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)
44 Downloads (Pure)

Abstract

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
Volume37
Issue number5
DOIs
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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