The effects of misclassification in routine healthcare databases on the accuracy of prognostic prediction models: a case study of the CHA2DS2-VASc score in atrial fibrillation

Abstract Background Research on prognostic prediction models frequently uses data from routine healthcare. However, potential misclassification of predictors when using such data may strongly affect the studied associations. There is no doubt that such misclassification could lead to the derivation...

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Bibliographic Details

Published in:	Diagnostic and Prognostic Research
Main Authors:	S. van Doorn, T. B. Brakenhoff, K. G. M. Moons, F. H. Rutten, A. W. Hoes, R. H. H. Groenwold, G. J. Geersing
Format:	Article
Language:	English
Published:	BMC 2017-11-01
Subjects:	Routine care data Validation Prediction model Atrial fibrillation CHA2DS2-VASc Misclassification
Online Access:	http://link.springer.com/article/10.1186/s41512-017-0018-x