Evidence map›Paper›PMID 35233531›Full record

ArticleNeuro-oncology advances

Improved prediction of postoperative pediatric cerebellar mutism syndrome using an artificial neural network.

Jai Sidpra, Adam P Marcus, Ulrike Löbel, Sebastian M Toescu, Derek Yecies, Gerald Grant, Kristen Yeom, David M Mirsky, Hani J Marcus, Kristian Aquilina and 1 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Neuro-oncology advances. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.0field-weighted citation impact, top 27% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 9 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 5 institutions in 2 countries.

Jai SidpraUniversity College London Medical School, London, UK.ORCID https://orcid.org/0000-0003-1985-5503
Adam P MarcusDepartment of Brain Sciences and Computing, Imperial College London, London, UK.
Ulrike LöbelDepartment of Neuroradiology, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK.
Sebastian M ToescuDepartment of Neurosurgery, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK.ORCID https://orcid.org/0000-0001-8768-9231
Derek YeciesDepartment of Neurosurgery, Lucile Packard Children's Hospital, Stanford, California, USA.ORCID https://orcid.org/0000-0001-8534-4651
Gerald GrantDepartment of Neurosurgery, Lucile Packard Children's Hospital, Stanford, California, USA.ORCID https://orcid.org/0000-0002-2651-4603
Kristen YeomDepartment of Neuroradiology, Lucile Packard Children's Hospital, Stanford, California, USA.ORCID https://orcid.org/0000-0001-9860-3368
David M MirskyDepartment of Radiology, Children's Hospital Colorado, University of Colorado School of Medicine, Aurora, Colorado, USA.ORCID https://orcid.org/0000-0003-2162-515X
Hani J MarcusDepartment of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK.ORCID https://orcid.org/0000-0001-8000-392X
Kristian AquilinaDevelopmental Biology and Cancer Section, University College London Great Ormond Street Institute of Child Health, London, UK.ORCID https://orcid.org/0000-0001-7015-5196
Kshitij MankadDevelopmental Biology and Cancer Section, University College London Great Ormond Street Institute of Child Health, London, UK.ORCID https://orcid.org/0000-0001-5979-9337
Great Ormond Street Hospital for Children NHS Foundation Trust · GBLucile Packard Children's Hospital · USChildren's Hospital Colorado · USImperial College London · GBWellcome / EPSRC Centre for Interventional and Surgical Sciences · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPostoperative 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).

methodsAn 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

resultsTwo 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 (

conclusionUsing an ANN, we show improved prediction of pCMS in comparison to previous models and conventional methods.

Indexed as

artificial neural networkcomplicationsmagnetic resonance imagingposterior fossa tumorpostoperative pediatric cerebellar mutism syndrome

Identifiers

PMID35233531
PMCPMC8882257
OpenAlexW4206238471

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.