Longitudinal versus transverse incision for common femoral artery exposure: a systematic review and meta‐analysis
Bibliographic record
Abstract
BACKGROUND: A longitudinal or a transverse incision is routinely used for common femoral artery (CFA) exposure. Some believe a transverse incision is associated with a lower incidence of postoperative complications. We performed a systematic review and meta-analysis to evaluate the risk of postoperative surgical site infection, lymphatic complications, wound dehiscence and haematoma formation when using a longitudinal or transverse incision for CFA exposure. METHODS: Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines were adhered to. We searched various databases such as MEDLINE via PubMed and Embase for relevant studies from inception till 31 May 2020. Relevant search terms such as 'longitudinal', 'transverse', 'vertical', 'horizontal', 'femoral', 'incision' were used. We included both randomized controlled trials and case-controlled studies, and extracted data related to study characteristics and postoperative complications. We assessed risk of bias using the Cochrane risk of bias tool and the Newcastle-Ottawa scale. A random-effects meta-analysis was performed to obtain the pooled proportions and risk ratios (RR) for our study outcomes. RESULTS: We included seven studies with a total of 5922 groin incisions. A longitudinal incision was associated with a significantly higher incidence of wound infection (RR 2.93, 95% confidence interval (CI) 1.12-7.70, P = 0.03) and wound dehiscence (RR 2.87, 95% CI 1.06-7.77, P = 0.04). The risk of lymphatic complications (RR 1.09, 95% CI 0.39-3.05, P = 0.87) and wound haematoma (RR 2.85, 95% CI 0.88-9.21, P = 0.08) were similar. CONCLUSIONS: A longitudinal incision may be associated with a higher incidence of wound infection and wound dehiscence, as compared to using a transverse incision for CFA exposure.
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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 | 0.011 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.035 |
| Bibliometrics | 0.004 | 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".