Is the Risk of Infection Lower with Sutures than with Staples for Skin Closure After Orthopaedic Surgery? A Meta-analysis of Randomized Trials
Bibliographic record
Abstract
BACKGROUND: Two previous meta-analyses comparing staples versus sutures have led to conflicting relative risks for surgical site infection between skin closure methods after orthopaedic surgery. Consequently, the choice of sutures or staples for skin closure continues to be a subject of conversation. Recently, additional randomized trials have been published, and an updated meta-analysis is needed to inform this debate. QUESTIONS/PURPOSES: To determine using a meta-analysis of randomized trials (1) whether there is a difference in surgical site infection (SSI) between staples and sutures for skin closure after orthopaedic surgery, and (2) whether that finding remains the same when the analysis is limited to randomized trials with a low risk of bias. METHODS: A systematic review and meta-analysis of randomized controlled trials (RCTs) comparing staples with sutures for skin closure after orthopaedic surgery was conducted. We excluded barbed sutures, surgical zippers, and skin adhesives from this meta-analysis. Medline, Embase, CINAHL, Cochrane Library, and Global Index Medicus were searched from date of inception to October 18, 2017. The sole outcome of interest was SSI as defined by the original study authors, with preference given to Center for Disease Control and Prevention (CDC) definitions whenever possible, recognizing that this may result in the pooling of more common minor events with rarer, more severe events, and in so doing, overestimate between-group differences. Because of this, subgroup analysis was planned based on severity of infection. Relative risk was calculated using a random-effects model (relative risk [RR], 95% confidence interval [CI]). Heterogeneity was estimated using I. Publication bias was explored using visual inspection of the funnel plot and Egger's test. Subgroup analysis was planned for type of orthopaedic surgery, suture material, SSI category, and country development index. Subgroup interaction p values were calculated. The Cochrane risk of bias tool was used to assess study quality. Sensitivity analysis was planned to assess whether the results changed when the analysis was limited to studies with low risk of bias. In total, 17 RCTs (2446 patients) were eligible, of which five RCTs (501 patients) were at low risk of bias. RESULTS: In the primary analysis, patients randomized to staples had a higher risk of SSI versus those who received sutures for skin closure (RR, 2.05; 95% CI,1.38-3.06; I = 0%). However, most of the events were driven by superficial SSI, and only two deep infections were explicitly reported in total (one in each group). After a post-hoc sensitivity analysis excluded a highly influential trial with high risk of bias, the results were highly fragile, relying on a difference of only four additional events in the staples group. When we limited the analysis to RCTs with low risk of bias, no difference was found between sutures and staples in terms of SSI (RR, 1.45; 95% CI, 0.31-6.79; I = 46%). Effect sizes were consistent across subgroups (p value for subgroup interaction was not significant for elective versus trauma; hip versus knee arthroplasty; suture material; high versus middle- versus low-income settings). CONCLUSIONS: Even in this relatively large meta-analysis, existing RCTs do not provide definitive evidence of a difference in SSI risk when staples are used instead of sutures for skin closure after orthopaedic surgery. Currently, the total body of evidence remains weak and, even when limiting to only low risk of bias studies, it is not possible to rule in or rule out clinically important differences between staples and sutures. Until randomized studies of adequate power and followup duration are performed to definitively inform this issue, the choice between staples versus sutures should be based on other factors such as local availability, surgeon preference, and cost. LEVEL OF EVIDENCE: Level I, therapeutic study.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Meta-epidemiology (broad) Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Meta-analysis | low |
| gpt | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Meta-analysis | high |
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 | 0.047 | 0.113 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.072 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".