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Record W4416138448 · doi:10.3390/ijms262210945

Molecular Diagnostics Supporting a ≥35% Diffuse Peritubular Capillaritis Extent Threshold for Diagnosis of AMR—A Retrospective Dual Center Study

2025· article· en· W4416138448 on OpenAlexaff
Michael Eder, Marian C. Clahsen‐van Groningen, Michael Mengel, Haris Omić, Daniel Cejka, Benjamin Adam, Nicolas Kozakowski, Željko Kikić

Bibliographic record

VenueInternational Journal of Molecular Sciences · 2025
Typearticle
Languageen
FieldMedicine
TopicRenal Transplantation Outcomes and Treatments
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBiopsyMolecular diagnosticsGene expressionGrading (engineering)Retrospective cohort studyAnatomical pathology

Abstract

fetched live from OpenAlex

Peritubular capillaritis (ptc) is a hallmark lesion of antibody-mediated rejection (AMR), but the grading of its extent is historically based on arbitrary defined cut-offs. Molecular AMR diagnosis via intragraft gene expression measurements may provide evidence to challenge established ptc categories. We retrospectively included 38 renal allograft biopsies from clinical routine, performed because of suspicion of AMR. Biopsies were re-assessed by an experienced nephropathologist and intragraft gene expression was measured using the NanoString nCounter® platform. Ptc categories were correlated with AMR gene expression to identify a ptc extent cut-off with optimal prediction of molecular diagnosis of AMR [gene expression levels above first quartile (AMRQ>1)]. Finally, an independent validation cohort (n = 25, Erasmus MC, Rotterdam, The Netherlands) was included to reproduce the results. Re-assessment of biopsies revealed AMR in 26/68.4%, mixed rejection in 5/13.2%, and T-cell-mediated rejection in 3/7.9%. Biopsies with diffuse ptc had significantly higher AMR gene expression compared to biopsies with focal ptc and biopsies with no ptc (64.0/53.3–84.0 vs. 31.5/27.0–49.5, p = 0.023 and 27.0/14.3–31.8, p = 0.003, median/IQR). Sensitivity analysis revealed that a ≥35% ptc cut-off resulted in higher AUCs for predicting AMRQ>1 compared to ptc50% (AUC 0.78, 95% CI: 0.63–0.93, p = 0.009 versus AUC: 0.74, CI: 0.56–0.90, p = 0.03). In the validation cohort, only the ptc35–, but not the ptc50%, cut-off significantly predicted AMRQ>1 (AUC 0.75, 95% CI: 0.54–0.96 p = 0.04 vs. AUC 0.69, CI: 0.46–0.93, p = 0.13). Using intragraft gene expression measurement, we identified a new ptc extent threshold with better prediction of molecular AMR. The newly proposed cut-off of ≥35% could potentially improve diagnostic evaluation and prognostication in cases with suspected or diagnosed AMR.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.018
GPT teacher head0.347
Teacher spread0.329 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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