Swallowing dysfunctions in patients with disorders of consciousness: Evidence from neuroimaging data, assessment, and management
Bibliographic record
Abstract
Following severe brain injuries, a subset of patients may remain in an altered state of consciousness; most of these patients require artificial feeding. Currently, a functional oral phase and the presence of exclusive oral feeding may constitute signs of consciousness. Additionally, the presence of pharyngo-laryngeal secretions, saliva aspiration, cough reflex and tracheostomy are related to the level of consciousness. However, the link between swallowing and consciousness is yet to be fully understood. The primary aim of this review is to establish a comprehensive overview of the relationship between an individual's conscious behaviour and swallowing (reflexive and voluntary). Previous studies of brain activation during volitional and non-volitional swallowing tasks in healthy subjects are also reviewed. We demonstrate that the areas activated by voluntary swallowing tasks (primary sensorimotor, cingulate, insula, premotor, supplementary motor, cerebellum, and operculum) are not specific to deglutitive function but are shared with other motor tasks and brain networks involved in consciousness. This review also outlines suitable assessment and treatment methods for dysphagic patients with disorders of consciousness. Finally, we propose that markers of swallowing could contribute to the development of novel diagnostic guidelines for patients with disorders of consciousness.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".