Consensus on the definition, components, timeframe and grading of composite outcome of postoperative pulmonary complication—protocol for an international mixed-method consensus study (PrECiSIOn)
Bibliographic record
Abstract
INTRODUCTION: Postoperative pulmonary complications (PPCs) represent a significant cause of postoperative morbidity and even mortality. However, there is a lack of consensus regarding this composite endpoint, the definition of the individual components, classification and optimal outcome measures. This study aims to refine the PPCs composite framework by evaluating its construct validity, assessing the necessity and risks of a composite measure and exploring the feasibility of differentiating severity categories. METHODS: A Delphi consensus process will be conducted, engaging an international multidisciplinary group of 30-40 panellists, including clinicians, researchers, patients, public representatives and health economists. Through iterative rounds, the study will seek agreement on the individual components of the PPCs composite. Additionally, consensus will establish a framework for a composite outcome measure based on a standardised severity classification, appropriate timeframes and weighted grading of PPCs. ANALYSIS: tests or the Kruskal-Wallis test. ETHICS AND DISSEMINATION: The study will be conducted in strict compliance with the principles of the Declaration of Helsinki and will adhere to ACCORD guidance for reporting. Ethics approval has been obtained for this study from the University of Wolverhampton, UK (SOABE/202425/staff/3). Informed consent will be obtained from all panellists before the commencement of the Delphi process. The results of the study will be published in a peer-reviewed journal with the authorship assigned in accordance with ICMJE requirements. TRIAL REGISTRATION NUMBER: NCT06916598 (clinicaltrials.gov).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".