Application of clinical prediction modeling in pediatric neurosurgery: a case study

Hendrik Jan Mijderwijk*, Thomas Beez, Daniel Hänggi, Daan Nieboer

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)
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There has been an increasing interest in articles reporting on clinical prediction models in pediatric neurosurgery. Clinical prediction models are mathematical equations that combine patient-related risk factors for the estimation of an individual’s risk of an outcome. If used sensibly, these evidence-based tools may help pediatric neurosurgeons in medical decision-making processes. Furthermore, they may help to communicate anticipated future events of diseases to children and their parents and facilitate shared decision-making accordingly. A basic understanding of this methodology is incumbent when developing or applying a prediction model. This paper addresses this methodology tailored to pediatric neurosurgery. For illustration, we use original pediatric data from our institution to illustrate this methodology with a case study. The developed model is however not externally validated, and clinical impact has not been assessed; therefore, the model cannot be recommended for clinical use in its current form.

Original languageEnglish
Pages (from-to)1495-1504
Number of pages10
JournalChild's Nervous System
Issue number5
Publication statusPublished - 30 May 2021

Bibliographical note

Funding Open Access funding enabled and organized by Projekt DEAL.

Publisher Copyright: © 2021, The Author(s).


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