Improved prediction of postoperative pediatric cerebellar mutism syndrome using an artificial neural network.
Abstract
<h4>Background</h4>Postoperative pediatric cerebellar mutism syndrome (pCMS) is a
common but severe complication that may arise following the resection of posterior
fossa tumors in children. Two previous studies have aimed to preoperatively predict
pCMS, with varying results. In this work, we examine the generalization of these models
and determine if pCMS can be predicted more accurately using an artificial neural
network (ANN).<h4>Methods</h4>An overview of reviews was performed to identify risk
factors for pCMS, and a retrospective dataset was collected as per these defined risk
factors from children undergoing resection of primary posterior fossa tumors. The
ANN was trained on this dataset and its performance was evaluated in comparison to
logistic regression and other predictive indices via analysis of receiver operator
characteristic curves. The area under the curve (AUC) and accuracy were calculated
and compared using a Wilcoxon signed-rank test, with P < .05 considered statistically significant.<h4>Results</h4>Two hundred and four children
were included, of whom 80 developed pCMS. The performance of the ANN (AUC 0.949; accuracy
90.9%) exceeded that of logistic regression (P < .05) and both external models (<i>P</i> < .001).<h4>Conclusion</h4>Using an ANN,
we show improved prediction of pCMS in comparison to previous models and conventional
methods.
Type
Journal articleSubject
artificial neural networkcomplications
magnetic resonance imaging
posterior fossa tumor
postoperative pediatric cerebellar mutism syndrome
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https://hdl.handle.net/10161/27040Published Version (Please cite this version)
10.1093/noajnl/vdac003Publication Info
Sidpra, Jai; Marcus, Adam P; Löbel, Ulrike; Toescu, Sebastian M; Yecies, Derek; Grant,
Gerald; ... Mankad, Kshitij (2022). Improved prediction of postoperative pediatric cerebellar mutism syndrome using an
artificial neural network. Neuro-oncology advances, 4(1). pp. vdac003. 10.1093/noajnl/vdac003. Retrieved from https://hdl.handle.net/10161/27040.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
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Show full item recordScholars@Duke
Gerald Arthur Grant
Allan H. Friedman Distinguished Professor of Neurosurgery

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