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1000 Titel
  • BMI variability and cardiovascular outcomes within clinical trial and real-world environments in type 2 diabetes: an IMI2 SOPHIA study
1000 Autor/in
  1. Massey, Robert J. |
  2. Chen, Yu |
  3. Panova-Noeva, Marina |
  4. Mattheus, Michaela |
  5. Siddiqui, Moneeza K. |
  6. Schloot, Nanette C. |
  7. Ceriello, Antonio |
  8. Pearson, Ewan R. |
  9. Dawed, Adem Y. |
1000 Verlag BioMed Central
1000 Erscheinungsjahr 2024
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2024-07-16
1000 Erschienen in
1000 Quellenangabe
  • 23(1):256
1000 Copyrightjahr
  • 2024
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1186/s12933-024-02299-8 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11253469/ |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • <jats:title>Abstract</jats:title><jats:sec> <jats:title>Background</jats:title> <jats:p>BMI variability has been associated with increased cardiovascular disease risk in individuals with type 2 diabetes, however comparison between clinical studies and real-world observational evidence has been lacking. Furthermore, it is not known whether BMI variability has an effect independent of HbA1c variability.</jats:p> </jats:sec><jats:sec> <jats:title>Methods</jats:title> <jats:p>We investigated the association between BMI variability and 3P-MACE risk in the Harmony Outcomes trial (<jats:italic>n</jats:italic> = 9198), and further analysed placebo arms of REWIND (<jats:italic>n</jats:italic> = 4440) and EMPA-REG OUTCOME (<jats:italic>n</jats:italic> = 2333) trials, followed by real-world data from the Tayside Bioresource (<jats:italic>n</jats:italic> = 6980) using Cox regression modelling. BMI variability was determined using average successive variability (ASV), with first major adverse cardiovascular event of non-fatal stroke, non-fatal myocardial infarction, and cardiovascular death (3P-MACE) as the primary outcome.</jats:p> </jats:sec><jats:sec> <jats:title>Results</jats:title> <jats:p>After adjusting for cardiovascular risk factors, a + 1 SD increase in BMI variability was associated with increased 3P-MACE risk in Harmony Outcomes (HR 1.12, 95% CI 1.08–1.17, <jats:italic>P</jats:italic> &lt; 0.001). The most variable quartile of participants experienced an 87% higher risk of 3P-MACE (<jats:italic>P</jats:italic> &lt; 0.001) relative to the least variable. Similar associations were found in REWIND and Tayside Bioresource. Further analyses in the EMPA-REG OUTCOME trial did not replicate this association. BMI variability’s impact on 3P-MACE risk was independent of HbA1c variability.</jats:p> </jats:sec><jats:sec> <jats:title>Conclusions</jats:title> <jats:p>In individuals with type 2 diabetes, increased BMI variability was found to be an independent risk factor for 3P-MACE across cardiovascular outcome trials and real-world datasets. Future research should attempt to establish a causal relationship between BMI variability and cardiovascular outcomes.</jats:p> </jats:sec>
1000 Sacherschließung
lokal Diabetes management
lokal Sodium-Glucose Transporter 2 Inhibitors/therapeutic use [MeSH]
lokal Type 2 diabetes
lokal Aged [MeSH]
lokal Risk Assessment [MeSH]
lokal Cardiovascular disease
lokal Cardiovascular Diseases/diagnosis [MeSH]
lokal Risk Factors [MeSH]
lokal Diabetes Mellitus, Type 2/mortality [MeSH]
lokal Randomized Controlled Trials as Topic [MeSH]
lokal 3P-MACE risk
lokal HbA1c variability
lokal Heart Disease Risk Factors [MeSH]
lokal Male [MeSH]
lokal Health outcomes
lokal Cardiovascular Diseases/mortality [MeSH]
lokal Sodium-Glucose Transporter 2 Inhibitors/adverse effects [MeSH]
lokal Diabetes Mellitus, Type 2/diagnosis [MeSH]
lokal BMI variability
lokal Female [MeSH]
lokal Diabetes Mellitus, Type 2/complications [MeSH]
lokal Biomarkers/blood [MeSH]
lokal Humans [MeSH]
lokal Treatment Outcome [MeSH]
lokal Cardiovascular Diseases/epidemiology [MeSH]
lokal Middle Aged [MeSH]
lokal Diabetes Mellitus, Type 2/blood [MeSH]
lokal Time Factors [MeSH]
lokal Body Mass Index [MeSH]
lokal Glycated Hemoglobin/metabolism [MeSH]
lokal Research
lokal Blood Glucose/metabolism [MeSH]
lokal Blood Glucose/drug effects [MeSH]
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://frl.publisso.de/adhoc/uri/TWFzc2V5LCBSb2JlcnQgSi4=|https://frl.publisso.de/adhoc/uri/Q2hlbiwgWXU=|https://frl.publisso.de/adhoc/uri/UGFub3ZhLU5vZXZhLCBNYXJpbmE=|https://frl.publisso.de/adhoc/uri/TWF0dGhldXMsIE1pY2hhZWxh|https://frl.publisso.de/adhoc/uri/U2lkZGlxdWksIE1vbmVlemEgSy4=|https://frl.publisso.de/adhoc/uri/U2NobG9vdCwgTmFuZXR0ZSBDLg==|https://frl.publisso.de/adhoc/uri/Q2VyaWVsbG8sIEFudG9uaW8=|https://frl.publisso.de/adhoc/uri/UGVhcnNvbiwgRXdhbiBSLg==|https://frl.publisso.de/adhoc/uri/RGF3ZWQsIEFkZW0gWS4=
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  1. Innovative Medicines Initiative 2 Joint Undertaking |
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    1000 Förderer Innovative Medicines Initiative 2 Joint Undertaking |
    1000 Förderprogramm -
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