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Record W3136686112 · doi:10.1055/s-0041-1726088

Cognitive Deficits in Pediatric Craniopharyngioma: An Updated Review

2021· article· en· W3136686112 on OpenAlexaff
Abdulrahman Al-Mirza, Omar Al-Taei, Tariq Al‐Saadi

Bibliographic record

VenueJournal of Pediatric Neurology · 2021
Typearticle
Languageen
FieldMedicine
TopicPituitary Gland Disorders and Treatments
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
Fundersnot available
KeywordsCognitionCraniopharyngiomaMedicineCognitive impairmentPediatricsAudiologyClinical psychologyPsychiatryPsychology

Abstract

fetched live from OpenAlex

Abstract Craniopharyngiomas (CP) are brain tumors that often occur in children and adolescent that results in many neurological and endocrinological disorders. The aim of this systematic review is to provide updated version of studies used to formalize standard tests used for cognitive impairment in pediatric patients with craniopharyngioma. A systematic review was conducted in PubMed, EBSCO, ProQuest, Science Direct, Wiley Online, and Springer to identify studies assessing cognitive impairment in pediatric patients with craniopharyngioma. Academic and learning dysfunctions were reported in seven studies among 41 of 178 patients (23%). Visual–spatial deficits were reported in six studies. Speech and verbal dysfunctions were reported in three studies. Memory deficits were reported in eight studies among 61 of 197 patients (31%). Motor dysfunctions were reported in five studies. Sleep related issues were reported in four studies among 33 of 70 patients (47.1%). Patients with treated pediatric CP demonstrate a high incidence of neurological deficits including cognitive dysfunctions. Academic and learning dysfunctions, visual–spatial deficits, speech and verbal dysfunctions, memory deficits, and sleep-related issues were the most commonly reported cognitive deficits in the present study.

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)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0090.008
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.019
GPT teacher head0.295
Teacher spread0.276 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations2
Published2021
Admission routes1
Has abstractyes

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