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Record W2800508133 · doi:10.1111/ajt.14871

Clinical utility of complement-dependent C3d assay in kidney recipients presenting with late allograft dysfunction

2018· article· en· W2800508133 on OpenAlexafffund
James H. Lan, David Gjertson, Ying Zheng, Stephanie Clark, Elaine F. Reed, Michael Cecka

Bibliographic record

VenueAmerican Journal of Transplantation · 2018
Typearticle
Languageen
FieldMedicine
TopicRenal Transplantation Outcomes and Treatments
Canadian institutionsUniversity of British Columbia
FundersNational Institute of Allergy and Infectious DiseasesNational Institutes of HealthUniversity of British Columbia
KeywordsMedicineInternal medicineCreatinineKidney transplantationGastroenterologyMultivariate analysisUrologyDonor specific antibodiesKidney transplantBiopsyFibrosisKidneyPathology

Abstract

fetched live from OpenAlex

The objective of this study was to evaluate the utility of a complement-dependent C3d assay to risk stratify donor-specific antibodies (DSA) in a multicenter cohort of kidney recipients presenting with new-onset clinical dysfunction. A total of 106 subjects with evidence of DSA at a mean period of 5.3 ± 5.0 years posttransplant underwent testing using C3d reagents. C3d positivity was strongly associated with both the peak and sum IgG DSA MFI, with 98.3% (n = 57/58) of strongly reactive sera (peak MFI > 10 000) eliciting a positive signal. Patients with C3d+ DSA had a higher creatinine (P = .03), more significant graft fibrosis (P = .035), and a faster rate of graft loss posttest compared to those with C3d- DSA (P = .05). Subanalysis of patients with low-moderate level DSA confirmed the inferior outcome associated with C3d positivity. Despite the prognostic value of C3d as a stand-alone test, the assay did not provide independent risk prediction after incorporation of graft fibrosis in a multivariate model (P = .94). Overall, C3d offered limited discriminatory value for strong DSA with peak IgG MFI > 10 000 and in patients where histologic data is available, but its utilization may be considered in those with low-moderate level DSA and where an allograft biopsy is not accessible.

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)0.001
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 score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.034
GPT teacher head0.350
Teacher spread0.316 · 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

Citations9
Published2018
Admission routes2
Has abstractno

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