Weaning children from mechanical ventilation with a computer-driven system (closed-loop protocol): A pilot study*
Bibliographic record
Abstract
OBJECTIVE: To evaluate the applicability, tolerance, and efficacy of a closed-loop protocol to wean children from mechanical ventilation. DESIGN: Prospective single-center pilot study. SETTING: Tertiary care university hospital. PATIENTS: Twenty mechanically ventilated children aged between 1 and 17 yrs, with a body weight > or =10 kg, no inotropes, and no heavy sedation. INTERVENTIONS: Patients were weaned in pressure support mode by a closed-loop computerized protocol (closed-loop protocol) that interprets clinical data in real time and controls pressure support levels. MEASUREMENTS AND MAIN RESULTS: The closed-loop protocol applicability and tolerance were evaluated. The efficacy of this protocol was evaluated by comparing the duration of mechanical ventilation with a historical group of 20 patients weaned with a clinician-decision protocol. The closed-loop protocol successfully decreased pressure support ventilation in 16 children, recommended separation from the ventilator in 14 children, and did not cause any serious adverse events. Mechanical ventilation duration was 5.1 +/- 4.2 days in the closed-loop group and 6.7 +/- 11.5 days (mean +/- sd) in the clinician-decision group (p = .33) with no difference in the need for reintubation or noninvasive mechanical ventilation (one of 20 and four of 20, respectively; p = .20). CONCLUSIONS: A closed-loop protocol was successfully used to wean children from mechanical ventilation. Further studies are required to assess the impact of this novel therapeutic strategy on the length of mechanical ventilation.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".