Algorithms to define diabetes type using data from administrative databases: A systematic review of the evidence-Reference-Cited by-同舟云学术

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Algorithms to define diabetes type using data from administrative databases: A systematic review of the evidence

Published:2023-09 Issue: Volume:203 Page:110859
ISSN:0168-8227
Container-title:Diabetes Research and Clinical Practice
language:en
Short-container-title:Diabetes Research and Clinical Practice

Author:

Sajjadi Seyedeh Forough,Sacre Julian W.,Chen Lei,Wild Sarah H.,Shaw Jonathan E,Magliano Dianna J.

Publisher

Elsevier BV

Subject

Endocrinology,General Medicine,Endocrinology, Diabetes and Metabolism,Internal Medicine

Reference32 articles.

1. Frequency and phenotype of type 1 diabetes in the first six decades of life: a cross-sectional, genetically stratified survival analysis from UK Biobank;Thomas;Lancet Diabetes Endocrinol,2018

2. Development and validation of algorithms to classify type 1 and 2 diabetes according to age at diagnosis using electronic health records;Ke;BMC Med Res Methodol,2020

3. An algorithm for identification and classification of individuals with type 1 and type 2 diabetes mellitus in a large primary care database;Sharma;Clin Epidemiol,2016

4. Identifying optimal survey-based algorithms to distinguish diabetes type among adults with diabetes;Nooney;J Clin Trans Endocrinol,2020

5. Development and validation of algorithms to identify newly diagnosed type 1 and type 2 diabetes in pediatric population using electronic medical records and claims data;Teltsch;Pharmacoepidemiol Drug Saf,2019

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Receipt of Diabetes Specialty Care and Management Services by Older Adults With Diabetes in the U.S., 2015–2019: An Analysis of Medicare Fee-for-Service Claims;Diabetes Care;2024-05-22

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