Objectives: Pediatric appendicitis remains a challenging diagnosis in the emergency department (ED). Available risk prediction algorithms may contribute to excessive ED imaging studies. Incorporation of physician gestalt assessment could help refine predictive tools and improve diagnostic imaging decisions.

Methods: This study was a subanalysis of a parent study that prospectively enrolled patients ages 5 to 20.9 years with a chief complaint of abdominal pain presenting to 11 community EDs within an integrated delivery system between October 1, 2016, and September 30, 2018. Prior to diagnostic imaging, attending emergency physicians enrolled patients with ≤5 days of right-sided or diffuse abdominal pain using a Web-based application embedded in the electronic health record. Predicted risk (gestalt) of acute appendicitis was prospectively entered using a sliding scale from 1% to 100%. As a planned secondary analysis, we assessed the performance of gestalt via c-statistics of receiver operating characteristic (ROC) curves; tested associations between gestalt performance and patient, physician, and facility characteristics; and examined clinical characteristics affecting gestalt estimates.

Results: Of 3,426 patients, 334 (9.8%) had confirmed appendicitis. Physician gestalt had excellent ROC curve characteristics (c-statistic = 0.83, 95% confidence interval = 0.81 to 0.85), performing particularly well in the low-risk strata (appendicitis rate = 1.1% in gestalt 1%-10% range, negative predictive value of 98.9% for appendicitis diagnosis). Physicians with ≥5 years since medical school graduation demonstrated improved gestalt performance over those with less experience (p = 0.007). All clinical characteristics tested, except pain <24 hours, were significantly associated with physician gestalt value (p < 0.05).

Conclusion: Physician gestalt for acute appendicitis diagnosis performed well, especially in low-risk patients and when employed by experienced physicians.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8310728PMC
http://dx.doi.org/10.1111/acem.13931DOI Listing

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