093 Tracheostomy in plw motor neuron disease – prolonged survival with continuous ventilation via a cuffed tube
Bibliographic record
Abstract
The role of tracheostomy in the management of ventilatory failure due to motor neuron disease (MND) remains controversial. Although it is an effective alternative to non-invasive ventilation (NIV) in supporting ventilation, the risk of prolonged survival in the face of reduced quality of life is a concern. We present 25 patients living with (plw) MND who underwent tracheostomy. There were 16 males, the mean age was 64.0 yrs (36–83), 13 patients underwent tracheostomy prior to the diagnosis and could not be weaned, the mean duration of tracheostomy to death or December 2019 was 3.4 yrs (0.2–8.7). 19 patients required continuous ventilation using a permanently cuffed tube. All the patients became entirely dependant, and 8 had limited or no communication despite eye gaze or environmental control systems. 14 patients were in care homes and 11 required 24 hr support at home. Several patients expressed their desire to maintain invasive ventilatory support despite inevitable and progressively increasing dependence. Many plw MND become dependent on invasive ventilatory support before the diagnosis is established and may live for prolonged periods following tracheostomy despite total dependence. The use of tra- cheostomy in MND raises issues about the balance of patient autonomy, resource allocation and the role of medical professionals. robinhoward@nhs.net
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".