicitis. Conclusion The risk-stratified diagnostic algorithm yields a high diagnostic accuracy for patients with suspicion of appendicitis. Its implementation can safely reduce the NAR, simultaneously minimizing the use of CT scans and optimizing healthcare-related costs in the treatment of acute appendicitis. Trial registration ClinicalTrials.gov Identifier: NCT02627781 (December 2015)
Type of Medium:
Online Resource
ISSN:
1435-2443
,
1435-2451
DOI:
10.1007/s00423-020-02022-7
Language:
English
Publisher:
Springer Science and Business Media LLC
Publication Date:
2021
detail.hit.zdb_id:
1459390-7
