Classifying individuals based on a densely captured sequence of vital signs: An example using repeated blood pressure measurements during hemodialysis treatment.
Published
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
Language
- eng
Conference Location
- United States