Evidence map›Paper›PMID 41459412›Full record

ArticleClinical epidemiology2025

Validation Study of Mild Traumatic Brain Injury Case-Identifying Algorithms in French Emergency Departments: High Performance in Children but Limited in Adults.

Louis-Marie Paget, Fleur Lorton, Cécile Forgeot, Nathalie Beltzer, Anne Gallay

Abstract read
In one paragraph

Article in Clinical epidemiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Louis-Marie PagetDirection des maladies non transmissibles et traumatismes, Santé publique France, Saint-Maurice, Île-de-France, France.
Fleur LortonPediatric Emergency Department, UIC14 Femme-Enfant-Adolescent, CIC1413, Nantes Université, Nantes University Hospital, INSERM, Nantes, France.
Cécile ForgeotDirection Appui, Traitements et Analyses de données, Santé publique France, Saint-Maurice, Île-de-France, France.
Nathalie BeltzerDirection des maladies non transmissibles et traumatismes, Santé publique France, Saint-Maurice, Île-de-France, France.
Anne GallayDirection des maladies non transmissibles et traumatismes, Santé publique France, Saint-Maurice, Île-de-France, France.ORCID 0000-0001-6467-7043

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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).

Indexed as

algorithmsbrain concussion/epidemiologydatabasesemergency servicefactual/standardsFrancehospitalinternational classification of diseasesmild traumatic brain injuryvalidation studies as topicvalidation study

Identifiers

PMID41459412
PMCPMC12739176

What Socratic holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.