Weaning strategies for children on home invasive mechanical ventilation
Bibliographic record
Abstract
Abstract Children who require home mechanical ventilation (HMV) with an artificial airway or invasive mechanical ventilation (HMV) have a possibility of successful weaning due to the potential of compensatory lung growth. Internationally accepted guidelines on how to wean from HMV in children is not available, we summarize the weaning strategies from the literature reviews combined with our 27‐year experience in the Pediatric Home Respiratory Care program at the tertiary care center in Thailand. The readiness to wean is considered in patients with hemodynamic stability, having effective cough measured by maximal inspiratory pressure, requiring a fraction of inspired oxygen (FiO2) < 40%, positive end expiratory pressure <5 cmH2O, and acceptable arterial blood gases. The strategies of weaning is start weaning during the daytime while the child is awake and close monitoring is feasible. Disconnect time is gradually increased through naps and sleeping hours. Weaning from the conventional mechanical ventilator to Bilevel PAP or CPAP are optional. Factors affected the successful weaning are mainly the underlying diseases, complications, growth and development, caregivers, and resources. Weaning should be stopped during acute illness or increased work of breathing. The readiness for decannulation could be determined by using the speaking devices, tracheostomy capping, and measurement of end‐expiratory pressure. Polysomnography and airway evaluation by bronchoscopy are recommended before decannulation. Weaning when the child is ready is crucial because living with HMV can be challenging and stressful. Failure to remove a tracheostomy when indicated can result in delayed speech, social problems as well as risk for infection.
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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 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".