Protocol and statistical analysis plan for the identification and treatment of hypoxemic respiratory failure and acute respiratory distress syndrome with protection, paralysis, and proning: A type-1 hybrid stepped-wedge cluster randomised effectiveness-implementation study
Bibliographic record
Abstract
Objective: To describe a study protocol and statistical analysis plan (SAP) for the identification and treatment of hypoxemic respiratory failure (HRF) and acute respiratory distress syndrome (ARDS) with protection, paralysis, and proning (TheraPPP) study prior to completion of recruitment, electronic data retrieval, and analysis of any data. Design: TheraPPP is a stepped-wedge cluster randomised study evaluating a care pathway for HRF and ARDS patients. This is a type-1 hybrid effectiveness-implementation study design evaluating both intervention effectiveness and implementation; however primarily powered for the effectiveness outcome. Setting: Seventeen adult intensive care units (ICUs) across Alberta, Canada. Participants: We estimate a sample size of 18816 mechanically ventilated patients, with 11424 patients preimplementation and 7392 patients postimplementation. We estimate 2688 sustained ARDS patients within our study cohort. Intervention: An evidence-based, stakeholder-informed, multidisciplinary care pathway called Venting Wisely that standardises diagnosis and treatment of HRF and ARDS patients. Main outcome measures: The primary outcome is 28-day ventilator-free days (VFDs). The primary analysis will compare the mean 28-day VFDs preimplementation and postimplementation using a mixed-effects linear regression model. Prespecified subgroups include sex, age, HRF, ARDS, COVID-19, cardiac surgery, body mass index, height, illness acuity, and ICU volume. Results: This protocol and SAP are reported using the Standard Protocol Items: Recommendations for Interventional Trials guidance and the Guidelines for the Content of Statistical Analysis Plans in Clinical Trials. The study received ethics approval and was registered (ClinicalTrials.gov-NCT04744298) prior to patient enrolment. Conclusions: TheraPPP will evaluate the effectiveness and implementation of an HRF and ARDS care pathway.
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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 | 0.135 | 0.149 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.084 | 0.019 |
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".