Effectiveness of Iodophor vs Chlorhexidine Solutions for Surgical Site Infections and Unplanned Reoperations for Patients Who Underwent Fracture Repair
Bibliographic record
Abstract
Importance: The risk of developing a surgical site infection after extremity fracture repair is nearly 5 times greater than in most elective orthopedic surgical procedures. For all surgical procedures, it is standard practice to prepare the operative site with an antiseptic solution; however, there is limited evidence to guide the choice of solution used for orthopedic fracture repair. Objective: To compare the effectiveness of iodophor vs chlorhexidine solutions to reduce surgical site infections and unplanned fracture-related reoperations for patients who underwent fracture repair. Design, Setting, and Participants: The PREP-IT (Program of Randomized Trials to Evaluate Pre-operative Antiseptic Skin Solutions in Orthopaedic Trauma) master protocol will be followed to conduct 2 multicenter pragmatic cluster randomized crossover trials, Aqueous-PREP (Pragmatic Randomized Trial Evaluating Pre-Operative Aqueous Antiseptic Skin Solution in Open Fractures) and PREPARE (Pragmatic Randomized Trial Evaluating Pre-Operative Alcohol Skin Solutions in Fractured Extremities). The Aqueous-PREP trial will compare 4% aqueous chlorhexidine vs 10% povidone-iodine for patients with open extremity fractures. The PREPARE trial will compare 2% chlorhexidine in 70% isopropyl alcohol vs 0.7% iodine povacrylex in 74% isopropyl alcohol for patients with open extremity fractures and patients with closed lower extremity or pelvic fractures. Both trials will share key aspects of study design and trial infrastructure. The studies will follow a pragmatic cluster randomized crossover design with alternating treatment periods of approximately 2 months. The primary outcome will be surgical site infection and the secondary outcome will be unplanned fracture-related reoperations within 12 months. The Aqueous-PREP trial will enroll a minimum of 1540 patients with open extremity fractures from at least 12 hospitals; PREPARE will enroll a minimum of 1540 patients with open extremity fractures and 6280 patients with closed lower extremity and pelvic fractures from at least 18 hospitals. The primary analyses will adhere to the intention-to-treat principle and account for potential between-cluster and between-period variability. The patient-centered design, implementation, and dissemination of results are guided by a multidisciplinary team that includes 3 patients and other relevant stakeholders. Discussion: The PREP-IT master protocol increases efficiency through shared trial infrastructure and study design components. Because prophylactic skin antisepsis is used prior to all surgical procedures and the application, cost, and availability of all study solutions are similar, the results of the PREP-IT trials are poised to inform clinical guidelines and bring about an immediate change in clinical practice. Trial Registration: ClinicalTrials.gov Identifiers: NCT03385304 and NCT03523962.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".