Perioperative intensive glycemic control for liver transplant recipients to prevent surgical site infection: A systematic review and meta‐analysis
Bibliographic record
Abstract
BACKGROUND: Surgical Site Infections (SSIs) are common among liver transplant recipients and result in adverse patient outcomes. Standard glycemic control is effective in reducing SSIs. Some studies suggest intensive glycemic control reduces the risk of SSI further. METHODS: For this systematic review, were searched for studies comparing perioperative intensive and standard glycemic control in liver transplant recipients. Clinical trials registries and reference lists of included studies were also searched. No date or language restrictions were applied. Randomized controlled trials (RCTs) were assessed using Cochrane risk of bias tool and GRADE method. Cohort studies were assessed using the Newcastle-Ottawa Scale. RESULTS: Two RCTs and three cohort studies met the inclusion criteria. Low-quality evidence from the two RCTs in a meta-analysis with 264 recipients found it was uncertain whether the risk of SSI was reduced by having intensive glycemic control (Risk Ratio [RR] 1.52, 95% CI 0.66-3.51). However, there was an increased risk of hypoglycemia among recipients having intensive glycemic control (RR 2.34, 95% CI 1.40-3.92) n = 264. Meta-analyses found it uncertain whether secondary outcomes, allograft rejection and death, were reduced among recipients having intensive glycemic control; (RR 0.85, 95% CI 0.48-1.50) and (RR 0.92, 95% CI 0.44-1.95), respectively. The two cohort studies were poor quality and presented conflicting outcomes on the effects of intensive blood glucose control on SSI. CONCLUSION: There is insufficient evidence to recommend the use of intensive glycemic control among liver transplant recipients to reduce SSIs.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.005 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".