Pre-operative mechanical bowel preparation and prophylactic oral antibiotics for pediatric patients undergoing elective colorectal surgery: a protocol for a randomized controlled feasibility trial
Bibliographic record
Abstract
BACKGROUND: Infections after elective colorectal surgery remain a significant burden for patients and the healthcare system. Adult studies suggest that the combination of oral antibiotics and mechanical bowel preparation is effective at reducing infections after colorectal surgery. In children, there is limited evidence for either of these practices and the utility of combining oral antibiotics with mechanical bowel preparation remains uncertain. METHODS: This study aims to determine the feasibility of conducting a randomized controlled trial assessing the efficacy of oral antibiotics, with or without mechanical bowel preparation, in reducing the rates of post-operative infection in pediatric colorectal surgery. Participants aged 3 months to 18 years undergoing elective colorectal surgery will be randomized pre-operatively to one of three trial arms: (1) oral antibiotics; (2) oral antibiotics and mechanical bowel preparation; or (3) standard care. Twelve patients will be included in each trial arm. Feasibility outcomes of interest include the rate of participant recruitment, post-randomization exclusions, protocol deviations, adverse events, and missed follow-up appointments. Secondary outcomes include the rate of post-operative surgical site infections, length of hospital stay, time to full enteral feeds, reoperation, readmission, and complications. DISCUSSION: If the results of this trial prove feasible, a multi-center trial will be completed with sufficient power to evaluate the optimal pre-operative bowel preperation for pediatric patients undergoing elective colorectal surgery. TRIAL REGISTRATION: ClinicalTrials.gov: NCT03593252.
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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 | 0.080 | 0.061 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.052 | 0.010 |
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".