Liberation from mechanical ventilation using Extubation Advisor Decision Support (LEADS): protocol for a multicentre pilot trial
Bibliographic record
Abstract
INTRODUCTION: Timely successful liberation from invasive ventilation has the potential to minimise critically ill patients' exposure to invasive ventilation, save costs and improve outcomes; yet no trials have evaluated strategies to better inform extubation decision-making. The Liberation from mechanical ventilation using Extubation Advisor (EA) Decision Support (LEADS) Pilot Trial will assess the feasibility of a trial of a novel extubation decision support tool on feasibility metrics. The primary feasibility outcome will reflect our ability to recruit the desired population. Secondary feasibility outcomes will assess rates of (1) consent, (2) randomisation, (3) intervention adherence, (4) bidirectional crossovers and the (5) completeness of clinical outcomes collected. We will also evaluate physicians' perceptions of the usefulness of the EA tool and measure costs related to EA implementation. METHODS AND ANALYSIS: We will include critically ill adults who are invasively ventilated for ≥48 hours and who are ready to undergo a spontaneous breathing trial (SBT) with a view to extubation. Patients in the intervention arm will undergo an EA assessment that measures respiratory rate variability to derive an estimate of extubation readiness. Treating clinicians (respiratory therapists, attending physicians and intensive care unit fellows) will receive an EA report for each SBT conducted. The EA report will assist, rather than direct, extubation decision-making. Patients in the control arm will receive standard care. SBTs will be directed by clinicians, using current best evidence, without EA assessments or reports. We aim to recruit 1 to 2 patients/month in approximately 10 centres, and to achieve >75% consent rate, >95% randomisation among consented patients, >80% of EA reports generated and delivered (intervention arm), <10% crossovers (both arms) and >90% of patients with complete clinical outcomes. We will also report physician point-of-care perceptions of the usefulness of the EA tool. ETHICS AND DISSEMINATION: The LEADS Pilot Trial is approved by the Research Ethics Boards of all participating centres and Clinical Trials Ontario (4008). We will disseminate the LEADS trial findings through conference presentations and publication. TRIAL REGISTRATION NUMBER: NCT05506904. PROTOCOL VERSION: 24 April 2024.
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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 | 0.059 | 0.067 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.008 | 0.005 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.090 | 0.017 |
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".