Early surgical complications following kidney transplantation in adults: A systematic review
Bibliographic record
Abstract
OBJECTIVE: To quantify and characterise short-term (<90 days) surgical complications following kidney transplantation and identify risk factors for complications. METHODS: This systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and the protocol registered with PROSPERO (ID CRD42024535328). Studies reporting surgical and postoperative complications within 90 days of surgery were included as well as studies reporting on groups of complications such as urological, vascular or wound related. The quality of evidence was assessed using the Newcastle-Ottawa Scale (NOS) and number of fulfilled Martin criteria. RESULTS: Of 1654 articles screened, 30 were included. In studies reporting on complications within 30 days of surgery the weighted overall complication rate was 41 % (range 13-70 %), the weighted reoperation rate was 13 % (range 9.8-17 %) and the weighted rate of major complications was 19 % (range 7.6-24 %). In studies reporting on complications within 90 days of surgery the weighted overall complication rate was 36 % (range 12-60 %), the weighted reoperation rate was 17 % (range 5.0-23 %) and the weighted rate of major complications was 24 % (range 19-25 %). Studies were heterogenous and the quality was rated poor to good according to the NOS and fulfilling a median of 7 Martin criteria (range 4-9). Possible risk factors for complications included high BMI, recipient age and sex. CONCLUSION: Kidney transplantation remains a high-risk surgical procedure. We identified considerable variation in how complications were reported, limiting comparison of outcomes between centres as well as the potential impact of peri-operative interventions to improve surgical outcomes.
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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 | 0.034 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.010 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".