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Record W1639366416 · doi:10.1186/s40463-015-0087-1

Preoperative vocal cord paralysis and its association with malignant thyroid disease and other pathological features

2015· article· en· W1639366416 on OpenAlexaff
Emily Kay‐Rivest, Elliot J. Mitmaker, Richard J. Payne, Michael P. Hier, Alex Mlynarek, Jonathan Young, Véronique‐Isabelle Forest

Bibliographic record

VenueJournal of Otolaryngology - Head and Neck Surgery · 2015
Typearticle
Languageen
FieldMedicine
TopicThyroid and Parathyroid Surgery
Canadian institutionsJewish General HospitalMcGill University
Fundersnot available
KeywordsMedicineMalignancyPathologicalVocal cord paralysisParalysisCohortNodule (geology)ThyroidThyroid nodulesCordSurgeryRetrospective cohort studyRadiologyPathologyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Vocal cord paralysis (VCP) is found in both benign and malignant thyroid disease. This study was performed to determine if the presence of preoperative VCP predicts malignancy. METHODS: A retrospective analysis was performed on a cohort of 1923 consecutive patients undergoing thyroid surgery. The incidence of preoperative VCP was recorded. Patient and nodule characteristics were correlated with final pathology. RESULTS: 1.3% of our cohort was found to have preoperative VCP. Malignant pathology was discovered in 76% of patients with preoperative VCP. Among these patients, 72% had a left sided paralysis. 10.5% of patients with preoperative VCP had perineural invasion (PNI) on final pathology, compared to 1.1% of patients with normal VC function. CONCLUSION: Preoperative VCP appears to be a strong, though not an absolute, indicator of malignancy. Most VCP were on the left side. Assessing for preoperative VCP is crucial in all patients who need thyroid surgery, as even benign nodules can be accompanied by preoperative vocal cord paralysis.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.020
Threshold uncertainty score0.575

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.030
GPT teacher head0.282
Teacher spread0.251 · 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

Citations29
Published2015
Admission routes1
Has abstractyes

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