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Record W4399973779 · doi:10.1155/2024/4421589

Renal Manifestations of IgG4‐Related Disease: A Concise Review

2024· review· en· W4399973779 on OpenAlexaff
Shahrukh T Towheed, Wayel R. Zanjir, Kevin Yi Mi Ren, Jocelyn Garland, Marie Clements-Baker

Bibliographic record

VenueInternational Journal of Nephrology · 2024
Typereview
Languageen
FieldMedicine
TopicIgG4-Related and Inflammatory Diseases
Canadian institutionsQueen's University
Fundersnot available
KeywordsMedicineDiseaseIgG4-related diseaseRetroperitoneal fibrosisPathologyGlomerulonephritisPresentation (obstetrics)Kidney diseaseNephritisRenal pathologyEpidemiologyIntensive care medicineKidneyFibrosisInternal medicineSurgery

Abstract

fetched live from OpenAlex

IgG4-related disease (IgG4-RD) is an immune-mediated disorder marked by fibro-inflammatory masses that can infiltrate multiple organ systems. Due to its relatively recent discovery and limited understanding of its pathophysiology, IgG4-related disease may be difficult to recognize and is consequently potentially underdiagnosed. Renal involvement is becoming regarded as one of the key features of this disease. To date, the most well-recognized renal complication of IgG4-related disease is tubulointerstitial nephritis, but membranous glomerulonephritis, renal masses, and retroperitoneal fibrosis have also been reported. This concise review has two objectives. First, it will briefly encapsulate the history, epidemiology, and presentation of IgG4-related disease. Second, it will examine the reported renal manifestations of IgG4-related disease, exploring the relevant histology, imaging, clinical features, and treatment considerations. This synthesis will be highly relevant for nephrologists, rheumatologists, general internists, and renal pathologists to raise awareness and help improve early recognition of IgG4-related kidney disease (IgG4-RKD).

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.031
GPT teacher head0.384
Teacher spread0.353 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of NephrologySame topicIgG4-Related and Inflammatory DiseasesFrench-language works237,207