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Record W3034982546 · doi:10.2337/db20-1128-p

1128-P: Empagliflozin and Obstructive Sleep Apnea (OSA): Exploratory Analysis from the EMPA-REG OUTCOME Trial

2020· article· en· W3034982546 on OpenAlexaboutno aff
Ian J. Neeland, Björn Eliasson, Takatoshi Kasai, Nikolaus Marx, Bernard Zinman, Silvio E. Inzucchi, Christoph Wanner, Isabella Zwiener, Brian S. Wojeck, H. Klar Yaggi, Odd Erik Johansen

Bibliographic record

VenueDiabetes · 2020
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsnot available
Fundersnot available
KeywordsEmpagliflozinEMPAMedicineInternal medicineType 2 diabetesDiabetes mellitusWaistObesityCardiologyPlaceboEndocrinology

Abstract

fetched live from OpenAlex

OSA occurs more frequently in obese persons and in those with type 2 diabetes (T2D) and is linked to increased risk of cardiovascular disease (CVD). This post-hoc analysis of EMPA-REG OUTCOME investigated the baseline (BL) prevalence of investigator-reported OSA; explored the effects of the empagliflozin (EMPA) vs. placebo (PBO) on metabolic parameters in patients with OSA; and sought to determine its potential effect on incident OSA. OSA at BL was reported in 391/7020 patients with T2D and established CVD (5.6% [PBO 5.4%; EMPA 5.7%]). Those with OSA were more likely to be male (82.9 vs. 70.8%), have moderate to severe obesity (BMI ≥ 35 kg/m2: 55.2% vs. 18.2%; mean weight 105.5 vs. 85.2 kg), and have greater prevalence of coronary artery disease (88.0 vs. 74.9%) at BL. Over a median 3.1 years, EMPA had similar PBO-adjusted reductions in HbA1c, waist circumference and systolic blood pressure regardless of OSA status at BL. However, EMPA had a larger effect on weight reduction in patients with OSA (week 28 adjusted mean (±SE) difference vs. PBO from BL: -2.9±0.4 vs. -1.9±0.1 kg in those without OSA and at week 52: -2.9±0.5 vs. -1.9 kg ±0.1, respectively). During follow-up, fifty patients developed new-onset OSA (Figure) and EMPA reduced this risk by 52% (HR 0.48 [95% CI 0.27, 0.83]). In conclusion, EMPA induces favorable metabolic effects in patients with OSA and T2D/CVD and may reduce new-onset OSA. Disclosure I.J. Neeland: None. B. Eliasson: Consultant; Self; Amgen, AstraZeneca, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Merck Sharp & Dohme Corp., Mundipharma International, Novo Nordisk A/S, Sanofi. T. Kasai: Other Relationship; Self; Fukuda Denshi, Philips Respironics, ResMed. N. Marx: Other Relationship; Self; Amgen, AstraZeneca, Bayer Vital, Boehringer Ingelheim International GmbH, Daiichi Sankyo, Kowa Research Institute, Inc., Medtronic, Merck Sharp & Dohme Corp., Novo Nordisk A/S, Pfizer Inc., Sanofi-Aventis. 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. 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. 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. I. Zwiener: Employee; Self; Boehringer Ingelheim International GmbH. B.S. Wojeck: None. H.K. Yaggi: None. O. Johansen: Employee; Self; Boehringer Ingelheim International GmbH. 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)0.002
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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.030
GPT teacher head0.258
Teacher spread0.228 · 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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