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Clinical Phenotypes in Patients With Type 2 Diabetes Mellitus: Characteristics, Cardiovascular Outcomes and Treatment Strategies.
Gouda, Pishoy; Zheng, Sijia; Peters, Tricia; Fudim, Marat; Randhawa, Varinder Kaur; Ezekowitz, Justin; Mavrakanas, Thomas A; Giannetti, Nadia; Tsoukas, Michael; Lopes, Renato; Sharma, Abhinav.
Afiliação
  • Gouda P; Department of Medicine, Division of Cardiology, University of Alberta, Edmonton, AB, Canada.
  • Zheng S; Department of Medicine, McGill University Health Centre, 1001 Decarie Blvd, Montreal, QC, H4A3J1, Canada.
  • Peters T; Centre for Clinical Epidemiology, Lady Davis Institute for Medical Research, Montreal, QC, Canada.
  • Fudim M; Division of Endocrinology, Department of Medicine, The Jewish General Hospital, McGill University, Montreal, QC, Canada.
  • Randhawa VK; Department of Medicine, Duke Clinical Research Institute, Duke University Medical Center, Durham, NC, USA.
  • Ezekowitz J; Department of Cardiovascular Medicine, Kaufman Center for Heart Failure and Recovery, Cleveland Clinic Foundation, Cleveland, OH, 44195, USA.
  • Mavrakanas TA; Department of Medicine, Division of Cardiology, University of Alberta, Edmonton, AB, Canada.
  • Giannetti N; Canadian VIGOUR Centre, Alberta, Canada.
  • Tsoukas M; Division of Nephrology, Department of Medicine, McGill University Health Centre and Research Institute, Montreal, Canada.
  • Lopes R; Department of Medicine, McGill University Health Centre, 1001 Decarie Blvd, Montreal, QC, H4A3J1, Canada.
  • Sharma A; Division of Endocrinology, McGill University Health Centre, Montreal, Canada.
Curr Heart Fail Rep ; 18(5): 253-263, 2021 10.
Article em En | MEDLINE | ID: mdl-34427881
PURPOSE OF REVIEW: With recent advances in the pharmacological management of type 2 diabetes mellitus (T2DM), there is a growing need to understand which patients optimally benefit from these novel therapies. Various clinical clustering methodologies have emerged that utilise data-agnostic strategies to categorise patients that have similar clinical characteristics and outcomes; broadly, this characterisation is termed phenotyping. In patients with T2DM, we aimed to describe patient characteristics from phenotype studies, their cardiovascular risk profiles and the impact of antihyperglycemic treatment. RECENT FINDINGS: Numerous phenotypic studies have been undertaken that have utilised a combination of clinical, biochemical, imaging and genetic variables. Each of these has produced phenotypes that display a spectrum of cardiovascular risk. Studies that aimed to describe pathophysiological phenotypes generally identified five phenotypes: autoimmune phenotype, insulin-related phenotypes (including permutations of insulin deficiency and resistance), obesity phenotype, ageing phenotype, and a sex-related phenotype. Studies examining risk profiles have demonstrated that across such phenotypes there is a spectrum of risk for diabetic complications. Few studies have examined treatment effects across these phenotypes, and thus provide little insights towards making phenotype-guided treatment decisions Clustering analyses in patients with T2DM have identified distinct phenotypes with unique risk profiles. Further studies are needed that harness the use of clinical, biochemical, imaging and genetic data to explore therapeutic heterogeneity and response to antihyperglycemic treatment across the spectrum of patient phenotypes.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Diabetes Mellitus Tipo 2 / Insuficiência Cardíaca Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Diabetes Mellitus Tipo 2 / Insuficiência Cardíaca Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article