Long-term ventilation in children: longitudinal trends and outcomes
Bibliographic record
Abstract
BACKGROUND: Cross-sectional studies have suggested a rapid expansion in paediatric long-term ventilation (LTV) over the last 20 years but information on longitudinal trends is limited. METHODS: Data were collected prospectively on all patients receiving LTV over a 15-year period (1.1.95-31.12.09) in a single regional referral centre. RESULTS: 144 children commenced LTV during the 15-year period. The incidence of LTV increased significantly over time, with an accompanying 10-fold increase in prevalence due to a significant increase in institution of non-invasive ventilation (NIV). There was no significant increase in invasive ventilation. 5-year survival was 94% overall and was significantly higher for patients on NIV (97%) than invasively ventilated patients (84%). 10-year survival was 91% overall. Although some children were able to discontinue respiratory support (21% at 5 years and 42% at 10 years), the number of patients transitioned to adult services increased significantly over time (26% of total cohort). Patients with neuromuscular disease were less likely to discontinue support than other patients. CONCLUSIONS: The paediatric LTV population has expanded significantly over 15 years. Future planning of paediatric hospital and community services, as well as adult services, must take into account the needs of this growing population.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".