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Abstract 13951: Change in Albuminuria Measured by Urine Albumin-to-Creatinine Ratio (UACR) and Associated Clinical Outcomes in Patients With Chronic Kidney Disease (CKD) Associated With Type 2 Diabetes (T2D)

2023· article· en· W4389957806 on OpenAlexaff
Navdeep Tangri, Qixin Li, Yan Chen, Rakesh Singh, Keith A. Betts, Youssef Farag, Scott C. Beeman, Yuxian Du, Sheldon X. Kong, Todd Williamson, Aozhou Wu, Manasvi Sundar, Kevin M. Pantalone

Bibliographic record

VenueCirculation · 2023
Typearticle
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMedicineAlbuminuriaHazard ratioKidney diseaseInternal medicineRenal functionDiabetes mellitusCreatinineType 2 diabetesProportional hazards modelMyocardial infarctionUrologyCardiologyConfidence intervalEndocrinology

Abstract

fetched live from OpenAlex

Introduction: The impact of change in albuminuria measured by UACR on key clinical outcomes (overall survival [OS], a composite cardiovascular [CV] outcome, and kidney disease progression) in patients (pts) with CKD associated with T2D is understudied. Hypothesis: A decreased UACR is associated with a lower risk of clinical outcomes, while an increased UACR is associated with a higher risk of clinical outcomes. Methods: Adult pts with an elevated UACR ≥30 mg/g (initial test) after T2D and CKD diagnosis were identified from the Optum EHR database (1/2007-9/2021). UACR change was categorized as increased (>30% change), stable (-30% to 30%), or decreased (<-30%) based on the percentage change between the initial test and the last test (between 6 to 24 months after the initial test). Clinical outcomes, including OS, a composite CV outcome (CV death, myocardial infarction, stroke, or heart failure hospitalization), and kidney disease progression (≥40% eGFR decline or kidney failure) were evaluated after the last UACR test using Kaplan-Meier analysis. Hazard ratios (HR) of clinical outcomes for UACR change were estimated using Cox proportional hazard models adjusting for baseline characteristics. Results: Among 160,382 pts (median follow-up: 2.9 years), 89,562 had decreased UACR, 35,117 had stable UACR, and 35,703 had increased UACR. Compared with pts with stable UACR, pts with decreased UACR had significantly lower risks for all clinical outcomes (Figure) with adjusted HR of 0.93 for OS, 0.93 for the composite CV outcome, and 0.84 for kidney disease progression, while pts with increased UACR had significantly higher risks for OS (HR=1.24), the composite CV outcome (HR=1.24), and kidney disease progression (HR=1.41). Conclusions: In pts with CKD associated with T2D, >30% UACR decrease was associated with a lower long-term risk of overall mortality, CV events, and kidney disease progression. These findings highlight the importance of albuminuria monitoring in these pts.

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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.025
GPT teacher head0.295
Teacher spread0.270 · 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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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