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Personalized therapy algorithms for type 2 diabetes: a phenotype-based approach

Type 2 diabetes is a progressive disease with a complex and multifactorial pathophysiology. Patients with type 2 diabetes show a variety of clinical features, including different “phenotypes” of hyperglycemia (eg, fasting/preprandial or postprandial). Thus, the best treatment choice is sometimes dif...

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Autores principales: Ceriello, Antonio, Gallo, Marco, Candido, Riccardo, De Micheli, Alberto, Esposito, Katherine, Gentile, Sandro, Medea, Gerardo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove Medical Press 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4070713/
https://www.ncbi.nlm.nih.gov/pubmed/24971031
http://dx.doi.org/10.2147/PGPM.S50288
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author Ceriello, Antonio
Gallo, Marco
Candido, Riccardo
De Micheli, Alberto
Esposito, Katherine
Gentile, Sandro
Medea, Gerardo
author_facet Ceriello, Antonio
Gallo, Marco
Candido, Riccardo
De Micheli, Alberto
Esposito, Katherine
Gentile, Sandro
Medea, Gerardo
author_sort Ceriello, Antonio
collection PubMed
description Type 2 diabetes is a progressive disease with a complex and multifactorial pathophysiology. Patients with type 2 diabetes show a variety of clinical features, including different “phenotypes” of hyperglycemia (eg, fasting/preprandial or postprandial). Thus, the best treatment choice is sometimes difficult to make, and treatment initiation or optimization is postponed. This situation may explain why, despite the existing complex therapeutic armamentarium and guidelines for the treatment of type 2 diabetes, a significant proportion of patients do not have good metabolic control and at risk of developing the late complications of diabetes. The Italian Association of Medical Diabetologists has developed an innovative personalized algorithm for the treatment of type 2 diabetes, which is available online. According to the main features shown by the patient, six algorithms are proposed, according to glycated hemoglobin (HbA(1c), ≥9% or ≤9%), body mass index (≤30 kg/m(2) or ≥30 kg/m(2)), occupational risk potentially related to hypoglycemia, chronic renal failure, and frail elderly status. Through self-monitoring of blood glucose, patients are phenotyped according to the occurrence of fasting/preprandial or postprandial hyperglycemia. In each of these six algorithms, the gradual choice of treatment is related to the identified phenotype. With one exception, these algorithms contain a stepwise approach for patients with type 2 diabetes who are metformin-intolerant. The glycemic targets (HbA(1c), fasting/preprandial and postprandial glycemia) are also personalized. This accessible and easy to use algorithm may help physicians to choose a personalized treatment plan for each patient and to optimize it in a timely manner, thereby lessening clinical inertia.
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spelling pubmed-40707132014-06-26 Personalized therapy algorithms for type 2 diabetes: a phenotype-based approach Ceriello, Antonio Gallo, Marco Candido, Riccardo De Micheli, Alberto Esposito, Katherine Gentile, Sandro Medea, Gerardo Pharmgenomics Pers Med Review Type 2 diabetes is a progressive disease with a complex and multifactorial pathophysiology. Patients with type 2 diabetes show a variety of clinical features, including different “phenotypes” of hyperglycemia (eg, fasting/preprandial or postprandial). Thus, the best treatment choice is sometimes difficult to make, and treatment initiation or optimization is postponed. This situation may explain why, despite the existing complex therapeutic armamentarium and guidelines for the treatment of type 2 diabetes, a significant proportion of patients do not have good metabolic control and at risk of developing the late complications of diabetes. The Italian Association of Medical Diabetologists has developed an innovative personalized algorithm for the treatment of type 2 diabetes, which is available online. According to the main features shown by the patient, six algorithms are proposed, according to glycated hemoglobin (HbA(1c), ≥9% or ≤9%), body mass index (≤30 kg/m(2) or ≥30 kg/m(2)), occupational risk potentially related to hypoglycemia, chronic renal failure, and frail elderly status. Through self-monitoring of blood glucose, patients are phenotyped according to the occurrence of fasting/preprandial or postprandial hyperglycemia. In each of these six algorithms, the gradual choice of treatment is related to the identified phenotype. With one exception, these algorithms contain a stepwise approach for patients with type 2 diabetes who are metformin-intolerant. The glycemic targets (HbA(1c), fasting/preprandial and postprandial glycemia) are also personalized. This accessible and easy to use algorithm may help physicians to choose a personalized treatment plan for each patient and to optimize it in a timely manner, thereby lessening clinical inertia. Dove Medical Press 2014-06-19 /pmc/articles/PMC4070713/ /pubmed/24971031 http://dx.doi.org/10.2147/PGPM.S50288 Text en © 2014 Ceriello et al. This work is published by Dove Medical Press Limited, and licensed under Creative Commons Attribution – Non Commercial (unported, v3.0) License The full terms of the License are available at http://creativecommons.org/licenses/by-nc/3.0/. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.
spellingShingle Review
Ceriello, Antonio
Gallo, Marco
Candido, Riccardo
De Micheli, Alberto
Esposito, Katherine
Gentile, Sandro
Medea, Gerardo
Personalized therapy algorithms for type 2 diabetes: a phenotype-based approach
title Personalized therapy algorithms for type 2 diabetes: a phenotype-based approach
title_full Personalized therapy algorithms for type 2 diabetes: a phenotype-based approach
title_fullStr Personalized therapy algorithms for type 2 diabetes: a phenotype-based approach
title_full_unstemmed Personalized therapy algorithms for type 2 diabetes: a phenotype-based approach
title_short Personalized therapy algorithms for type 2 diabetes: a phenotype-based approach
title_sort personalized therapy algorithms for type 2 diabetes: a phenotype-based approach
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4070713/
https://www.ncbi.nlm.nih.gov/pubmed/24971031
http://dx.doi.org/10.2147/PGPM.S50288
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