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Number-Based Approach to Insulin Taxonomy

This article describes a number-based system for the classification of insulin regimes. It utilizes a patient-centered variable (number of injections per day) and pharmacokinetic/dynamic characteristics to craft a taxonomic system that is able to incorporate all available insulin preparations and co...

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Detalles Bibliográficos
Autores principales: Kalra, Sanjay, Gupta, Yashdeep
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Healthcare 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4674470/
https://www.ncbi.nlm.nih.gov/pubmed/26350081
http://dx.doi.org/10.1007/s13300-015-0129-8
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author Kalra, Sanjay
Gupta, Yashdeep
author_facet Kalra, Sanjay
Gupta, Yashdeep
author_sort Kalra, Sanjay
collection PubMed
description This article describes a number-based system for the classification of insulin regimes. It utilizes a patient-centered variable (number of injections per day) and pharmacokinetic/dynamic characteristics to craft a taxonomic system that is able to incorporate all available insulin preparations and coformulations. This framework of systematics is robust enough to include various molecules that have been recently developed. It serves to enhance understanding of the subject, and facilitates the practical or clinical usage of theoretical knowledge. We propose that number-based insulin taxonomic models should be used in clinical guidelines and recommendations rather than restricting ourselves to pharmaceutical-based classifications. PubMed articles including both review articles and clinical trials published since the year 1990 were searched, to gather evidence and information on the various types of insulins available, and how they can be used, based on the number or frequency of injections prescribed per day.
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spelling pubmed-46744702015-12-17 Number-Based Approach to Insulin Taxonomy Kalra, Sanjay Gupta, Yashdeep Diabetes Ther Review This article describes a number-based system for the classification of insulin regimes. It utilizes a patient-centered variable (number of injections per day) and pharmacokinetic/dynamic characteristics to craft a taxonomic system that is able to incorporate all available insulin preparations and coformulations. This framework of systematics is robust enough to include various molecules that have been recently developed. It serves to enhance understanding of the subject, and facilitates the practical or clinical usage of theoretical knowledge. We propose that number-based insulin taxonomic models should be used in clinical guidelines and recommendations rather than restricting ourselves to pharmaceutical-based classifications. PubMed articles including both review articles and clinical trials published since the year 1990 were searched, to gather evidence and information on the various types of insulins available, and how they can be used, based on the number or frequency of injections prescribed per day. Springer Healthcare 2015-09-09 2015-12 /pmc/articles/PMC4674470/ /pubmed/26350081 http://dx.doi.org/10.1007/s13300-015-0129-8 Text en © The Author(s) 2015 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ), which permits any noncommercial use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Review
Kalra, Sanjay
Gupta, Yashdeep
Number-Based Approach to Insulin Taxonomy
title Number-Based Approach to Insulin Taxonomy
title_full Number-Based Approach to Insulin Taxonomy
title_fullStr Number-Based Approach to Insulin Taxonomy
title_full_unstemmed Number-Based Approach to Insulin Taxonomy
title_short Number-Based Approach to Insulin Taxonomy
title_sort number-based approach to insulin taxonomy
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4674470/
https://www.ncbi.nlm.nih.gov/pubmed/26350081
http://dx.doi.org/10.1007/s13300-015-0129-8
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