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Record W4401162451 · doi:10.4103/pajo.pajo_43_24

Prevalence of neurofibromatosis type 1 in patients presenting with neurofibromas of the eyelid and orbit

2024· article· en· W4401162451 on OpenAlexaffabout
Elisa Moya Kazmarek, Victória de Lima Burnier, Sabrina Bergeron, Bryan Arthurs, Christian El Hadad, José João Mansure, Miguel N. Burnier

Bibliographic record

VenueThe Pan-American Journal of Ophthalmology · 2024
Typearticle
Languageen
FieldMedicine
TopicNeurofibromatosis and Schwannoma Cases
Canadian institutionsRoyal Victoria HospitalMcGill University Health CentreMcGill University
Fundersnot available
KeywordsPlexiform neurofibromaNeurofibromatosisNeurofibromaEyelidMedicineOrbit (dynamics)DermatologyPopulationRadiologyPathology

Abstract

fetched live from OpenAlex

Abstract Aims: This study aimed to demonstrate the prevalence of neurofibromatosis type 1 diagnosis in patients presenting with neurofibromas of eyelid and orbit and the factors associated with this disease. Materials and Methods: Charts from patients with pathology reports of neurofibroma of the eyelid and orbit from the MUHC-McGill University Ocular Pathology Laboratory from 2007 to 2022 were reviewed to find information about clinical diagnosis of neurofibromatosis type (NF) 1, sex, age, presence of Lisch nodules, and other findings. The data were analyzed with the Chi-square test and Fisher’s exact test. Results: The prevalence of NF1 in patients presenting neurofibromas of the eyelid and orbit was 47.62% in the population studied. All patients with plexiform neurofibromas and all the ones presenting Lisch nodules had an NF1 diagnosis. Conclusion: All patients with plexiform neurofibromas of the eyelid or orbit and their relatives should be investigated for NF1. Ophthalmological evaluation is essential for the identification of Lisch nodules since their presence, associated with two neurofibromas are enough to meet the criteria for NF1; therefore, the family of patients with that presentation should be clinically, and if necessary, genetically tested.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.310

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.015
GPT teacher head0.269
Teacher spread0.255 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueThe Pan-American Journal of OphthalmologySame topicNeurofibromatosis and Schwannoma CasesFrench-language works237,207