Core Outcome Measures for Clinical Research in Acute Respiratory Failure Survivors. An International Modified Delphi Consensus Study
Bibliographic record
Abstract
RATIONALE: Research evaluating acute respiratory failure (ARF) survivors' outcomes after hospital discharge has substantial heterogeneity in terms of the measurement instruments used, creating barriers to synthesizing study data. OBJECTIVES: To identify a minimum set of core outcome measures that are essential to include in all clinical research studies evaluating ARF survivors after discharge. METHODS: We conducted a three-round modified Delphi consensus process with 77 participants (47% female, 55% outside the United States), including clinical researchers from more than 16 countries across six continents, patients/caregivers, clinicians, and research funders. Participants reviewed standardized information on measure instruments for seven consensus-derived outcomes plus one recommended outcome. MEASUREMENTS AND MAIN RESULTS: Response rates were 91 to 97% across the three rounds. Among 75 measurement instruments evaluated, the following met a priori consensus criteria: EQ-5D and 36-item Short Form Health Survey version 2 (optional) for the "satisfaction with life and personal enjoyment" and "pain" outcomes, and both the Hospital Anxiety and Depression Scale and the Impact of Events Scale-Revised for the "mental health" outcome. No measures reached consensus for the following outcomes: cognition, muscle and/or nerve function, physical function, and pulmonary function. All measures considered for pulmonary function met consensus criteria for exclusion. The following measures did not reach the threshold for consensus but achieved the highest scores for their respective outcomes: the Montreal Cognitive Assessment (cognition), manual muscle testing and handgrip dynamometry (muscle and/or nerve function), and 6-minute-walk test (physical function). CONCLUSIONS: This Core Outcome Measurement Set is recommended for use in all clinical research evaluating ARF survivors after hospital discharge. In the future, researchers should evaluate measures for outcomes not reaching consensus.
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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 | 0.481 | 0.373 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.009 | 0.005 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.005 | 0.016 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".