Identifying patients with asthma-chronic obstructive pulmonary disease overlap syndrome using latent class analysis of electronic health record data: a study protocol.
Identifying patients with asthma-chronic obstructive pulmonary disease overlap syndrome using latent class analysis of electronic health record data: a study protocol.
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DOI：
10.1038/s41533-018-0088-4
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发表时间：
2018-06-20
影响因子：
3.1
通讯作者：
Davies GA
中科院分区：
文献类型：
--
作者：
Al Sallakh MA;Rodgers SE;Lyons RA;Sheikh A;Davies GA
哮喘和慢性阻塞性肺疾病（COPD）是两种常见的不同临床诊断，具有重叠的临床特征。这两种情况都越来越多地使用电子健康记录（EHR）进行研究。哮喘-COPD重叠综合征（ACOS）是一个新兴的概念，其中两种疾病的临床特征并存，但尚无一致的定义。尽管如此，我们预计ACOS患者的EHR数据与“仅哮喘”或“仅COPD”患者的EHR数据存在系统性差异。我们的目标是开发一个潜在的类模型，以了解EHR数据中哮喘和COPD之间的重叠。从安全匿名信息链接（SAIL）数据库中，我们将使用2014年1月1日在威尔士40岁或以上的人在2014年或之前记录的常规收集的初级保健数据。基于这个潜在类别模型，我们将训练一个分类算法，并将其性能与哮喘和COPD的常用客观和自我报告病例定义进行比较。由此产生的分类算法旨在用于在初级保健数据集中识别患有ACOS、“仅哮喘”和“仅COPD”的人。
Asthma and chronic obstructive pulmonary disease (COPD) are two common different clinical diagnoses with overlapping clinical features. Both conditions have been increasingly studied using electronic health records (EHR). Asthma-COPD overlap syndrome (ACOS) is an emerging concept where clinical features from both conditions co-exist, and for which, however, there is no consensus definition. Nonetheless, we expect EHR data of people with ACOS to be systematically different from those with “asthma only” or “COPD only”. We aim to develop a latent class model to understand the overlap between asthma and COPD in EHR data. From the Secure Anonymised Information Linkage (SAIL) databank, we will use routinely collected primary care data recorded in or before 2014 in Wales for people who aged 40 years or more on 1st Jan 2014. Based on this latent class model, we will train a classification algorithm and compare its performance with commonly used objective and self-reported case definitions for asthma and COPD. The resulting classification algorithm is intended to be used to identify people with ACOS, ‘asthma only’, and ‘COPD only’ in primary care datasets.
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DOI：
10.3399/bjgp16x686953
发表时间：
2016-09-01
期刊：
The British journal of general practice : the journal of the Royal College of General Practitioners
影响因子：
--
作者：
Akker, Ingrid Looijmans-van den;van der Zeijden, Hans;Verheij, Theo Jm
通讯作者：
Verheij, Theo Jm
影响因子：
5.8
作者：
Makikyro, Elina M. S.;Jaakkola, Maritta S.;Jaakkola, Jouni J. K.
通讯作者：
Jaakkola, Jouni J. K.
影响因子：
14.2
作者：
Ghebre, Michael A.;Bafadhel, Mona;Desai, Dhananjay;Cohen, Suzanne E.;Newbold, Paul;Rapley, Laura;Woods, Jo;Rugman, Paul;Pavord, Ian D.;Newby, Chris;Burton, Paul R.;May, Richard D.;Brightling, Chris E.
通讯作者：
Brightling, Chris E.
影响因子：
3.5
作者：
Lyons RA;Jones KH;John G;Brooks CJ;Verplancke JP;Ford DV;Brown G;Leake K
通讯作者：
Leake K
影响因子：
4.4
作者：
Jorm, Louisa
通讯作者：
Jorm, Louisa