Optimizing the approach to monitoring allograft inflammation using serial urinary CXCL10/creatinine testing in pediatric kidney transplant recipients
Bibliographic record
Abstract
BACKGROUND: Urinary CXCL10/creatinine (uCXCL10/Cr) is proposed as an effective biomarker of subclinical rejection in pediatric kidney transplant recipients. This study objective was to model implementation in the clinical setting. METHODS: Banked urine samples at a single center were tested for uCXCL10/Cr to validate published thresholds for rejection diagnosis (>80% specificity). The positive predictive value (PPV) for rejection diagnosis for uCXCL10/Cr-indicated biopsy was modeled with first-positive versus two-test-positive approaches, with accounting for changes associated with urinary tract infection (UTI), BK and CMV viremia, and subsequent recovery. RESULTS: Seventy patients aged 10.5 ± 5.6 years at transplant (60% male) had n = 726 urine samples with n = 236 associated biopsies (no rejection = 167, borderline = 51, and Banff 1A = 18). A threshold of 12 ng/mmol was validated for Banff 1A versus no-rejection diagnosis (AUC = 0.74, 95% CI = 0.57-0.92). The first-positive test approach (n = 69) did not resolve a clinical diagnosis in 38 cases (55%), whereas the two-test approach resolved a clinical diagnosis in the majority as BK (n = 17/60, 28%), CMV (n = 4/60, 7%), UTI (n = 8/60, 13%), clinical rejection (n = 5/60, 8%), and transient elevation (n = 18, 30%). In those without a resolved clinical diagnosis, PPV from biopsy for subclinical rejection is 24% and 71% (p = .017), for first-test versus two-test models, respectively. After rejection treatment, uCXCL10/Cr level changes were all concordant with change in it-score. Sustained uCXCL10/Cr after CMV and BK viremia resolution was associated with later acute rejection. CONCLUSIONS: Urinary CXCL10/Cr reliably identifies kidney allograft inflammation. These data support a two-test approach to reliably exclude other clinically identifiable sources of inflammation, for kidney biopsy indication to rule out subclinical rejection.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".