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Record W2095128587 · doi:10.1159/000070747

Increased Frequency of HLA A2/DR4 and A2/DR8 Haplotypes in Young Saskatchewan Aboriginal People with Diabetic End-Stage Renal Disease

2003· article· en· W2095128587 on OpenAlexaffabout
Roland Dyck, Clara Bohm, Helena Klomp

Bibliographic record

VenueAmerican Journal of Nephrology · 2003
Typearticle
Languageen
FieldMedicine
TopicChronic Kidney Disease and Diabetes
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsOdds ratioMedicineHuman leukocyte antigenInternal medicineConfidence intervalHaplotypeDiabetes mellitusDiseaseEnd stage renal diseaseHLA-DQGastroenterologyImmunologyAntigenGenotypeEndocrinologyBiologyGenetics

Abstract

fetched live from OpenAlex

AIMS: To determine the association of HLA with diabetic end-stage renal disease (DESRD) in Saskatchewan aboriginal people. METHODS: This was a retrospective study of HLA profiles in four groups of Saskatchewan residents with ESRD diagnosed from 1980 to 1998: aboriginal people with and without DESRD, and non-aboriginal people with and without DESRD. The aboriginal DESRD group was also subdivided into those <or=50 and >50 years of age. Frequencies of individual and combinations of HLA antigens were compared between groups and subgroups. RESULTS: HLA data were available for 634 subjects. Young aboriginal people with DESRD had a higher frequency of HLA-A2 than older AB DESRD subjects (69 vs. 36%; p = 0.03), and of HLA-DR4 and/or DR8 compared to older AB DESRD subjects (91 vs. 68%; p = 0.07) and AB non-DESRD subjects (91 vs. 67%; p = 0.03). Over 65% of young AB DESRD subjects had either an A2/DR4 or A2/DR8 haplotype (odds ratio 5.09 [confidence intervals 1.35, 20.15] versus older AB DESRD subjects; odds ratio 3.32 [confidence intervals 1.20, 9.3] versus AB non-DESRD subjects). Forty percent of young AB DESRD subjects were homozygous for at least one of A2, DR4 or DR8. CONCLUSIONS: Our findings suggest that DESRD in young AB subjects with T2DM has a genetic basis related to HLA.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.010
Threshold uncertainty score0.730

Codex and Gemma teacher scores by category

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

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 head0.004
GPT teacher head0.239
Teacher spread0.235 · 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.

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

Citations23
Published2003
Admission routes2
Has abstractyes

Explore more

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