Risk factors for surgical site infection following operative treatment of ankle fractures: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: This study aims to quantitatively summarize risk factors associated with surgical site infection after open reduction and internal fixation of ankle fractures. METHODS: Relevant original studies were searched in Medline, Embase, China National Knowledge Infrastructure, Wanfang database and Cochrane central database (all through April 2018). Studies eligible had to meet the quality assessment criteria by Newcastle-Ottawa Scale and to evaluate the risk factors for surgical site infection after open reduction and internal fixation of ankle fractures. The Stata 11.0 was used to this meta-analysis. RESULTS: 10 studies involving 8103 cases of ankle fracture treated by open reduction and internal fixation and 583 cases of surgical site infection were included in this meta-analysis. The incidence of surgical site infection is 7.19%. Our meta-analysis identified the significant increased risk factors with surgical site infection after open reduction and internal fixation of ankle fractures (P < 0.05) is: body mass index (both continuous and dichotomous variables); American Society of Anesthesiologists ≥3; diabetes; alcohol; open fracture; subluxation/dislocation; incision cleanness grade 2-4; high-energy mechanism; chronic heart disease; history of allergy; and use of antibiotic prophylaxis. After sensitivity analysis, meta-analysis results for these factors did not change the significance, indicating that the results were robust. CONCLUSION: Patients involved with the above-mentioned medical conditions were at risk for surgical site infection after open reduction and internal fixation of ankle fracture. The present study may in this respect serve as a baseline reference and this knowledge will allow the formulation of public health strategies to prevent surgical site infection after orthopedic surgery.
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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 | 0.015 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.044 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".