DIALAPP: a prospective validation of a new diagnostic algorithm for acute appendicitis
- Purpose: 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.
Author: | Patrizia MalkomesORCiDGND, Franziska EdmaierGND, Juliane LieseORCiDGND, Alexander Reinisch-LieseORCiDGND, Hanan el YouzouriGND, Teresa SchreckenbachORCiDGND, Andreas M. BucherGND, Wolf Otto BechsteinORCiDGND, Andreas SchnitzbauerORCiDGND |
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URN: | urn:nbn:de:hebis:30:3-628357 |
DOI: | https://doi.org/10.1007/s00423-020-02022-7 |
ISSN: | 1435-2451 |
Parent Title (English): | Langenbeck's archives of surgery |
Publisher: | Springer |
Place of publication: | Berlin ; Heidelberg |
Document Type: | Article |
Language: | English |
Date of Publication (online): | 2020/11/19 |
Date of first Publication: | 2020/11/19 |
Publishing Institution: | Universitätsbibliothek Johann Christian Senckenberg |
Release Date: | 2023/01/31 |
Tag: | Acute appendicitis; Clinical trial; Diagnostic algorithm; Negative appendectomy rate; Risk-stratification |
Volume: | 406 |
Issue: | 1 |
Page Number: | 12 |
First Page: | 141 |
Last Page: | 152 |
Note: | Open Access funding enabled and organized by Projekt DEAL. |
HeBIS-PPN: | 507172612 |
Institutes: | Medizin |
Dewey Decimal Classification: | 6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit |
Sammlungen: | Universitätspublikationen |
Licence (German): | Creative Commons - Namensnennung 4.0 |