Prospective Validation of a Non-Invasive Bedside Protocol for Tracheostomy Decannulation in Acquired Brain Injury With Otolaryngologic Concordance
Bibliographic record
Abstract
BACKGROUND: Decannulation of tracheostomy in individuals with acquired brain injury (ABI) is challenging and often requires endoscopic airway assessment. A reliable noninvasive bedside protocol could support decision-making in neurorehabilitation settings. METHODS: We conducted a prospective observational cohort study at a tertiary neurorehabilitation center between July 2021 and March 2025. Thirty-six adults with chronic ABI and tracheostomies were assessed using a structured bedside protocol comprising tracheostomy capping tolerance, suction requirement ≤2 episodes per 24 hours, modified Evans blue dye aspiration screening, and laryngeal ultrasonography. All participants subsequently underwent blinded nasopharyngolaryngoscopic (NPL) examination as the reference standard. RESULTS: Twenty-six participants (72.2%) were protocol positive; 24 were suitable for decannulation on NPL and two were unsuitable. Among 10 protocol-negative participants, nine were unsuitable and one was suitable. Sensitivity was 96.0% (95% CI 79.6-99.9), specificity 81.8% (95% CI 48.2-97.7), and overall accuracy 91.7%. Agreement with NPL findings was strong (κ = 0.80). No aspiration pneumonia, respiratory deterioration, or recannulation occurred during four weeks of follow-up. CONCLUSIONS: The bedside protocol may serve as a screening tool to support decannulation assessment and guide the need for confirmatory endoscopic evaluation. Larger multicentre studies are warranted.
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 | 0.021 | 0.074 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".