Best practices protocol for the evaluation of bulbar dysfunction: summary recommendations from the NEALS bulbar subcommittee symposium
Bibliographic record
Abstract
OBJECTIVE: The aim of this Symposium was to develop a consensus based, bulbar assessment protocol for implementation within NEALS clinics. METHODS: A one-day symposium, held in April 2017, was organized into Speech and Swallowing sections to establish summary recommendations for the assessment of bulbar dysfunction within each group. RESULTS: Summary recommendations included speech referrals and AAC evaluations at initial visit, CNS-BFS, maximum sustained phonation, and speaking rate. Dysarthria evaluation included the speech subsystem involvement of respiration, phonation, resonance, and articulation. Specific recommendations for swallowing were established for each of the following domains: dietary/oral intake, airway defense physiologic capacity, swallow safety screen, patient-reported swallow-related outcomes, oral sensorimotor exam, and pulmonary function. Practice parameters focused upon patient education and unresolved questions included the use of videofluoscopy, monitoring diet progression, and swallow safety screening. CONCLUSIONS: The working goal is to establish a clinical bulbar protocol, designed to be incorporated within ALS clinics and ultimately to formulate a best practice set of bulbar ALS guidelines, available for implementation throughout the international ALS community.
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 | 0.195 | 0.156 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.007 | 0.008 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.010 | 0.008 |
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".