Effect of Oral Screen Training After Stroke—A Randomised Controlled Trial
Bibliographic record
Abstract
OBJECTIVE: To assess the effects of oral screen training in patients with dysphagia post-stroke. BACKGROUND: Oral screen training has been identified as an effective method for improving orofacial and oropharyngeal motor functions. However, the evidence supporting a positive transfer effect on swallowing capacity post-primary stroke rehabilitation is still unclear. The aim of this randomised controlled trial was to investigate the effect of a 12-week oral screen training programme using a prefabricated oral screen, with swallowing capacity as the primary outcome. MATERIALS AND METHODS: In a randomised trial, stroke survivors with residual dysphagia post-rehabilitation were randomised into intervention group (n = 12) and control group (n = 12). The intervention group underwent 12 weeks of oral screen training. The main outcome was swallowing capacity, with lip force as a training indicator. Secondary outcomes were assessed by the Eating Assessment Tool, Masticatory performance, Nordic Orofacial Test-Screening, Life Satisfaction Questionnaire and the Edmonton Symptom Assessment System. RESULTS: At the 3-month follow-up, the group that trained with an oral screen showed a significantly greater increase in lip force than the control group (mean lip force increase 10.2 N vs. 3.1 N; p = 0.02). There was no significant improvement in swallowing capacity (mean increase 0.7 mL/min vs. 0.8 mL/min; p = 0.43), or in any of the secondary variables in the intervention group relative to the control group. CONCLUSION: The findings from this study showed that oral screen training initiated after completion of regular rehabilitation post-stroke can increase lip force. However, there was no indication of any transfer effect on swallowing capacity. TRIAL REGISTRATION: Clinicaltrial.gov identifier: NCT03167892.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.003 | 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 teacher head, 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".