Predictive scoring systems to differentiate between simple and complex appendicitis in children (PRE-APP study)

Several clinical prediction rules have been developed for preoperative differentiation between simple and complex appendicitis in children, as potential treatment strategies differ. This study aimed to externally validate applicable clinical prediction rules that could be used to differentiate between simple and complex appendicitis in children.

Potential clinical prediction rules were identified by a scoping review of the literature. Clinical prediction rules applicable in our daily practice were subsequently externally validated in a multicenter historical cohort consisting of 1 tertiary center and 1 large teaching hospital. All children (<18 years old) with histopathologically confirmed acute appendicitis between 2013 and 2020 were included. Test results of clinical prediction rules were compared to the gold standard of either simple or complex appendicitis consisting of predefined perioperative and histopathological criteria. Areas under the receiver operating characteristic curves were determined for the selected clinical prediction rules. Areas under the receiver operating characteristic curve >0.7 were considered acceptable and potentially useful.

In total, 31 clinical prediction rules were identified, of which 12 could be evaluated in our cohort consisting of 550 children. The main reason to exclude clinical prediction rules was the use of variables that were not routinely measured in our cohort. In our cohort, 208/550 (38%) were diagnosed with complex appendicitis according to the gold standard. Clinical prediction rules with areas under the receiver operating characteristic curve >0.7 were: Gorter (0.81), Bogaard (0.79), Bröker (0.79), Graham (0.77), Hansson (0.76), BADCF (0.76), and Eddama (0.75).

In this study, clinical prediction rules consisting of a combination of clinical and objective variables had the highest discriminative ability. External validation showed that 7 clinical prediction rules were potentially useful. Integration of these clinical prediction rules in daily practice is proposed to guide decision making regarding treatment strategies.