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Record W3034462014 · doi:10.2337/db20-30-or

30-OR: Empagliflozin Delays Need for Insulin Initiation in Patients with Type 2 Diabetes and Cardiovascular Disease: Findings from EMPA-REG OUTCOME

2020· article· en· W3034462014 on OpenAlexaboutno aff
Muthiah Vaduganathan, Naveed Sattar, David Fitchett, Anne Pernille Ofstad, Martina Brueckmann, Jyothis T. George, Subodh Verma, Michaela Mattheus, Christoph Wanner, Silvio E. Inzucchi, Bernard Zinman, Javed Butler

Bibliographic record

VenueDiabetes · 2020
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsnot available
Fundersnot available
KeywordsEmpagliflozinMedicineInsulinEMPAInternal medicineEndocrinologyType 2 diabetesDiabetes mellitusHypoglycemia

Abstract

fetched live from OpenAlex

Insulin in T2D is associated with hypoglycemia and weight gain, requires training, can be expensive, and is generally not preferred by patients. Reducing insulin needs is attractive to both patients and practitioners. In EMPA-REG OUTCOME, 7020 patients were treated with empagliflozin (EMPA) 10, 25 mg, or placebo (PBO). Median follow-up was 3.1 yrs. After the first 12 weeks, changes in background glucose-lowering therapy were permitted. We assessed treatment effects of pooled EMPA vs. PBO on time to new initiation of insulin among insulin-naïve patients and time to total daily insulin dose increase by >20% among insulin-treated patients. In 3633 (52%) insulin-naïve patients, EMPA reduced need for insulin use vs. PBO by 54% (11.1% vs. 22.3%; HR 0.46 [0.39-0.54]), adjusted for key covariates (Figure). In 3387 (48%) patients using insulin at baseline, EMPA reduced need for a >20% increase in insulin dose by 57% (19.1% vs. 36.8%; HR 0.43 [0.37-0.49]). Reductions in incident insulin use was most pronounced in patients within 5 yrs of T2D diagnosis (HR 0.31 [0.21-0.45]) compared with T2D duration of >5-10 yrs (0.42 [0.31-0.59]) or >10 yrs (0.56 [0.44-0.71); Pinteraction =0.03. In patients with T2D and CVD, EMPA markedly and durably delays the need for insulin initiation, more so in those recently diagnosed, and reduces need for large dose increases in those already using insulin. Disclosure M. Vaduganathan: Advisory Panel; Self; Bayer AG, Boehringer Ingelheim Pharmaceuticals, Inc., Relypsa, Inc. Consultant; Self; Amgen, AstraZeneca, Baxter. N. Sattar: Advisory Panel; Self; Amgen, AstraZeneca, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Novo Nordisk A/S, Pfizer Inc., Sanofi. Research Support; Self; Boehringer Ingelheim Pharmaceuticals, Inc. D.H. Fitchett: Consultant; Self; AstraZeneca, Boehringer Ingelheim International GmbH. Speaker’s Bureau; Self; Lilly Diabetes. Other Relationship; Self; Novo Nordisk Inc. A. Ofstad: Employee; Self; Boehringer Ingelheim International GmbH. M. Brueckmann: Employee; Self; Boehringer Ingelheim International GmbH. J.T. George: Employee; Self; Boehringer Ingelheim International GmbH. S. Verma: Advisory Panel; Self; Amgen, AstraZeneca, Bayer AG, Boehringer Ingelheim (Canada) Ltd., Boehringer Ingelheim Pharmaceuticals, Inc., Eli Lilly and Company, Janssen Pharmaceuticals, Inc., Merck & Co., Inc., Novo Nordisk A/S, Sanofi. Research Support; Self; Amgen, AstraZeneca, Bayer AG, Boehringer Ingelheim International GmbH, Bristol-Myers Squibb, Janssen Pharmaceuticals, Inc., Merck & Co., Inc. Other Relationship; Self; AstraZeneca, AstraZeneca, Bayer AG, Boehringer Ingelheim (Canada) Ltd., Boehringer Ingelheim International GmbH, Eli Lilly and Company, Eli Lilly and Company, EOCI Pharmacomm, Janssen Pharmaceuticals, Inc., Merck & Co., Inc., Novartis Pharmaceuticals Canada Inc., Novo Nordisk A/S, Novo Nordisk A/S, Sanofi, Sanofi, Sun Pharmaceuticals, Toronto Knowledge Translation Working Group. M. Mattheus: None. C. Wanner: Advisory Panel; Self; Eli Lilly and Company, Merck & Co., Inc., Mundipharma International. Consultant; Self; Boehringer Ingelheim (Canada) Ltd., Sanofi Genzyme. Speaker’s Bureau; Self; AstraZeneca. Other Relationship; Self; Boehringer Ingelheim International GmbH. S.E. Inzucchi: Advisory Panel; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Lexicon Pharmaceuticals, Inc., Novo Nordisk A/S, Sanofi. Consultant; Self; Abbott, Merck & Co., Inc., vTv Therapeutics. B. Zinman: Advisory Panel; Self; Abbott, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Janssen Pharmaceuticals, Inc., Merck Sharp & Dohme Corp., Novo Nordisk Inc., Sanofi-Aventis. J. Butler: Consultant; Self; Amgen, Array BioPharma, AstraZeneca, Bayer AG, Boehringer Ingelheim Pharmaceuticals, Inc., Bristol-Myers Squibb, CVRx, G3 Pharmaceuticals, Innolife Co., Ltd., Janssen Pharmaceuticals, Inc., Luitpold Pharmaceuticals, Inc., Medtronic, Merck & Co., Inc., Novartis Pharmaceuticals Corporation, Relypsa, Inc., VIfor. Funding Boehringer Ingelheim and Eli Lilly and Company Diabetes Alliance

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)0.003
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: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.020
GPT teacher head0.229
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 designNon-randomized trial
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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Citations1
Published2020
Admission routes1
Has abstractyes

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