Two Distinct Clinical Phenotypes of Bulbar Motor Impairment in Amyotrophic Lateral Sclerosis
Bibliographic record
Abstract
Objective: Understanding clinical variants of motor neuron diseases such as amyotrophic lateral sclerosis (ALS) is critical for discovering disease mechanisms and across-patient differences in therapeutic response. The current work describes two clinical subgroups of patients with ALS that, despite similar levels of bulbar motor involvement, have disparate clinical and functional speech presentations. Methods: Participants included 47 healthy control speakers and 126 speakers with ALS. Participants with ALS were stratified into three clinical subgroups (i.e., bulbar asymptomatic, bulbar symptomatic high speech function, and bulbar symptomatic low speech function) based on clinical metrics of bulbar motor impairment. Acoustic and lip kinematic analytics were derived from each participant's recordings of reading samples and a rapid syllable repetition task. Group differences were reported on clinical scales of ALS and bulbar motor severity and on multiple speech measures. Results: The high and low speech-function subgroups were found to be similar on many of the dependent measures explored. However, these two groups were differentiated on the basis of an acoustic measure used as a proxy for tongue movement. Conclusion: This study supports the hypothesis that high and low speech-function subgroups do not differ solely in overall severity, but rather, constitute two distinct bulbar motor phenotypes. The findings suggest that the low speech-function group exhibited more global involvement of the bulbar muscles than the high speech-function group that had relatively intact lingual function. This work has implications for clinical measures used to grade bulbar motor involvement, suggesting that a single bulbar measure is inadequate for capturing differences among phenotypes.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".