Lingual and Jaw Kinematic Abnormalities Precede Speech and Swallowing Impairments in ALS
Bibliographic record
Abstract
Early identification of bulbar involvement in persons with ALS is critical for improving diagnosis and prognosis; however, efficacious diagnostic markers have not yet been identified. The purpose of this study was to determine whether kinematic changes of the tongue and jaw during swallowing, measured using 3D electromagnetic articulography (EMA), predate clinically identifiable symptoms of speech and swallowing impairment in persons diagnosed with ALS. Data were collected from 16 adults diagnosed with ALS and 18 neurotypical controls. Groups were aged matched. Eligible participants with ALS were tolerating an unrestricted diet (FOIS = 7), produced intelligible speech (> 97%), and had a speaking rate greater than 150 words per minute. Participants completed a 3-mL water swallow task, during which EMA recorded kinematic measures of the anterior and posterior regions of tongue including lingual speed, range of motion, duration, coordination, and efficiency. Jaw speed and range of motion were also recorded. Persons diagnosed with ALS demonstrated reduced posterior lingual range of motion (11.40 mm ± 4.01 vs. 16.07 mm ± 5.27), slower posterior lingual speeds (83.67 mm/s ± 47.96 vs. 141.35 mm/s ± 66.54), increased lingual movement duration (13.46 s ± 6.75 vs. 9.21 s ± 3.28), and reduced lingual coordination (0.04 s ± 0.11 vs. 17 s ± 0.19) during the 3-oz water swallow task compared to controls. Persons diagnosed with ALS demonstrated increased range of motion (9.86 mm ± 5.38 vs. 6 mm ± 3.78) and increased jaw speed (68.62 mm/s ± 50.13 vs. 34.72 mm/s ± 17.75) during swallowing compared to controls. The current findings suggest that changes in lingual and jaw motor performance during a simple water swallow task are present in persons with ALS who are pre-symptomatic of clinically detectable bulbar impairment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".