The effect of time to irrigation and debridement on the rate of reoperation in open fractures
Bibliographic record
Abstract
AIMS: Despite long-standing dogma, a clear relationship between the timing of surgical irrigation and debridement (I&D) and the development of subsequent deep infection has not been established in the literature. Traditionally, I&D of an open fracture has been recommended within six hours of injury based on animal studies from the 1970s, however the clinical basis for this remains unclear. Using data from a multicentre randomized controlled trial of 2,447 open fracture patients, the primary objective of this secondary analysis is to determine if a relationship exists between timing of wound I&D (within six hours of injury vs beyond six hours) and subsequent reoperation rate for infection or healing complications within one year for patients with open limb fractures requiring surgical treatment. METHODS: To adjust for the influence of patient and injury characteristics on the timing of I&D, a propensity score was developed from the dataset. Propensity-adjusted regression allowed for a matched cohort analysis within the study population to determine if early irrigation put patients independently at risk for reoperation, while controlling for confounding factors. Results were reported as odds ratios (ORs), 95% confidence intervals (CIs), and p-values. All analyses were conducted using STATA 14. RESULTS: In total, 2,286 of 2,447 patients randomized to the trial from 41 orthopaedic trauma centres across five countries had complete data regarding time to I&D. Prior to matching, the patients managed with early I&D had a higher proportion requiring reoperation for infection or healing complications (17% vs 13%; p = 0.019), however this does not account for selection bias of more severe injuries preferentially being treated earlier. When accounting for propensity matching, early irrigation was not associated with reoperation (OR 0.71 (95% CI 0.47 to 1.07); p = 0.73). CONCLUSION: 2021;103-B(6):1055-1062.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".