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Record W2896703135 · doi:10.1111/dom.13556

The relationships between markers of tubular injury and intrarenal haemodynamic function in adults with and without type 1 diabetes: Results from the Canadian Study of Longevity in Type 1 Diabetes

2018· article· en· W2896703135 on OpenAlexafffundabout
Petter Bjornstad, Sunita Singh, Janet K. Snell‐Bergeon, Julie A. Lovshin, Yuliya Lytvyn, Leif E. Lovblom, Marian Rewers, Geneviève Boulet, Vesta Lai, Josephine Tse, Leslie Cham, Andrej Orszag, Alanna Weisman, Hillary A. Keenan, Michael H. Brent, Narinder Paul, Vera Bril, Bruce A. Perkins, David Z.I. Cherney

Bibliographic record

VenueDiabetes Obesity and Metabolism · 2018
Typearticle
Languageen
FieldMedicine
TopicChronic Kidney Disease and Diabetes
Canadian institutionsUniversity Health NetworkLunenfeld-Tanenbaum Research InstituteMount Sinai HospitalUniversity of Toronto
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institutes of HealthUniversity of TorontoJuvenile Diabetes Research Foundation International
KeywordsEffective renal plasma flowMedicineRenal functionInternal medicineEndocrinologyTamm–Horsfall proteinType 2 diabetesAlbuminuriaType 1 diabetesLipocalinDiabetes mellitusUrologyKidneyRenal blood flow

Abstract

fetched live from OpenAlex

Objective Our aim was to define the relationships between plasma biomarkers of kidney injury and intrarenal haemodynamic function (glomerular filtration rate [GFR], effective renal plasma flow [ERPF], renal vascular resistance [RVR]) in adults with type 1 diabetes (T1D). Methods The study sample comprised patients with longstanding T1D (duration ≥50 years), among whom 44 were diabetic kidney disease (DKD) resistors (eGFR >60 mL/min/1.73 m 2 and <30 mg/d urine albumin excretion) and 22 had DKD, in addition to 73 control participants. GFR INULIN and ERPF PAH were measured, RVR was calculated, and afferent (R A )/efferent (R E ) areteriolar resistances were derived from Gomez equations. Plasma neutrophil gelatinase‐associated lipocalin (NGAL), β2 microglobulin (B2M), osteopontin (OPN) and uromodulin (UMOD) were measured using immunoassay kits from Meso Scale Discovery. Results Plasma NGAL, B2M and OPN were higher and UMOD was lower in DKD patients vs DKD resistors and non‐diabetic controls. In participants with T1D, plasma NGAL inversely correlated with GFR (r = −0.33; P = 0.006) and ERPF (r = −0.34; P = 0.006), and correlated positively with R A (r = 0.26; P = 0.03) and RVR (r = 0.31; P = 0.01). In participants without T1D, NGAL and B2M inversely correlated with GFR (NGAL r = −0.18; P = 0.13 and B2M r = −0.49; P < 0.0001) and with ERPF (NGAL r = −0.19; P = 0.1 and B2M r = −0.42; P = 0.0003), and correlated positively with R A (NGAL r = 0.19; P = 0.10 and B2M r = 0.3; P = 0.01) and with RVR (NGAL r = 0.20; P = 0.09 and B2M r = 0.34; P = 0.003). Differences were significant after adjusting for age, sex, HbA1c, SBP and LDL. There were statistical interactions between T1D status, B2M and intrarenal haemodynamic function ( P < 0.05). Conclusions Elevated NGAL relates to intrarenal haemodynamic dysfunction in T1D, whereas elevated NGAL and B2M relate to intrarenal haemodynamic dysfunction in adults without T1D. These data may define a diabetes‐specific interplay between tubular injury and intrarenal haemodynamic dysfunction.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.211
Threshold uncertainty score0.425

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.229
Teacher spread0.217 · 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

Citations21
Published2018
Admission routes3
Has abstractyes

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