Prospective randomised controlled trial using the REthinking Clinical Trials (REaCT) platform and National Surgical Quality Improvement Program (NSQIP) to compare no preparation versus preoperative oral antibiotics alone for surgical site infection rates in elective colon surgery: a protocol
Bibliographic record
Abstract
INTRODUCTION: been an RCT published comparing OA alone versus no preparation. Of the four possible regimens (OA alone, MBP alone, OA plus MBP and no preparation), randomised evidence is conflicting for studied groups. Furthermore, guidelines vary, with recommendations for OA alone, OA plus MBP or no preparation. The National Surgical Quality Improvement Program (NSQIP) has automated data collection for surgical patients. Similarly, the 'REthinking Clinical Trials' (REaCT) platform increases RCT enrolment by simplifying pragmatic trial design. In this novel RCT protocol, we combine REaCT and NSQIP to compare OA alone versus no preparation for SSI rate reduction in elective colon surgery. To our knowledge, this is the first published RCT protocol that leverages NSQIP for data collection. In our feasibility study, 67 of 74 eligible patients (90%) were enrolled and 63 of 67 (94%) were adherent to protocol. The 'REaCT-NSQIP' trial design has great potential to efficiently generate level I evidence for other perioperative interventions. METHODS AND ANALYSIS: SSI rates following elective colorectal surgery after preoperative OA or no preparation will be compared. We predict 45% relative rate reduction of SSI, improvement in length of stay, reduced costs and increased quality of life, with similar antibiotic-related complications. Consent, using the 'integrated consent model', and randomisation on a mobile device are completed by the surgeon in a single clinical encounter. Data collection for the primary end point is automatic through NSQIP. Analysis of cost per weighted case, cost utility and quality-adjusted life years will be done. ETHICS AND DISSEMINATION: This study is approved by The Ontario Cancer Research Ethics Board. Results will be disseminated in surgical conferences and peer-reviewed journals. TRIAL REGISTRATION NUMBER: NCT03663504; Pre-results, recruitment phase.
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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 | 0.070 | 0.100 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.026 | 0.004 |
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".