Rate of speech decline in individuals with amyotrophic lateral sclerosis
Bibliographic record
Abstract
Although speech declines rapidly in some individuals with amyotrophic lateral sclerosis (ALS), longitudinal changes in speech have rarely been characterized. The study objectives were to model the rate of decline in speaking rate and speech intelligibility as a function of disease onset site, sex, and age at onset in 166 individuals with ALS; and estimate time to speech loss from symptom onset. We also examined the association between clinical (speaking rate/intelligibility) measures and patient-reported measures of ALS progression (ALSFRS-R). Speech measures declined faster in the bulbar-onset group than in the spinal-onset group. The rate of decline was not significantly affected by sex and age. Functional speech was still maintained at 60 months since disease onset for most patients with spinal onset. However, the time to speech loss was 23 months based on speaking rate < 120 (w/m) and 32 months based on speech intelligibility < 85% in individuals with ALS-bulbar onset. Speech measures were more responsive to functional decline than were the patient-reported measures. The findings of this study will inform future work directed toward improving speech prognosis in ALS, which is critical for determining the appropriate timing of interventions, providing appropriate counseling for patients, and evaluating functional changes during clinical trials.
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 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 | 0.005 |
| 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 | 0.001 | 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".