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Record W3158223156 · doi:10.1002/mus.27262

Vocal fold injection material does not preclude interpretation of laryngeal electromyography

2021· article· en· W3158223156 on OpenAlexaff
Michael A. Belsky, R. Jun Lin, Clark A. Rosen, Michael C. Munin, Libby J. Smith

Bibliographic record

VenueMuscle & Nerve · 2021
Typearticle
Languageen
FieldMedicine
TopicVoice and Speech Disorders
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsMedicineVocal fold paralysisElectromyographyVocal cord paralysisAnesthesiaAudiologyParalysisSurgeryPhysical medicine and rehabilitation

Abstract

fetched live from OpenAlex

INTRODUCTION/AIMS: Temporary vocal fold injection (VFI) is a common treatment for acute and subacute vocal fold paralysis (VFP). Laryngeal electromyography (LEMG) is useful for diagnosing neurogenic causes of VFP. This study evaluated whether the presence of VFI material prevents interpretation of LEMG in patients with acute and subacute VFP. METHODS: Patients with acute and subacute unilateral VFP (onset ≤6 mo) who underwent temporary VFI within 3 mo preceding LEMG were evaluated. A matched control group that did not undergo VFI was also studied. The LEMG team (laryngologist and electromyographer) performed and interpreted LEMG using a pre-specified protocol, including qualitative and quantitative motor unit analysis. RESULTS: Eighteen patients with VFI underwent LEMG successfully with interpretation of spontaneous activity and motor unit recruitment. Fourteen patients were seen in follow-up to determine accuracy of established LEMG prognosis. Seven of seven subjects with poor LEMG prognosis did not recover vocal fold motion. Five of seven subjects with fair LEMG prognosis recovered vocal fold motion. Findings were similar for the control group. DISCUSSION: VFI augmentation material did not prevent interpretation of meaningful LEMG data in patients with acute and subacute VFP, and accurate prognoses of vocal fold motion recovery were established.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.155
Threshold uncertainty score0.354

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 head0.008
GPT teacher head0.250
Teacher spread0.242 · 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 designBench or experimental
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

Citations5
Published2021
Admission routes1
Has abstractyes

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