Multicentre randomised controlled trial protocol of urine CXCL10 monitoring strategy in kidney transplant recipients
Bibliographic record
Abstract
INTRODUCTION: Subclinical inflammation is an important predictor of death-censored graft loss, and its treatment has been shown to improve graft outcomes. Urine CXCL10 outperforms standard post-transplant surveillance in observational studies, by detecting subclinical rejection and early clinical rejection before graft functional decline in kidney transplant recipients. METHODS AND ANALYSIS: This is a phase ii/iii multicentre, international randomised controlled parallel group trial to determine if the early treatment of rejection, as detected by urine CXCL10, will improve kidney allograft outcomes. Incident adult kidney transplant patients (n~420) will be enrolled to undergo routine urine CXCL10 monitoring postkidney transplant. Patients at high risk of rejection, defined as confirmed elevated urine CXCL10 level, will be randomised 1:1 stratified by centre (n=250). The intervention arm (n=125) will undergo a study biopsy to check for subclinical rejection and biopsy-proven rejection will be treated per protocol. The control arm (n=125) will undergo routine post-transplant monitoring. The primary outcome at 12 months is a composite of death-censored graft loss, clinical biopsy-proven acute rejection, de novo donor-specific antibody, inflammation in areas of interstitial fibrosis and tubular atrophy (Banff i-IFTA, chronic active T-cell mediated rejection) and subclinical tubulitis on 12-month surveillance biopsy. The secondary outcomes include decline of graft function, microvascular inflammation at 12 months, development of IFTA at 12 months, days from transplantation to clinical biopsy-proven rejection, albuminuria, EuroQol five-dimension five-level instrument, cost-effectiveness analysis of the urine CXCL10 monitoring strategy and the urine CXCL10 kinetics in response to rejection therapy. ETHICS AND DISSEMINATION: The study has been approved by the University of Manitoba Health Research Ethics Board (HS20861, B2017:076) and the local research ethics boards of participating centres. Recruitment commenced in March 2018 and results are expected to be published in 2023. De-identified data may be shared with other researchers according to international guidelines (International Committee of Medical Journal Editors [ICJME]). TRIAL REGISTRATION NUMBER: NCT03206801; Pre-results.
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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 | 0.030 | 0.032 |
| Meta-epidemiology (narrow) | 0.007 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.004 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.059 | 0.009 |
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".