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Record W2905846861 · doi:10.1002/mus.26405

The requirement for a disease‐specific patient‐reported outcome measure of dysphagia in oculopharyngeal muscular dystrophy

2018· article· en· W2905846861 on OpenAlexaff
Claudia Côté, Cynthia Gagnon, Sarah Youssof, Nicolette sKurtz, Bernard Brais

Bibliographic record

VenueMuscle & Nerve · 2018
Typearticle
Languageen
FieldHealth Professions
TopicDysphagia Assessment and Management
Canadian institutionsMcGill UniversityCentre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-JeanUniversité de Sherbrooke
Fundersnot available
KeywordsOculopharyngeal muscular dystrophyDysphagiaMedicineContent validityPhysical therapyDelphi methodOropharyngeal dysphagiaPatient-reported outcomePsychometricsQuality of life (healthcare)Clinical psychologySurgeryNursing

Abstract

fetched live from OpenAlex

INTRODUCTION: There is no patient-reported outcome (PRO) questionnaire specifically designed to assess oropharyngeal dysphagia in oculopharyngeal muscular dystrophy (OPMD). To select a suitable questionnaire, content validity of the existing questionnaires must be assessed. This study sought (1) to identify dysphagia-related symptoms in OPMD and (2) to assess content validity of currently available PRO for the assessment of dysphagia severity in OPMD. METHODS: A two-step literature review was conducted of dysphagia-related symptom identification and oropharyngeal dysphagia-related PRO. Symptoms were validated with an expert panel by using a Delphi survey. Content validity of PRO questionnaires was documented through content analysis. RESULTS: Ten PRO questionnaires were identified. None of the questionnaires cover the entire symptom spectrum in OPMD and thus lack content validity. DISCUSSION: The development and validation of a new PRO questionnaire to assess dysphagia in OPMD is required to establish the importance of symptomatic relief from new treatments. Muscle Nerve 59:445-450, 2019.

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)0.000
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 score0.217
Threshold uncertainty score0.751

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.092
GPT teacher head0.379
Teacher spread0.286 · 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

Citations12
Published2018
Admission routes1
Has abstractyes

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