A Systematic Review and Meta‐Analysis of Combined Antibiotic Spacer with Ilizarov Methods in the Treatment of Infected Nonunion of Tibia
Bibliographic record
Abstract
Background . The objective of this systematic review was to evaluate current studies available reporting the antibiotic spacer combined with Ilizarov methods in the treatment of infected nonunion of tibia and to perform meta‐analysis of bone results and infection recurrence to assess the efficacy of an antibiotic spacer combined with Ilizarov methods. Methods . The MEDLINE, Embase, Cochrane Library, CNKI, and CBM (Chinese Biological Medicine) databases were searched for articles published between January 2000 and July 2020. Assessment of study quality was performed using a modified version of the Newcastle‐Ottawa scale. Effect size and 95% confidence intervals were calculated for the main outcome. Heterogeneity was assessed. Fixed‐effect modeling and Stata version 15.1 were used to analyze the data. Sensitivity analyses were conducted with the evidence of heterogeneity. Results . 11 studies involving 210 patients with infected nonunion of tibia were finally included in our meta‐analysis. Bone results and infection recurrence were analyzed based on the single‐arm meta‐analysis. The average of external fixation index (EFI) was 46.88 days/cm in all studies included. The excellent rate in bone results and the rate of infection recurrence was 65% (95% CI: [0.22, 0.97], I 2 = 0.0 % , P = 0.932) and 6.99% (95% CI: [0.052, 0.325], I 2 = 0.0 % , P = 1.000) in patients with infected nonunion of tibia treated with an antibiotic spacer combined with Ilizarov methods. Conclusions . Our meta‐analysis revealed that the patients with infected nonunion of tibia treated with an antibiotic spacer combined with Ilizarov methods had a high rate of excellent bone results and a low rate of infection recurrence. Therefore, combining the antibiotic spacer with Ilizarov methods may be an applicable choice for repairing and reconstructing infected nonunion of tibia.
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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) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| 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".