A better performing algorithm for identification of implausible growth data from longitudinal pediatric medical records.

ABSTRACT: Tracking trajectories of body size in children provides insight into chronic disease risk. One measure of pediatric body size is body mass index (BMI), a function of height and weight. Errors in measuring height or weight may lead to incorrect assessment of BMI. Yet childhood measures of height and weight extracted from electronic medical records often include values which seem biologically implausible in the context of a growth trajectory. Removing biologically implausible values reduces noise in the data, and thus increases the ease of modeling associations between exposures and childhood BMI trajectories, or between childhood BMI trajectories and subsequent health conditions. We developed open-source algorithms (available on github) for detecting and removing biologically implausible va

SUBMITTER: Harrall KK 

PROVIDER: S-EPMC11303760 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature