Subclinical rejection and allograft survival in kidney transplantation: protocol for a systematic review and meta-analysis
Bibliographic record
Abstract
Introduction Subclinical rejection (SCR) refers to the presence of acute rejection without accompanying kidney allograft dysfunction. The impact of SCR on long-term graft survival remains a subject of ongoing debate. Methods and analysis We will perform a systematic search of databases including MEDLINE, Embase and Cochrane Central, from January 1995 to November 2023. We will include English-language studies involving adult kidney transplant patients who investigated SCR. We will exclude studies focused on ‘for-cause’ biopsies. Both title, abstract screening and full-text screening will be performed by two or more reviewers. The primary outcome of this study will be death-censored allograft loss. The secondary outcome will include development of subsequent rejection. For time-dependent outcomes, we will prioritise HRs and the 95% CIs. In cases where HRs are unavailable, we will calculate risk ratios based on the recorded events. The risk of bias will be assessed using the Cochrane Collaboration’s revised tool for assessing the risk of bias in randomised trials and the Newcastle-Ottawa scale for cohort studies. We will employ a random effects model. We will evaluate heterogeneity using the I 2 variable. We will assess publication bias by funnel plots, Begg and Mazumdar test, and Egger’s test. Ethics and dissemination Ethics approval does not apply as no original data will be collected. The results will be disseminated through peer-reviewed publications and conference presentations. PROSPERO registration number CRD42023463536.
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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 | 0.062 | 0.102 |
| Meta-epidemiology (narrow) | 0.006 | 0.004 |
| Meta-epidemiology (broad) | 0.021 | 0.025 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.049 | 0.005 |
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".