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Record W4281839833 · doi:10.2337/db22-405-p

405-P: Glycemic Control Impacts Renal Function Decline among People with Type 1 Diabetes after the Onset of Diabetic Kidney Disease

2022· article· en· W4281839833 on OpenAlexaboutno aff
HETAL SHAH, Janet B. McGill, Irl B. Hirsch, CHUN-YI WU, Andrzej T. Gałecki, Michael Mauer, Alessandro Doria

Bibliographic record

VenueDiabetes · 2022
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRenal functionAlbuminuriaType 2 diabetesInternal medicineGlycemicDiabetes mellitusKidney diseaseEndocrinologyCreatinineProteinuriaUrologyKidney

Abstract

fetched live from OpenAlex

While poor glycemic control increases the risk of diabetic kidney disease (DKD) , its impact on renal function decline among those with established DKD is unclear. To examine this, we tested the relationship between baseline HbA1c and renal outcomes in the 3-year Preventing Early Renal Loss (PERL) trial (n=530) , which included persons with type 1 diabetes (T1D) and early-to-moderate DKD (eGFR 40-100 ml/min/1.73m2 and persistent albuminuria and/or ongoing GFR decline) . In Cox regression models, baseline HbA1c was associated (p<0.0001) with a higher risk of progression to ESKD or serum creatinine doubling (HR 1.87 per HbA1c unit increment, 95% CI 1.42-2.47) , and in mixed-effects linear regression models, with 0.87 and 0.51 ml/min/1.73m2/year higher rates of estimated glomerular filtration rate (eGFR) and iohexol GFR decline (p<0.00for both) . Baseline albumin excretion rate (AER) was a modifier of the HbA1c-GFR slope relationships (p for interaction <0.05) , such that HbA1c was associated with a higher rate of GFR decline among those with AER≥200 μg/min than among those with AER<20 or 20≤AER<200 (Fig.1) . Thus, worse glycemic control in PERL was a major determinant of GFR decline and ESKD risk after DKD onset, especially in persons with overt proteinuria. Efforts to normalize HbA1c should continue among such persons. Disclosure H.Shah: None. J.B.Mcgill: Advisory Panel; Gilead Sciences, Inc., Lilly Diabetes, MannKind Corporation, Novo Nordisk A/S, Provention Bio, Inc., Salix Pharmaceuticals, Consultant; Bayer AG, Boehringer Ingelheim International GmbH, Research Support; Dexcom, Inc., Novo Nordisk. I.B.Hirsch: Consultant; Abbott Diabetes, Bigfoot Biomedical, Inc., GWave, Roche Diabetes Care, Research Support; Beta Bionics, Inc., Insulet Corporation, Medtronic. C.Wu: None. A.Galecki: None. M.Mauer: None. A.Doria: Research Support; Novo Nordisk Foundation. Perl consortium: n/a. Funding National Institutes of Health UC4DK101108Juvenile Diabetes Research Foundation 17-2012-377The Leona M. and Harry B. Helmsley Charitable Trust 2018PG-T1D014

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)0.002
metaresearch head score (Gemma)0.003
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 score0.007
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.202
Teacher spread0.197 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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