MétaCan
Menu
Back to cohort
Record W3118099260 · doi:10.1016/j.xocr.2020.100259

Pituitary adenoma presenting with nasal obstruction: A case report

2020· article· en· W3118099260 on OpenAlexaff
Mitchell McDonough, André le Roux, Christopher J. Chin

Bibliographic record

VenueOtolaryngology Case Reports · 2020
Typearticle
Languageen
FieldMedicine
TopicPituitary Gland Disorders and Treatments
Canadian institutionsDalhousie UniversitySaint John Regional Hospital
Fundersnot available
KeywordsMedicinePituitary adenomaClivusNasal cavityHyposmiaDifferential diagnosisPituitary tumorsNasal congestionAdenomaRadiologySurgerySkullNosePathologyDisease

Abstract

fetched live from OpenAlex

A 58-year-old lady presented with worsening congestion, nasal obstruction, and hyposmia. After failing medical therapy, a computed tomography (CT) scan was ordered which demonstrated a large tumor (6.1 cm × 3.9 cm x 5.2cm) in the nasal cavity. There was erosion through the skull base superiorly and the clivus inferiorly (Fig. 1). At this point she was referred to our center where she underwent endoscopic biopsies that demonstrated a pituitary adenoma. Formal visual testing showed decreased visual acuity in the right eye. She then underwent successful endoscopic resection of the tumor with significant improvement clinically. Pituitary adenomas are relatively common lesions and represent approximately 15% of all intracranial neoplasms. The presentation can be varied, but often patients present with headache, endocrinological disturbances, or visual changes. Nasal obstruction is a very rare presentation of a pituitary adenoma, but has been described in the literature, first being described in 1910. In the workup of a large nasal mass, imaging and histological exam is essential. The differential for nasal obstruction is large, but pituitary tumors (including adenoma) should be on the differential and kept in the back of the mind whenever a patient presents with a large posteriorly-based sinonasal mass.

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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.328
Threshold uncertainty score0.914

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.017
GPT teacher head0.257
Teacher spread0.239 · 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 designCase report
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

Citations1
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueOtolaryngology Case ReportsSame topicPituitary Gland Disorders and TreatmentsFrench-language works237,207