Prophylaxis for patients at Risk to Eliminate Post-operative Atrial Fibrillation (PREP-AF trial): a protocol for a feasibility randomized controlled study
Bibliographic record
Abstract
BACKGROUND: Postoperative atrial fibrillation (POAF) is a frequent adverse event after thoracic surgery with associated morbidity, mortality, and healthcare costs. It has been shown to be preventable with prophylactic amiodarone, which is only recommended in high-risk individuals due to the potential associated side effects. Risk factors for POAF have been identified and incorporated into a prediction model to identify high-risk patients. Further evaluation in the form of a multicenter clinical trial is required to assess the effectiveness of prophylaxis specifically in this high-risk population. The feasibility of such a trial first needs to be assessed. METHODS: The PREP-AF trial is a double-blind randomized controlled feasibility trial. Individuals undergoing major thoracic surgery who are identified to be high-risk by the POAF prediction model will be randomized 1:1 to receive a short course of amiodarone vs. placebo in the immediate postoperative period. The primary outcome is feasibility, which will be measured by the number of eligible patients identified, consented, and randomized; intervention adherence; and measurement of future outcomes of a full trial. DISCUSSION: This study will determine the feasibility of a randomized controlled trial to assess the effectiveness of prophylactic amiodarone, in high-risk patients undergoing major thoracic surgery. This will inform the development of a multi-center trial to establish if prophylactic amiodarone is safe and effective at reducing the incidence of POAF. Preventing this adverse event will not only improve outcomes for patients but also reduce the associated health resource utilization and costs. TRIAL REGISTRATION: ClinicalTrials.gov NCT04392921 . Registered on 19 May 2020.
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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 | 0.014 | 0.141 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".