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Record W3209703444 · doi:10.1044/2021_jslhr-21-00038

Psychometric Properties of Rapid Word-Based Rate Measures in the Assessment of Bulbar Amyotrophic Lateral Sclerosis: Comparisons With Syllable-Based Rate Tasks

2021· article· en· W3209703444 on OpenAlexaff

Bibliographic record

VenueJournal of Speech Language and Hearing Research · 2021
Typearticle
Languageen
FieldMedicine
TopicBotulinum Toxin and Related Neurological Disorders
Canadian institutionsUniversity Health NetworkHealth Sciences CentreSunnybrook Health Science CentreToronto Rehabilitation InstituteUniversity of Toronto
FundersNational Institute on Deafness and Other Communication Disorders
KeywordsAmyotrophic lateral sclerosisTongueDysarthriaRehabilitationSyllableProtocol (science)Electromyography

Abstract

fetched live from OpenAlex

Purpose Rapid maximum performance repetition tasks have increasingly demonstrated their utility as clinimetric markers supporting diagnosis and monitoring of bulbar disease in amyotrophic lateral sclerosis (ALS). A recently developed protocol uses novel real-word repetitions instead of traditional nonword/syllable sequences in hopes of improving sensitivity to motor speech impairments by adding a phonological target constraint that would activate a greater expanse of the motor speech neuroanatomy. This study established the psychometric properties of this novel clinimetric protocol in its assessment of bulbar ALS and compared performance to traditional syllable sequence dysdiadochokinetic (DDK) tasks. Specific objectives were to (a) compare rates between controls and speakers with symptomatic versus presymptomatic bulbar disease, (b) characterize their discriminatory ability in detecting presymptomatic bulbar disease compared to healthy speech, (c) determine their articulatory movement underpinnings, and (d) establish within-individual longitudinal changes. Method DDK and novel tongue (“ticker”—TAR) and labial (“pepper”—LAR) articulatory rates were compared betweenn= 18 speakers with presymptomatic bulbar disease,n= 10 speakers with symptomatic bulbar disease, andn= 13 healthy controls. Bulbar disease groups were determined by a previously validated speaking rate cutoff. Discriminatory ability was determined using receiver operating characteristic analysis. Within-individual change over time was characterized in a subset of 16 participants with available longitudinal data using linear mixed-effects models. Real-time articulatory movements of the tongue front, tongue dorsum, jaw, and lips were captured using 3-D electromagnetic articulography; effects of movement displacement and speed on clinimetric rates were determined using stepwise linear regressions. Results All clinimetric rates (traditional DDK tasks and novel tasks) were reduced in speakers with symptomatic bulbar disease; only TAR was reduced in speakers with presymptomatic bulbar disease and was able to detect this group with an excellent discrimination ability (area under the curve = 0.83). Kinematic analyses revealed associations with expected articulators, greater motor complexity, and differential articulatory patterns for the novel real-word repetitions than their DDK counterparts. Only LAR significantly declined longitudinally over the disease course. Conclusion Novel real-word clinimetric rate tasks evaluating tongue and labial articulatory dysfunction are valid and effective markers for early detection and tracking of bulbar disease in ALS.

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)0.007
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.154
GPT teacher head0.368
Teacher spread0.214 · 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 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

Citations6
Published2021
Admission routes1
Has abstractyes

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