INTRODUCTION: Mild traumatic brain injury (mTBI) is an important public health issue, but France does not have a dedicated epidemiological surveillance system for mTBI. Data on Emergency departments (ED) of the OSCOUR network could be useful for setting up a dedicated mTBI surveillance system. However, the performance of potential algorithms based on ICD-10 codes for identifying cases of mTBI in OSCOUR has not been assessed. The objective of this study is to measure the performance of various potential algorithms, based on ICD-10 codes, for identifying mTBI ED visits in the OSCOUR database. MATERIAL AND METHODS: We performed a retrospective multicenter validation study of algorithms for identifying mTBI based on ICD-10 codes using the OSCOUR database. We calculated sensitivity, specificity, positive and negative predictive values of the various algorithms by using medical charts from ED visits as a reference source. Our study population consisted of a random sample of patients of all ages in France who visited one of the four ED from the OSCOUR network, which participated in our study in 2019. RESULTS: 5,185 medical charts were reviewed. Algorithms performance varied according to population characteristics, and none of the algorithms tested for the identification of mTBI cases achieved the minimum performance requirements (sensitivity and PPV ≥ 80%) over all age or sex groups. However, sub-group analyses highlighted that one algorithm (BA31_OPT1) had acceptable performance for identifying mTBI according to our "broad" definition for people under 18 years old. Sensitivity, specificity, PPV and NPV for this algorithm were 85.2%, 99.4%, 95.2% and 98%, respectively. CONCLUSION: Most mTBI case identification algorithms performed poorly in identifying mTBI cases of all ages in the OSCOUR database. Nevertheless, it was possible to identify cases defined according to a "broad" mTBI definition in the paediatric population (0-17 years).
Auteur : Paget Louis-Marie, Lorton Fleur, Forgeot Cécile, Beltzer Nathalie, Gallay Anne
Clinical epidemiology, 2025, vol. 17, p. 1099-1115
