Prevention of Infections in Cardiac Surgery study (PICS): study protocol for a pragmatic cluster-randomized factorial crossover pilot trial
Bibliographic record
Abstract
Abstract Background A wide range of prophylactic antibiotic regimens are used for patients undergoing open-heart cardiac surgery. This reflects clinical equipoise in choice and duration of antibiotic agents. Although individual-level randomized control trials (RCT) are considered the gold standard when evaluating the efficacy of an intervention, this approach is highly resource intensive and a cluster RCT can be more appropriate for testing clinical effectiveness in a real-world setting. Methods/design We are conducting a factorial cluster-randomized crossover pilot trial in cardiac surgery patients to evaluate the feasibility of this design for a definite trial to evaluate the optimal duration and choice of perioperative antibiotic prophylaxis. Specifically, we will evaluate: (a) the non-inferiority of a single preoperative dose compared to prolonged prophylaxis and (b) the potential superiority of adding vancomycin to routine cefazolin in terms of preventing deep and organ/space sternal surgical site infections (s-SSIs). There are four strategies: (i) short-term cefazolin, (ii) long-term cefazolin, (iii) short-term cefazolin + vancomycin, and (iv) long-term cefazolin + vancomycin. These strategies are delivered in a different order in each health-care center participating in the trial. The centers are randomized to an order, and the current strategy becomes the standard operating procedure in that center during the study. The three feasibility outcomes include: (1) the proportion of patients receiving preoperative, intra-operative, and postoperative antibiotics according to the study protocol, (2) the proportion of completed follow-up assessments, and (3) a full and final assessment of the incidence of s-SSIs by the outcome adjudication committee. Discussion We believe that a cluster-randomized factorial crossover trial is an effective and feasible design for these research questions, allowing an evaluation of the clinical effectiveness in a real-world setting. A waiver of individual informed consent was considered appropriate by the research ethics boards in each participating site in Canada as long as an information letter with an opt-out option was provided. However, a waiver of consent was not approved at two sites in Germany and Switzerland, respectively. Trial registration Clinicaltrials.gov, NCT02285140 . Registered on 15 October 2015.
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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 | 0.049 | 0.045 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.011 | 0.005 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.053 | 0.008 |
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".