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Record W2982125719 · doi:10.1093/eurheartj/ehz747.0052

192Effect of dapagliflozin on cardiovascular outcomes in patients with type 2 diabetes according to baseline renal function and albuminuria status: Insights from DECLARE-TIMI 58

2019· article· en· W2982125719 on OpenAlexaff
Thomas A. Zelniker, Itamar Raz, Ofri Mosenzon, Jamie P. Dwyer, Hiddo J.L. Heerspink, Avivit Cahn, Kyung Ah Im, Deepak L. Bhatt, Lawrence A. Leiter, Darren K. McGuire, John Wilding, Ingrid Gause‐Nilsson, Anna Maria Langkilde, Marc S. Sabatine, Stephen D. Wiviott

Bibliographic record

VenueEuropean Heart Journal · 2019
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineAlbuminuriaDapagliflozinRenal functionInternal medicineCreatinineUrologyType 2 diabetesHazard ratioDiabetes mellitusTIMICardiologyEndocrinologyMyocardial infarctionConfidence intervalPercutaneous coronary intervention

Abstract

fetched live from OpenAlex

Abstract Background Renal dysfunction including both reduced estimated glomerular filtration rate (eGFR) and the presence of albuminuria have each been shown to predict cardiovascular (CV) outcomes. Sodium glucose co-transporter 2 inhibitors (SGLT2i), which promote glucose excretion in the kidneys, reduce CV events and hospitalizations for heart failure (HHF) in patients with type 2 diabetes mellitus (T2DM). Purpose To analyze the CV efficacy of dapagliflozin according to baseline renal function and albuminuria status in DECLARE-TIMI 58. Methods The DECLARE-TIMI 58 trial compared dapagliflozin vs. placebo in 17,160 patients with T2DM and a creatinine clearance >60 ml/min/1.73m2 at enrollment. The dual primary endpoints were CV death/HHF and MACE (MI, stroke, CV death). We categorized patients according baseline eGFR [<60 vs. ≥60 ml/min/1.73m2 according to the CKD-EPI formula] and urinary albumin:creatinine ratio (UACR) [<30 vs. ≥30 mg/g]. Cox regression models with interaction testing were applied. The Gail-Simon test was used to test for interaction of the absolute risk differences. Results In total, 5198 (30.3%) patients had albuminuria (UACR 30–300: n=4029; UACR >300: n=1169) and 1265 (7.4%) had an eGFR <60 ml/min/1.73m2. Accordingly, 10958 (63.9%) patients had no manifestation of CKD, 5367 (31.3%) had either an eGFR <60 ml/min/1.73m2 or albuminuria, and 548 (3.2%) patients had both manifestations. Patients with more abnormal markers had higher event rates for CV death/HHF (KM event rates at 4 years of 3.9%, 8.3%, 17.4%) and MACE (7.5%, 11.7%, and 18.9%) for no, 1, or 2 markers of CKD, respectively. The relative risk reductions for CV death/HHF and MACE were generally consistent across the subgroups (both P-interaction >0.29), though numerically greatest (42%) in patients with reduced eGFR and albuminuria. However, the absolute risk difference increased substantially in patients with greater kidney damage (absolute risk difference of CV death/HHF: −0.5%, −1.0%, and −8.3%, respectively; P-INT for ARD 0.002; Figure). See figure for MACE and component outcomes. Conclusions Patients with baseline renal disease had higher rates of adverse CV outcomes. Dapagliflozin reduced events with generally consistent relative risk, but reduced the absolute risk of CVD/HHF by the greatest amount in patients with kidney disease evidenced by both reduced eGFR and albuminuria. Acknowledgement/Funding AstraZeneca, Deutsche Forschungsgemeinschaft (ZE 1109/1-1)

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 score0.002
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
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)0.0010.000

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 head0.011
GPT teacher head0.220
Teacher spread0.209 · 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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Citations6
Published2019
Admission routes1
Has abstractyes

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