A comparison of modeling approaches for static and dynamic prediction of central-line bloodstream infections using electronic health records (part 1): regression models

A comparison of modeling approaches for static and dynamic prediction of central-line bloodstream infections using electronic health records (part 1): regression models

Abstract Background Hospitals register information in the electronic health records (EHRs) continuously until discharge or death. As such, there is no censoring for in-hospital outcomes. We aimed to compare different static and dynamic regression modeling approaches to predict central line–associate...

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Bibliographic Details
Main Authors: Shan Gao, Elena Albu, Hein Putter, Pieter Stijnen, Frank E Rademakers, Veerle Cossey, Yves Debaveye, Christel Janssens, Ben Van Calster, Laure Wynants
Format: Article
Language:English
Published: BMC 2025-07-01
Series:Diagnostic and Prognostic Research
Subjects:
Risk prediction
Central line–associated bloodstream infection
Dynamic model
Logistic regression
Survival analysis
Online Access:https://doi.org/10.1186/s41512-025-00199-3
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https://doi.org/10.1186/s41512-025-00199-3

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