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Record W3000308703 · doi:10.1016/j.ekir.2019.12.016

Autosomal Dominant Tubulointerstitial Kidney Disease—Uromodulin Misclassified as Focal Segmental Glomerulosclerosis or Hereditary Glomerular Disease

2020· article· en· W3000308703 on OpenAlexafffund
Justin Chun, Minxian Wang, Maris S. Wilkins, Andrea U. Knob, Ava Benjamin, Lihong Bu, Martin R. Pollak

Bibliographic record

VenueKidney International Reports · 2020
Typearticle
Languageen
FieldMedicine
TopicRenal Diseases and Glomerulopathies
Canadian institutionsUniversity of Calgary
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institutes of HealthAlberta Innovates - Health Solutions
KeywordsTamm–Horsfall proteinFocal segmental glomerulosclerosisMedicinePathologyKidney diseaseDiseaseKidneyGlomerulonephritisInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: , a gene encoding the tubular protein uromodulin, in 8 families with suspected glomerular disease. METHODS: was performed by Sanger sequencing. RESULTS: co-segregating with disease. Consistent with ADTKD, most patients in our study presented with autosomal dominant inheritance, subnephrotic range proteinuria, minimal hematuria, and renal impairment. Kidney biopsies showed histologic features of glomerular injury consistent with secondary FSGS, including focal sclerosis and partial podocyte foot process effacement. CONCLUSION: Our study demonstrates that with the use of standard clinical testing and kidney biopsy, clinicians were unable to make the diagnosis of ADTKD-UMOD; patients were often labeled with a clinical diagnosis of FSGS. We show that genetic testing can establish the diagnosis of ADTKD-UMOD with secondary FSGS. Genetic testing in individuals with FSGS histology should not be limited to genes that directly impair podocyte function.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.358
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.000

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 head0.021
GPT teacher head0.273
Teacher spread0.252 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations26
Published2020
Admission routes2
Has abstractyes

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