Comparison of Lingual Pressure Generation Capacity in Parkinson Disease, Amyotrophic Lateral Sclerosis, and Healthy Aging
Bibliographic record
Abstract
PURPOSE: The tongue plays a key role in bolus propulsion during swallowing, with reduced lingual pressure generation representing a risk factor for impaired swallowing safety and efficiency. We compared lingual pressure generation capacity in people with Parkinson disease (PwPD), people with amyotrophic lateral sclerosis (PwALS), and healthy older adults. We hypothesized that both patient cohorts would demonstrate reduced maximum anterior isometric pressure (MAIP) and regular effort saliva swallow (RESS) pressures compared with healthy controls, with the greatest reductions expected in the ALS cohort. METHOD: We enrolled 20 PwPD, 18 PwALS, and 20 healthy adults over 60 years of age. The Iowa Oral Performance Instrument was used to measure MAIP, RESS, and lingual functional reserve (LFR, i.e., MAIP - RESS). Descriptive statistics were calculated; between-groups differences were explored using univariate analyses of variance and post hoc Sidak tests with alpha set at .05. RESULTS: Mean MAIPs for the PD, ALS, and heathy cohorts were 54.7, 33.5, and 47.4 kPa, respectively. Significantly lower MAIP was found in PwALS compared with PwPD and healthy controls. RESS values did not differ significantly across groups. LFR was significantly higher in PwPD versus PwALS and healthy controls. CONCLUSIONS: Lingual pressure generation capacity and functional reserve were reduced in PwALS, but not in PwPD, beyond changes seen with healthy aging. Both patient cohorts displayed preserved lingual pressure during saliva swallows. Future studies exploring longitudinal changes in tongue pressure generation on isometric and saliva swallowing tasks will be needed to confirm whether tongue pressure measures serve as noninvasive clinical biomarkers of swallowing impairment.
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 | 0.002 |
| 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 | 0.001 |
| 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".