Appendiceal diameter as a predictor of appendicitis in children: improved diagnosis with three diagnostic categories derived from a logistic predictive model
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To develop and assess the performance of a diameter-based logistic predictive model and a derived 3-category interpretive scheme for the sonographic diagnosis of paediatric appendicitis.
Appendiceal diameters were extracted from reports of ultrasound examinations in children and young adults. Data were used to generate a logistic predictive model which was used to define negative, equivocal and positive interpretive categories. Diagnostic performance of the derived 3-category interpretive scheme was compared with simulated binary interpretive schemes.
Six hundred forty-one appendix ultrasound reports were reviewed with appendicitis present in 181 (28.2 %). Cut-off diameters based on the logistic predictive model were ≤6 mm = normal, >6 mm–8 mm = equivocal and >8 mm = positive with appendicitis present in 2.6 % (11/428), 64.9 % (72/111) and 96.1 % (98/102) of cases in each group. These cut-offs conferred 97.2 % accuracy with 17.3 % (111/641) of cases considered equivocal. Of the binary cut-offs, a 6 mm cut-off performed best with 91.6 % accuracy. AIC analysis favoured the logistic model over the binary model for prediction of appendicitis.
A 3-category interpretive scheme based on a logistic predictive model provides higher accuracy in the diagnosis of appendicitis than traditional binary diameter cut-offs. Inclusion of an equivocal interpretive category more accurately reflects the probability distribution of prediction of appendicitis by ultrasound.
• Three diameter categories outperform a 6-mm cut-off to diagnose appendicitis
• Three categories allow more confident exclusion of appendicitis
• Three categories allow more confident diagnosis of appendicitis
• Three categories more accurately reflect the probability of appendicitis by ultrasound
KeywordsAppendicitis Ultrasound Sensitivity and specificity Child Organ size
The scientific guarantor of this publication is Andrew Trout, MD. The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article. The authors state that this work has not received any funding. Bin Zhang, PhD (co-author) kindly provided statistical advice for this manuscript. Institutional Review Board approval was obtained. Written informed consent was waived by the Institutional Review Board. Some study subjects or cohorts have been previously reported in a manuscript accepted for publication in the American Journal of Roentgenology. That manuscript did not explore or describe appendiceal diameter as a predictor of appendicitis. Methodology: retrospective, diagnostic or prognostic study, performed at one institution.
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