Comment on “An algorithm for identification and classification of individuals with type 1 and type 2 diabetes mellitus in a large primary care database”, written by Sharma et al
Valéry Bocquet Competence Center for Methodology and Statistics, Luxembourg Institute of Health, LuxembourgDiabetes is a disease whose global prevalence has been rising year after year, and by 2014 more than 400 million individuals were diagnosed with diabetes.1 As a consequence, screenin...
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doaj-13f382c55bd841aa86ea3f23cf7a35ce2020-11-25T01:01:16ZengDove Medical PressClinical Epidemiology1179-13492017-01-01Volume 9636531009Comment on “An algorithm for identification and classification of individuals with type 1 and type 2 diabetes mellitus in a large primary care database”, written by Sharma et alBocquet VValéry Bocquet Competence Center for Methodology and Statistics, Luxembourg Institute of Health, LuxembourgDiabetes is a disease whose global prevalence has been rising year after year, and by 2014 more than 400 million individuals were diagnosed with diabetes.1 As a consequence, screening of patients with type 1 or type 2 diabetes has become important, both to estimate the prevalence of diabetes and to treat affected individuals. For that purpose, a two-step algorithm suggested by Sharma et al2 was recently published, whose aims were to identify type 1 or type 2 individuals from a primary care database. The first step of the algorithm was based on the diagnostic records, treatment given, and results obtained from clinical tests. The second part was based on the combination of diagnostic codes, prescribed medications, age at the time of diagnosis, and finally whether the case was prevalent or incident.View original paper by Sharma et alhttps://www.dovepress.com/comment-on-ldquoan-algorithm-for-identification-and-classification-of--peer-reviewed-article-CLEPType 2 Diabetes Mellitusalgorithm |
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DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Bocquet V |
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Bocquet V Comment on “An algorithm for identification and classification of individuals with type 1 and type 2 diabetes mellitus in a large primary care database”, written by Sharma et al Clinical Epidemiology Type 2 Diabetes Mellitus algorithm |
author_facet |
Bocquet V |
author_sort |
Bocquet V |
title |
Comment on “An algorithm for identification and classification of individuals with type 1 and type 2 diabetes mellitus in a large primary care database”, written by Sharma et al |
title_short |
Comment on “An algorithm for identification and classification of individuals with type 1 and type 2 diabetes mellitus in a large primary care database”, written by Sharma et al |
title_full |
Comment on “An algorithm for identification and classification of individuals with type 1 and type 2 diabetes mellitus in a large primary care database”, written by Sharma et al |
title_fullStr |
Comment on “An algorithm for identification and classification of individuals with type 1 and type 2 diabetes mellitus in a large primary care database”, written by Sharma et al |
title_full_unstemmed |
Comment on “An algorithm for identification and classification of individuals with type 1 and type 2 diabetes mellitus in a large primary care database”, written by Sharma et al |
title_sort |
comment on “an algorithm for identification and classification of individuals with type 1 and type 2 diabetes mellitus in a large primary care database”, written by sharma et al |
publisher |
Dove Medical Press |
series |
Clinical Epidemiology |
issn |
1179-1349 |
publishDate |
2017-01-01 |
description |
Valéry Bocquet Competence Center for Methodology and Statistics, Luxembourg Institute of Health, LuxembourgDiabetes is a disease whose global prevalence has been rising year after year, and by 2014 more than 400 million individuals were diagnosed with diabetes.1 As a consequence, screening of patients with type 1 or type 2 diabetes has become important, both to estimate the prevalence of diabetes and to treat affected individuals. For that purpose, a two-step algorithm suggested by Sharma et al2 was recently published, whose aims were to identify type 1 or type 2 individuals from a primary care database. The first step of the algorithm was based on the diagnostic records, treatment given, and results obtained from clinical tests. The second part was based on the combination of diagnostic codes, prescribed medications, age at the time of diagnosis, and finally whether the case was prevalent or incident.View original paper by Sharma et al |
topic |
Type 2 Diabetes Mellitus algorithm |
url |
https://www.dovepress.com/comment-on-ldquoan-algorithm-for-identification-and-classification-of--peer-reviewed-article-CLEP |
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AT bocquetv commentonldquoanalgorithmforidentificationandclassificationofindividualswithtype1andtype2diabetesmellitusinalargeprimarycaredatabaserdquowrittenbysharmaetal |
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