Optimal surgical management in kidney and pancreas transplantation to minimise wound complications: A systematic review and meta-analysis
Bibliographic record
Abstract
Immunosuppression in transplant patients increases the risk of wound complications. However, an optimal surgical approach to kidney and pancreas transplantation can minimise this risk. We performed a systematic review and meta-analysis to examine factors contributing to incisional hernia formation in kidney and pancreas transplant recipients. Bias appraisal of studies was conducted via the Newcastle-Ottawa scale. We considered recipient factors, surgical methods, and complications of repair. The rate of incisional hernia formation in recipients of kidney and pancreas transplants was 4.4% (CI 95% 2.6–7.3, p < 0.001). Age above or below 50 years did not predict hernia formation (Q (1) = 0.09, p = 0.77). Body mass index (BMI) above 25 (10.8%, CI 95% 3.2–30.9, p < 0.001) increased the risk of an incisional hernia. Mycophenolate mofetil (MMF) use significantly reduced the risk of incisional hernia from 11.9% (CI 95% 4.3–28.7, p < 0.001) to 3.8% (CI 95% 2.5–5.7, p < 0.001), Q (1) = 4.25, p = 0.04. Sirolimus significantly increased the rate of incisional hernia formation from 3.7% (CI 95% 1.7–7.1, p < 0.001) to 18.1% (CI 95% 11.7–27, p < 0.001), Q (1) = 13.97, p < 0.001. While paramedian (4.1% CI 95% 1.7–9.4, p < 0.001) and Rutherford-Morrison incisions (5.6% CI 95% 2.5–11.7, p < 0.001) were associated with a lower rate of hernia compared to hockey-stick incisions (8.5% CI 95% 3.1–21.2, p < 0.001) these differences were not statistically significant (Q (1) = 1.38, p = 0.71). Single layered closure (8.1% CI 95% 4.9–12.8, p < 0.001) compared to fascial closure (6.1% CI 95% 3.4–10.6, p < 0.001) did not determine the rate of hernia formation [Q (1) = 0.55, p = 0.46]. Weight reduction and careful immunosuppression selection can reduce the risk of a hernia. Rutherford-Morrison incisions along with single-layered closure represent a safe and effective technique reducing operating time and costs.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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".