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Record W2796003675 · doi:10.1111/ajt.14758

Recurrent IgG4-related tubulointerstitial nephritis concurrent with chronic active antibody mediated rejection: A case report

2018· article· en· W2796003675 on OpenAlexaff
Rajni Chibbar, Glenda Wright, Pouneh Dokouhaki, Bhanu Prasad, M. Mengel, Lynn D. Cornell, Ahmed Shoker

Bibliographic record

VenueAmerican Journal of Transplantation · 2018
Typearticle
Languageen
FieldMedicine
TopicIgG4-Related and Inflammatory Diseases
Canadian institutionsRegina General HospitalUniversity of AlbertaUniversity of Saskatchewan
Fundersnot available
KeywordsMedicineImmunosuppressionIgG4-related diseaseConcomitantNephritisKidney diseaseAntibodyKidneyPathologyFibrosisInterstitial nephritisKidney transplantationImmunologyGastroenterologyInternal medicine

Abstract

fetched live from OpenAlex

IgG4-related disease is a relatively newly described entity that can affect nearly any organ, including the kidneys, where it usually manifests as tubulointerstitial nephritis (IgG4-TIN). The diagnosis can be suggested by characteristic histological features, including an inflammatory infiltrate with increased IgG4-positive plasma cells associated with "storiform" fibrosis. Serum IgG4 is usually elevated. In the native kidney and other organs, there is typically a brisk response to treatment with immunosuppression. Recurrence of IgG4-TIN after renal transplant has not been described in the literature. Here, we describe the first case of recurrent IgG4-TIN in a young patient concomitant with chronic active antibody mediated rejection five years after kidney transplant. Recurrent IgG4-TIN could be diagnosed by the characteristic histopathologic features and increased IgG4-positive plasma cells. Despite maintenance immunosuppression, this disease may recur in the kidney allograft.

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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0040.003
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0050.003
Science and technology studies0.0050.004
Scholarly communication0.0040.005
Open science0.0040.003
Research integrity0.0110.006
Insufficient payload (model declined to judge)0.0030.002

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 head0.006
GPT teacher head0.279
Teacher spread0.273 · 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 designCase report
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

Citations10
Published2018
Admission routes1
Has abstractno

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