Development and first results of the BEAT-PCD international Primary Ciliary Dyskinesia gene variant database: CiliaVar

Author(s):  
Rahma Mani ◽  
Mafalda Gomes ◽  
Adrián Rodríguez González ◽  
Claire Hogg ◽  
Deborah Morris-Rosendahl ◽  
...  
2019 ◽  
Vol 55 (2) ◽  
pp. 383-393 ◽  
Author(s):  
Nagehan Emiralioğlu ◽  
Ekim Z. Taşkıran ◽  
Can Koşukcu ◽  
Elif Bilgiç ◽  
Pergin Atilla ◽  
...  

2016 ◽  
Vol 49 (1) ◽  
pp. 1601181 ◽  
Author(s):  
Myrofora Goutaki ◽  
Elisabeth Maurer ◽  
Florian S. Halbeisen ◽  
Israel Amirav ◽  
Angelo Barbato ◽  
...  

Data on primary ciliary dyskinesia (PCD) epidemiology is scarce and published studies are characterised by low numbers. In the framework of the European Union project BESTCILIA we aimed to combine all available datasets in a retrospective international PCD cohort (iPCD Cohort).We identified eligible datasets by performing a systematic review of published studies containing clinical information on PCD, and by contacting members of past and current European Respiratory Society Task Forces on PCD. We compared the contents of the datasets, clarified definitions and pooled them in a standardised format.As of April 2016 the iPCD Cohort includes data on 3013 patients from 18 countries. It includes data on diagnostic evaluations, symptoms, lung function, growth and treatments. Longitudinal data are currently available for 542 patients. The extent of clinical details per patient varies between centres. More than 50% of patients have a definite PCD diagnosis based on recent guidelines. Children aged 10–19 years are the largest age group, followed by younger children (≤9 years) and young adults (20–29 years).This is the largest observational PCD dataset available to date. It will allow us to answer pertinent questions on clinical phenotype, disease severity, prognosis and effect of treatments, and to investigate genotype–phenotype correlations.


2018 ◽  
Author(s):  
Goutaki Myrofora ◽  
Eich Marc ◽  
Florian S. Halbeisen ◽  
Barben Juerg ◽  
Casaulta Carmen ◽  
...  

AbstractPrimary Ciliary Dyskinesia (PCD) is a rare hereditary, multi-organ disease caused by defects in ciliary structure and function. It results in a wide range of clinical manifestations, most commonly in the upper and lower airways. Central data collection in national and international registries is essential to studying the epidemiology of rare diseases and filling in gaps in knowledge of diseases such as PCD. For this reason, the Swiss Primary Ciliary Dyskinesia Registry (CH-PCD) was founded in 2013 as a collaborative project between epidemiologists and adult and paediatric pulmonologists.The registry records patients of any age, suffering from PCD, who are treated and resident in Switzerland. It collects information from patients identified through physicians, diagnostic facilities, and patient organisations. The registry dataset contains data on diagnostic evaluations, lung function, microbiology and imaging, symptoms, treatments, and hospitalizations.By May 2018, CH-PCD has contacted 566 physicians of different specialties and identified 134 patients with PCD. At present this number represents an overall 1 in 63,000 prevalence of people diagnosed with PCD in Switzerland. Prevalence differs by age and region; it is highest in children and adults younger than 30 years, and in Espace Mittelland. The median age of patients in the registry is 25 years (range 5-73), and 49 patients have a definite PCD diagnosis based on recent international guidelines. Data from CH-PCD are contributed to international collaborative studies and the registry facilitates patient identification for nested studies.CH-PCD has proven to be a valuable research tool that already has highlighted weaknesses in PCD clinical practice in Switzerland. Development of centralised diagnostic and management centres and adherence to international guidelines are needed to improve diagnosis and management—particularly for adult PCD patients.


2020 ◽  
Vol 26 (8) ◽  
Author(s):  
Fatemeh Sakhaee ◽  
Farzam Vaziri ◽  
Golnaz Bahramali ◽  
Seyed Davar Siadat ◽  
Abolfazl Fateh

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