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Record W4285153309 · doi:10.1177/27528464221078443

Posterior Vault Distraction for Multi-Suture Craniosynostosis in a Patient with Craniometaphyseal Dysplasia: A Case Report

2022· article· en· W4285153309 on OpenAlexaff
Diana Kennedy, Ian Loh, Helen M. Branson, Christopher R. Forrest

Bibliographic record

VenueCraniomaxillofacial Research & Innovation · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCraniofacial Disorders and Treatments
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsCraniosynostosisCranial vaultMedicineIntracranial pressureDistractionFibrous jointDistraction osteogenesisSurgeryDeformitySynostosisVentriculomegalyOrthodonticsSkullFetusPsychology

Abstract

fetched live from OpenAlex

Study Design Case report Objective Syndromic multi-suture craniosynostosis can result in complex dysmorphology and increased intracranial pressure. We present a case report of a child with craniometaphyseal dysplasia and syndromic multi-suture craniosynostosis who presented with increased intracranial pressure, ventriculomegaly and Chiari deformity Type 1. Methods The child underwent a posterior vault distraction to increase the intracranial volume. Results The posterior cranial expansion was successful in correcting the craniocerebral disproportion caused by multi-suture synostosis, and resolved the high intracranial pressure and papilloedema. There were no post-operative complications. Conclusions Posterior cranial vault distraction was an effective method of addressing increased intracranial pressure by correcting craniocerebral disproportion by increasing intracranial volume and also addressing the Chiari Type I deformity that resulted from syndromic multi-suture craniosynostosis in a child with craniometaphyseal dysplasia.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.667
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.056
GPT teacher head0.371
Teacher spread0.315 · 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 teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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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