A comparison of modeling approaches for static and dynamic prediction of central-line bloodstream infections using electronic health records (part 1): regression models
Categorical and time-to-event approaches had similar performance in the static and dynamic settings, except Cox models. Ignoring competing risks caused problems for risk prediction in the time-to-event framework (Cox), but not in the categorical framework (logistic regression).
Authors
- Frank Rademakers (ORCID: https://orcid.org/0000-0002-7786-4179)
- Pieter Stijnen (ORCID: https://orcid.org/0000-0002-3047-6902)
- Yves Debaveye (ORCID: https://orcid.org/0000-0003-1784-8297)
- Shan Gao (ORCID: https://orcid.org/0000-0003-0871-1694)
- Laure Wynants (ORCID: https://orcid.org/0000-0002-3037-122X)
- Veerle Cossey (ORCID: https://orcid.org/0000-0001-6900-1974)
- Hein Putter (ORCID: https://orcid.org/0000-0001-5395-1422)
- Ben Van Calster (ORCID: https://orcid.org/0000-0003-1613-7450)
- Elena Albu (ORCID: https://orcid.org/0000-0003-2602-0918)
- Christel Janssens
Institutions
- Leiden University Medical Center (NL)
- Maastricht University (NL)
- KU Leuven (BE)
Publication Details
- Journal
- Diagnostic and Prognostic Research
- Published
- 2025-07-21
- DOI
- https://doi.org/10.1186/s41512-025-00199-3
- Primary Topic
- Sepsis Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- KU Leuven