Skin Antisepsis Prior to Surgical Fixation of Open Extremity Fractures
Bibliographic record
Abstract
Open fractures are devastating injuries that lead to significant morbidity and prolonged disability to a large number of patients worldwide. In addition to bony union, the prevention of infection is a primary goal in the surgical treatment of open fractures, and is an important factor in determining a positive outcome. In addition to preoperative antibiotics and tetanus prophylaxis, along with surgical irrigation and debridement, perioperative skin antisepsis is part of the standard of care for these injuries. Despite recent randomized trials investigating different primary active ingredients in these skin antiseptic agents, it remains unclear whether alcohol-based skin antiseptics outperform aqueous solutions. This thesis comprises a combined analysis utilizing all open fracture participants from the PREP-IT trials, A-PREP and PREPARE. With these data, we were able to compare the risk of surgical site infection between alcohol-based and aqueous solutions, as well as examine specific subgroups including upper vs lower extremity open fractures as well as stratifying the fractures based on the severity of soft-tissue injury. The secondary outcome was to compare rates of unplanned reoperation up to 1-year following definitive fracture fixation. We demonstrated that for a large and diverse population of open fracture patients, the use of an alcohol-based or aqueous solution did not have a significant effect on the risk of surgical site infection following surgery for an open fracture. Moreover, we showed that there was also no significant difference in the risk of unplanned reoperation. These findings suggest that unlike in closed fractures as demonstrated by PREPARE, in open fractures the choice of surgical skin antiseptic agent has little impact on the risk of surgical site infection. This provides surgeons with the knowledge that either an alcohol-based or aqueous skin antiseptic solution can be used, and supports the use of iodine povacrylex in alcohol for all fractures given its proven effectiveness in the closed fracture population.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".