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Record W2946190892 · doi:10.2215/cjn.14831218

Early Glomerular Hyperfiltration and Long-Term Kidney Outcomes in Type 1 Diabetes

2019· article· en· W2946190892 on OpenAlexaff
Mark E. Molitch, Xiaoyu Gao, Ionut Bebu, Ian H. de Boer, John M. Lachin, Andrew D. Paterson, Bruce A. Perkins, Amy K. Saenger, Michael W. Steffes, Bernard Zinman

Bibliographic record

VenueClinical Journal of the American Society of Nephrology · 2019
Typearticle
Languageen
FieldMedicine
TopicChronic Kidney Disease and Diabetes
Canadian institutionsUniversity of TorontoSickKids FoundationUniversity Health NetworkLunenfeld-Tanenbaum Research InstituteMount Sinai HospitalHospital for Sick Children
FundersNational Institute of Diabetes and Digestive and Kidney Diseases
KeywordsMedicineGlomerular hyperfiltrationInterquartile rangeRenal functionUrologyHazard ratioDiabetes mellitusConfidence intervalInternal medicineSurgeryEndocrinologyDiabetic nephropathy

Abstract

fetched live from OpenAlex

Background and objectives Glomerular hyperfiltration has been considered to be a contributing factor to the development of diabetic kidney disease (DKD). To address this issue, we analyzed GFR follow-up data on participants with type 1 diabetes undergoing 125 I-iothalamate clearance on entry into the Diabetes Control and Complications Trial (DCCT)/Epidemiology of Diabetes Interventions and Complications study. Design, setting, participants, & measurements This was a cohort study of DCCT participants with type 1 diabetes who underwent an 125 I-iothalamate clearance (iGFR) at DCCT baseline. Presence of hyperfiltration was defined as iGFR levels ≥140 ml/min per 1.73 m 2 , with secondary thresholds of 130 or 150 ml/min per 1.73 m 2 . Cox proportional hazards models assessed the association between the baseline hyperfiltration status and the subsequent risk of reaching an eGFR <60 ml/min per 1.73 m 2 . Results Of the 446 participants, 106 (24%) had hyperfiltration (iGFR levels ≥140 ml/min per 1.73 m 2 ) at baseline. Over a median follow-up of 28 (interquartile range, 23, 33) years, 53 developed an eGFR <60 ml/min per 1.73 m 2 . The cumulative incidence of eGFR <60 ml/min per 1.73 m 2 at 28 years of follow-up was 11.0% among participants with hyperfiltration at baseline, compared with 12.8% among participants with baseline GFR <140 ml/min per 1.73 m 2 . Hyperfiltration was not significantly associated with subsequent risk of developing an eGFR <60 ml/min per 1.73 m 2 in an unadjusted Cox proportional hazards model (hazard ratio, 0.83; 95% confidence interval, 0.43 to 1.62) nor in an adjusted model (hazard ratio, 0.77; 95% confidence interval, 0.38 to 1.54). Application of alternate thresholds to define hyperfiltration (130 or 150 ml/min per 1.73 m 2 ) showed similar findings. Conclusions Early hyperfiltration in patients with type 1 diabetes was not associated with a higher long-term risk of decreased GFR. Although glomerular hypertension may be a mechanism of kidney injury in DKD, higher total GFR does not appear to be a risk factor for advanced DKD.

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)0.004
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 score0.004
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.331
Teacher spread0.309 · 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

Citations52
Published2019
Admission routes1
Has abstractyes

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