Patient Transitions Relevant to Individuals Requiring Ongoing Ventilatory Assistance: A Delphi Study
Bibliographic record
Abstract
BACKGROUND: Various terms, including 'prolonged mechanical ventilation' (PMV) and 'long-term mechanical ventilation' (LTMV), are used interchangeably to distinguish patient cohorts requiring ventilation, making comparisons and timing of clinical decision making problematic. OBJECTIVE: To develop expert, consensus-based criteria associated with care transitions to distinguish cohorts of ventilated patients. METHODS: A four-round (R), web-based Delphi study with consensus defined as >70% was performed. In R1, participants listed, using free text, criteria perceived to should and should not define seven transitions. Transitions comprised: T1 - acute ventilation to PMV; T2 - PMV to LTMV; T3 - PMV or LTMV to acute ventilation (reverse transition); T4 - institutional to community care; T5 - no ventilation to requiring LTMV; T6 - pediatric to adult LTMV; and T7 - active treatment to end-of-life care. Subsequent Rs sought consensus. RESULTS: Experts from intensive care (n=14), long-term care (n=14) and home ventilation (n=10), representing a variety of professional groups and geographical areas, completed all Rs. Consensus was reached on 14 of 20 statements defining T1 and 21 of 25 for T2. 'Physiological stability' had the highest consensus (97% and 100%, respectively). 'Duration of ventilation' did not achieve consensus. Consensus was achieved on 13 of 18 statements for T3 and 23 of 25 statements for T4. T4 statements reaching 100% consensus included: 'informed choice', 'patient stability', 'informal caregiver support', 'caregiver knowledge', 'environment modification', 'supportive network' and 'access to interprofessional care'. Consensus was achieved for 15 of 17 T5, 16 of 20 T6 and 21 of 24 T7 items. CONCLUSION: Criteria to consider during key care transitions for ventilator-assisted individuals were identified. Such information will assist in furthering the consistency of clinical care plans, research trials and health care resource allocation.
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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 | 0.078 | 0.087 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".