Literature DB >> 23331563

Asthma phenotypes identified by latent class analysis in the ISAAC phase II Spain study.

G Weinmayr1, F Keller, A Kleiner, J B du Prel, L Garcia-Marcos, J Batllés-Garrido, G Garcia-Hernandez, M M Suarez-Varela, D P Strachan, G Nagel.   

Abstract

BACKGROUND: Classification of respiratory symptoms may help to identify different underlying asthma phenotypes reflecting differences in aetiology and prognosis of wheezing disease among children.
OBJECTIVE: To determine childhood asthma phenotypes based on respiratory symptoms from a widely used questionnaire to further classify phenotypes in international settings.
METHODS: Between 2000 and 2002 cross-sectional studies were performed in four centres in Spain. Parental questionnaires were used to collect information on allergic diseases in more than 4000 children aged 8-12 years. In addition, objective markers for allergic sensitization and bronchial hyperresponsiveness (BHR) were measured. Latent class analyses (LCA) were applied to identify subgroups of children according to respiratory symptoms, and then the association of these groups with relevant clinical features such as concomitant allergic disease symptoms, atopy and BHR was studied.
RESULTS: We found seven classes, one corresponding to healthy children, three classes related to wheeze and three other classes mainly related to congestion and coughed-up phlegm. These tentative phenotypes differed in severity of symptoms and also in clinical correlates such as BHR and allergic sensitization. Atopy was more predominant in the 'wheeze phenotypes' whereas concomitant 'allergic' symptoms were most frequent in two of the 'wheeze phenotypes' and one of the 'cough phenotypes'.
CONCLUSIONS: LCA on reported symptoms in a cross-sectional survey allowed different subgroups with meaningful clinical correlates to be defined. It remains to be investigated to what extent these groups also have different aetiologies, prognoses and therapeutic needs.
© 2012 Blackwell Publishing Ltd.

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Year:  2013        PMID: 23331563     DOI: 10.1111/cea.12035

Source DB:  PubMed          Journal:  Clin Exp Allergy        ISSN: 0954-7894            Impact factor:   5.018


  16 in total

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Authors:  Ritesh Agarwal; Sahajal Dhooria; Ashutosh Nath Aggarwal; Venkata N Maturu; Inderpaul S Sehgal; Valliappan Muthu; Kuruswamy T Prasad; Lakshmikant B Yenge; Navneet Singh; Digambar Behera; Surinder K Jindal; Dheeraj Gupta; Thanagakunam Balamugesh; Ashish Bhalla; Dhruva Chaudhry; Sunil K Chhabra; Ramesh Chokhani; Vishal Chopra; Devendra S Dadhwal; George D'Souza; Mandeep Garg; Shailendra N Gaur; Bharat Gopal; Aloke G Ghoshal; Randeep Guleria; Krishna B Gupta; Indranil Haldar; Sanjay Jain; Nirmal K Jain; Vikram K Jain; Ashok K Janmeja; Surya Kant; Surender Kashyap; Gopi C Khilnani; Jai Kishan; Raj Kumar; Parvaiz A Koul; Ashok Mahashur; Amit K Mandal; Samir Malhotra; Sabir Mohammed; Prasanta R Mohapatra; Dharmesh Patel; Rajendra Prasad; Pallab Ray; Jai K Samaria; Potsangbam Sarat Singh; Honey Sawhney; Nusrat Shafiq; Navneet Sharma; Updesh Pal S Sidhu; Rupak Singla; Jagdish C Suri; Deepak Talwar; Subhash Varma
Journal:  Lung India       Date:  2015-04

2.  Atopic phenotypes identified with latent class analyses at age 2 years.

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7.  Overweight/obesity and respiratory and allergic disease in children: international study of asthma and allergies in childhood (ISAAC) phase two.

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8.  Subtypes of asthma based on asthma control and severity: a latent class analysis.

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Review 9.  Identification of Asthma Subtypes Using Clustering Methodologies.

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Review 10.  Artificial Intelligence and Machine Learning in Chronic Airway Diseases: Focus on Asthma and Chronic Obstructive Pulmonary Disease.

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