Reduction of Negative Appendectomy Rate Clinical Trial
Official title:
Evaluation of Diagnostic Algorithm for Suspected Acute Appendicitis
The diagnosis of acute appendicitis remains a challenge in daily clinical practice. The high
incidence of appendicitis drives the need to reduce morbidity and unnecessary costs due to
negative appendectomies. The aim of the present observation study is to evaluate a
diagnostic and therapeutic algorithm for suspected acute appendicitis.
The investigators believe that this diagnostic algorithm helps to simultaneously avoid
unnecessary operations, costs and radiation exposure.
This prospective observation study will be performed in the university hospital Frankfurt
with a 24-h emergency service, with surgery and radiology readily available. The data will
be compiled on patients older than 18 years who will be admitted to the emergency unit with
suspected appendicitis.
During the study period, the clinical workflow is standardized. In all cases a resident of
surgery and/or consultant surgeon clinically evaluate and perform an ultrasound scan on all
patients with suspected appendicitis. With the use of clinical and laboratory results the
physician (surgeon) will calculate the Alvarado Score and depending on the result the next
diagnostic steps or the treatment will be chosen. Additionally, the department of gynecology
of the university hospital routinely evaluate all women of childbearing age. Upon other
terms following variables will be collected: age, gender, white blood cells (WBC),
C-reactive protein (CRP), Alvarado Score, visuell pain scale, CT scan results, pathologic
findings, time between admission and operation, operation procedure, treatment and diagnosis
of patients without operation, length of hospital stay, and 30-day complication rate.
Furthermore, there will be a follow-up of all patients (with and without operation) after 30
days and 6 months.
The investigators assume that the use of a diagnostic and therapeutic algorithm reduces
unnecessary negative appendectomies and optimizes the duration of the hospital stay and the
costs.
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Observational Model: Cohort, Time Perspective: Prospective