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Record W3007584091 · doi:10.1177/0003489420909415

The Case of the Missing Nose: Congenital Arhinia Case Presentation and Management Recommendations

2020· article· en· W3007584091 on OpenAlexaff
Andrew K. Fuller, Hilary C. McCrary, M. Elise Graham, Jonathan R. Skirko

Bibliographic record

VenueAnnals of Otology Rhinology & Laryngology · 2020
Typearticle
Languageen
FieldMedicine
TopicCongenital Ear and Nasal Anomalies
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicinePresentation (obstetrics)Respiratory distressNosePediatricsCase presentationMagnetic resonance imagingAirwayCase managementAirway obstructionAirway managementSurgeryRadiologyNursing

Abstract

fetched live from OpenAlex

Objectives: To discuss the presentation and management of infants with arhinia or congenital absence of the nose. Methods: This case report describes an infant with arhinia that was diagnosed prenatally. In addition to a discussion of the case, a review of the literature was completed to define appropriate postnatal work-up and management. Results: The patient is a term male infant, diagnosed with arhinia on ultrasound and magnetic resonance imaging (MRI) performed at 21-weeks gestational age. Upon birth, the patient was subsequently intubated, followed by tracheostomy due to complete nasal obstruction. Through a genetics evaluation, the patient was found to be heterozygous for the SMCHD1 gene, with hypomethylation at the D4Z4 locus. Plans for reconstruction will be based on future imaging and the development of any nasal patency, however, the patient’s family plans to utilize a prosthetic nose until the patient is older. Conclusion: Arhinia is a rare condition causing respiratory distress in the neonatal period. While stabilization of the airway is the first priority, further management is not clearly defined given the rarity of the malformation. This case discusses stabilization of the airway with a review of treatment and reconstructive options.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.388
Threshold uncertainty score0.387

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.063
GPT teacher head0.340
Teacher spread0.277 · 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

Citations12
Published2020
Admission routes1
Has abstractyes

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