Classifying individuals based on a densely captured sequence of vital signs: An example using repeated blood pressure measurements during hemodialysis treatment.


Journal Article

Electronic Health Records (EHRs) present the opportunity to observe serial measurements on patients. While potentially informative, analyzing these data can be challenging. In this work we present a means to classify individuals based on a series of measurements collected by an EHR. Using patients undergoing hemodialysis, we categorized people based on their intradialytic blood pressure. Our primary criteria were that the classifications were time dependent and independent of other subjects. We fit a curve of intradialytic blood pressure using regression splines and then calculated first and second derivatives to come up with four mutually exclusive classifications at different time points. We show that these classifications relate to near term risk of cardiac events and are moderately stable over a succeeding two-week period. This work has general application for analyzing dense EHR data.

Full Text

Duke Authors

Cited Authors

  • Goldstein, BA; Chang, TI; Winkelmayer, WC

Published Date

  • October 2015

Published In

Volume / Issue

  • 57 /

Start / End Page

  • 219 - 224

PubMed ID

  • 26277118

Pubmed Central ID

  • 26277118

Electronic International Standard Serial Number (EISSN)

  • 1532-0480

Digital Object Identifier (DOI)

  • 10.1016/j.jbi.2015.08.010


  • eng

Conference Location

  • United States