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Record W4249177352 · doi:10.1093/ehjci/ehaa946.2883

Obstructive sleep apnoe and cardiovascular, heart failure and mortality outcomes with empagliflozin versus placebo in the EMPA-REG OUTCOME trial

2020· article· en· W4249177352 on OpenAlexaff
H. Klar Yaggi, B Eliasson, Takehiro Kasai, Nikolaus Marx, B. Zinman, Silvio E. Inzucchi, C. Wanner, Isabella Zwiener, Brian S. Wojeck, Ian J. Neeland, Odd Erik Johansen

Bibliographic record

VenueEuropean Heart Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsUniversity Health NetworkMount Sinai Hospital
Fundersnot available
KeywordsEmpagliflozinMedicinePlaceboMaceInternal medicineType 2 diabetesDiabetes mellitusHeart failureHazard ratioCardiologyMyocardial infarctionEndocrinologyConfidence intervalConventional PCI

Abstract

fetched live from OpenAlex

Abstract Background/Introduction Obstructive sleep apnoe (OSA) and type 2 diabetes (T2D) occurs more frequently in persons with obesity, and both OSA and T2D are associated with metabolic disturbances that increases the risk for cardiovascular disease (CVD). In EMPA-REG OUTCOME, a randomized placebo-controlled outcome trial involving 7020 patients with T2D and CVD, the sodium glucose co-transporter (SGLT)-2 inhibitor empagliflozin reduced HbA1c, systolic blood pressure, waist circumference, and weight, and also reduced the risk of 3-point major adverse CV events (3P- MACE) by 14%, CV death by 38% and hospitalization for heart failure (HHF) by 35%. Purpose We investigated incidence rates of CV, HHF, and mortality outcomes in patients with or without OSA at baseline, and the treatment effect of empagliflozin, in EMPA-REG OUTCOME. Methods The trial included patients from 42 countries with T2D (with HbA1c 7.0–9.0% for drug-naïve patients and 7.0–10.0% for those on stable glucose-lowering therapy), established CVD, and estimated glomerular filtration rate >30 mL/min/1.73 m2. Patients were randomised (1:1:1) to receive empagliflozin 10 mg, empagliflozin 25 mg, or placebo once daily in addition to standard of care. All CV outcomes were independently adjudicated and events were pooled for the 10 and 25mg doses. In this post-hoc analysis, OSA were assessed based on investigator reports using MedDRA 18.0 and incidence rates for outcomes were reported by adjusted event-rates per 100 patient-years. Analysis of effects on outcomes were performed using Cox regression models with multivariable adjustments. Results Of 7020 patients with T2D and CVD, OSA was reported in 391 (5.6% [placebo 5.4%; pooled empagliflozin doses 5.7%]. Compared with patients without OSA at baseline, those with OSA were more frequent males (82.9% vs 70.8%), living in region North-America (63.2% vs 17.3%), and had more obesity (BMI ≥35 kg/m2: 55.2% vs 18.2%) and more coronary artery disease (88.0 vs 74.9%). Over a median 3.1 years, individuals with OSA at baseline relative to those without OSA in the placebo group, experienced 1.3–2.0 fold higher event rates for 3P-MACE (OSA vs no OSA: 6.49 vs 4.27/100-patient-year), CV death (2.57 vs 1.99), HHF (2.71 vs 1.38) and all-cause mortality (4.29 vs 2.78). Empagliflozin improved CV, HHF, and mortality outcomes regardless of presence of OSA at baseline (p-for interactions >0.05 [Figure 1]). Conclusions In this post-hoc exploratory analysis, patients with OSA had higher frequency of events for 3P-MACE, HHF and mortality. The cardio-protective effects of empagliflozin was consistent in those with and without OSA at baseline. Figure 1. Sleep apnea and empagliflozin Funding Acknowledgement Type of funding source: Private company. Main funding source(s): Boehringer Ingelheim and Eli Lilly 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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.065
GPT teacher head0.301
Teacher spread0.236 · 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
Published2020
Admission routes1
Has abstractyes

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