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Record W4214901266 · doi:10.1055/s-0042-1743741

Preoperative Prediction Rule for Hydrocephalus in Children with Posterior Fossa Tumors: A Need to Introduce a New Scoring System

2022· article· en· W4214901266 on OpenAlexaboutno aff
Noor U. Maria

Bibliographic record

VenueJournal of Neurological Surgery Part B Skull Base · 2022
Typearticle
Languageen
FieldNeuroscience
TopicCerebrospinal fluid and hydrocephalus
Canadian institutionsnot available
Fundersnot available
KeywordsHydrocephalusMedicineResectionPosterior fossaSurgeryObstructive hydrocephalus

Abstract

fetched live from OpenAlex

Introduction: It has been estimated in a study that ~70% of patients were inadvertently exposed to pre-resection CSF diversionary procedures and hydrocephalus has seen to resolve after tumor resection in 70 to 90% of pediatric and 96% of adult patients. With all these points, it is prudent to explore, evaluate, introduce new, or modify already present predictive criteria such as the Canadian Preoperative Prediction Rule for Hydrocephalus for the judicious decision of pre-resection permanent CSF diversionary procedures. Objective: To evaluate predictive factors for post-resection hydrocephalus in pediatric patients with posterior cranial fossa tumors Methodology: We retrieved data of 70 children who had underwent surgery for posterior fossa tumors between January 2018 and December 2019. The medical records of 70 children who underwent surgery for a tumor in the posterior fossa between January 2017 and January 2019 were retrieved and studied retrospectively. Factors evaluated include age, clinical symptoms, tumor type, extent of surgical tumor resection, treatment with EVD and/or ETV, radiological findings, FOHR, and severity of hydrocephalus. Results: A total of 70 children: 45 males and 25 females, mean age 4.1 ± 3 years. Thirty patients had an EVD inserted before surgery. On T2-weighted imaging, all patients showed no evidence of flow void through the aqueduct secondary to obstruction of CSF outflow by tumor. Modification of radiological criteria that should include sigmoid and transverse sinus diameter, FOHR and Evans index. Updating and applying a “post-op scoring criteria” that takes into account the extent of resection, duration of surgery and intraoperative bleeding. Adding tumor specifications of midline location, superior extension and intra/extraparenchymal locations. Publication History Article published online: 15 February 2022 © 2022. Thieme. All rights reserved. Georg Thieme Verlag KG Rüdigerstraße 14, 70469 Stuttgart, Germany

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.028
GPT teacher head0.240
Teacher spread0.212 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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