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Record W4246961442 · doi:10.1002/hed.26032

The diagnostic value of cytology in parotid Warthin's tumors: international multicenter series

2019· article· en· W4246961442 on OpenAlexaff
Daniele Borsetto, Jonathan Fussey, Diego Cazzador, Joel Smith, Andrea Ciorba, Stefano Pelucchi, Sara Donà, Paolo Boscolo‐Rizzo, Michele Tomasoni, Davide Lombardi, Piero Nicolai, Elisabetta Zanoletti, Roberta Colangeli, Enzo Emanuelli, Max Sallis Osborne, Syed Ahsan, Margherita Tofanelli, Giancarlo Tirelli, Katherine McNamara, Leonard Liew, Katherine Harrison, Ambrogio Fassina, Samantha Sarcognato, Neil Sharma, Kanishka Rao, Paul Pracy, Paul Nankivell

Bibliographic record

VenueHead & Neck · 2019
Typearticle
Languageen
FieldMedicine
TopicSalivary Gland Tumors Diagnosis and Treatment
Canadian institutionsSurgical Specialties (Canada)
Fundersnot available
KeywordsMedicineCytologyMalignancyRadiological weaponRadiologyFine needle aspiration cytologyMedical diagnosisParotid glandAdenolymphomaRetrospective cohort studySurgeryPathology

Abstract

fetched live from OpenAlex

INTRODUCTION: Warthin's tumor (WT) is a common benign salivary gland neoplasm with a negligible risk of malignant transformation. However, there is a risk of malignant tumors being misdiagnosed as WT on cytology and inappropriately managed conservatively. METHODS: Patients from nine centers in Italy and the United Kingdom undergoing parotid surgery for cytologically diagnosed WT were included in this multicenter retrospective series. Definitive histology was compared with preoperative cytological diagnoses. Surgical complications were recorded. RESULTS: A total of 496 tumors were identified. In 88.9%, the final histological diagnosis was WT. In 21 cases (4.2%) a malignant neoplasm was diagnosed, which had been incorrectly labeled as WT on cytology. CONCLUSIONS: The risk of undiagnosed malignancy should be balanced against surgical risks when considering the management of WT. Although nonsurgical management remains an appropriate option, there may be a rationale for serial clinical or radiological evaluation if surgical excision is not performed.

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 score0.006
Threshold uncertainty score0.274

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 studies0.0000.000
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 head0.009
GPT teacher head0.274
Teacher spread0.265 · 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

Citations21
Published2019
Admission routes1
Has abstractyes

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