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Record W4409167017 · doi:10.1080/23772484.2025.2485261

Respiratory epithelial hamartoma – a case series and the importance of its diagnosis

2025· article· en· W4409167017 on OpenAlexaff
Joseph Rassam, Nora Haloob, Steve Connor, Claire Hopkins

Bibliographic record

VenueActa Oto-Laryngologica Case Reports · 2025
Typearticle
Languageen
FieldMedicine
TopicTracheal and airway disorders
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsHamartomaSeries (stratigraphy)Respiratory systemMedicineComputer sciencePathologyInternal medicineBiologyPaleontology

Abstract

fetched live from OpenAlex

Introduction Respiratory epithelial adenomatoid hamartomas (REAH) are benign growths that can occur in the nasal cavity. When mistaken for inflammatory nasal polyps, it can result in presumed poor treatment response. This case series and review outlines their clinical presentation and importance of its recognition.Methods Cases were retrospectively analysed from a single centre over a 12-month period. Imaging and histology results were analysed.Results Four cases were reviewed. All males in their 6th decade undergoing treatment for chronic rhinosinusitis with nasal polyps. All reported hyposmia, poor response to steroids and had a widened olfactory cleft on CT imaging. There was no recurrence following surgical resection.Conclusion Our findings are consistent with other case series. It is essential that clinicians are aware of REAH and consider it in patients who fit this clinical picture to manage expectations of treatments, in particular steroids and biologics. If undergoing sinus surgery, olfactory cleft histological sampling should be considered.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0020.002
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.016
GPT teacher head0.273
Teacher spread0.256 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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