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Minimizing misclassification bias with a model to identify acetabular fractures using health administrative data: A cohort study

Acetabular fractures (AFs) are relatively uncommon thereby limiting their study. Analyses using population-based health administrative data can return erroneous results if case identification is inaccurate (‘misclassification bias’). This study measured the impact of an AF prediction model based exc...

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Detalles Bibliográficos
Autores principales:	Adamczyk, Andrew, Grammatopoulos, George, van Walraven, Carl
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Lippincott Williams & Wilkins 2021
Materias:	3700
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8718247/ https://www.ncbi.nlm.nih.gov/pubmed/34967356 http://dx.doi.org/10.1097/MD.0000000000028223

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