Risk factors for wound complications of closed calcaneal fractures after surgery: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: To better clinical outcomes, open reduction and internal fixations (ORIFs) have been commonly performed in the case of closed displaced intra-articular calcaneal fractures (CDICFs). Nonetheless, postoperative wound complications remain a significant problem. Therefore, the aim of our study is to summarise relevant evidence investigating the risk factors for postoperative wound complications of CDICFs following ORIFs. METHODS: A meta-analysis was conducted on relevant clinical studies to identify the risk factors for wound complications of CDICFs after ORIFs. Electronic databases were searched for all relevant studies up to October 2014. The Newcastle-Ottawa scale was used to evaluate the methodological quality, and study-specific odds ratios (ORs) were pooled using the fixed-effects model or random-effects model. Sensitivity analysis and meta-regression analysis was performed to evaluate the heterogeneity. RESULTS: Ten observational studies involving 1559 patients with 1651 fractures were included in this meta-analysis. The results showed that diabetes (OR, 9.76; p < 0.01), no drainage (OR, 5.86; p < 0.01), fracture severity (OR, 3.31; p < 0.01) and bone graft (OR, 1.74; p < 0.01) were the risk factors for wound complications of CDICFs after ORIFs. A trend of more wound complications in patients with a history of smoking was detected. However, female patients, ORIFs performed within 14 days of injury, smoking, hypertension and drinking did not significantly increase the risk of wound complications (p > 0.05). CONCLUSIONS: Based on available relevant evidence, bone graft, diabetes, no drainage and fracture severity were all associated with an increased risk of wound complications after ORIF for CDICFs.
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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 | 0.010 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.041 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| 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".