Wire Cerclage Versus Cable Closure After Sternotomy for Dehiscence and DSWI: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Objective Cable closure has been introduced as a potential alternative to traditional wire cerclage (WC) for closure of median sternotomy. To evaluate whether cable closure improves patient outcomes, we conducted a systematic review and meta-analysis of the literature. Methods Ovid versions of Medline and Embase, and Google Scholar were used for the literature search. This yielded 7 studies ( n = 2,758), which compared traditional WC to cable closure systems. Outcomes included deep sternal wound infection, sternal dehiscence, postoperative pain score, and sternal wound infection. Results We found significantly lower incidence of sternal dehiscence for cable closure compared to WC (risk ratio [RR] 0.14, 95% confidence interval [CI]: 0.03 to 0.59 , P < 0.01 , I 2 = 0%) but no difference in DSWI (RR 0.97, 95% CI: 0.39 to 2.42, P = 0.95, I 2 = 33%). Cable closure was also associated with lower pain when compared with the WC group (mean difference −1.04 points, 95% CI: −1.89 to −0.19 , P = 0.02, I 2 = 87%). Conclusions This study suggests that cable closure results in less incidence of sternal dehiscence and pain compared to WC. Nonetheless, there remains a limited number of studies on this topic and further high-quality studies are required to confirm the results of this meta-analysis.
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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 | 0.009 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.029 |
| Bibliometrics | 0.005 | 0.005 |
| 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) | 0.004 | 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, 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".