The Swiss Paediatric Airway Cohort (SPAC).
Eva S L PedersenCarmen C M de JongCristina Ardura-GarciaJuerg BarbenCarmen CasaultaUrs FreyAnja JochmannPhilipp LatzinAlexander MoellerNicolas RegameyFlorian SingerBen SpycherOliver SutterMyrofora GoutakiClaudia Elisabeth KuehniPublished in: ERJ open research (2018)
Chronic respiratory symptoms, such as cough, wheeze and dyspnoea, are common in children; however, most research has, with the exception of a few large-scale clinical cohort studies, been performed in the general population or in small, highly-selected samples. The Swiss Paediatric Airway Cohort (SPAC) is a national, prospective clinical cohort of children and adolescents who visit physicians for recurrent conditions, such as wheeze and cough, and exercise-related respiratory problems. The SPAC is an observational study and baseline assessment includes standardised questionnaires for families and data extracted from hospital records, including results of clinically indicated investigations, diagnoses and treatments. Outcomes are assessed through annual questionnaires, monthly symptom reporting via mobile phone and follow-up visits. The SPAC will address important questions about clinical phenotypes, diagnosis, treatment, and the short- and long-term prognosis of common respiratory problems in children. The cohort currently consists of 347 patients from four major hospitals (Bern, Zurich, Basel and Lucerne), with 70-80 additional patients joining each month. More centres will join and the target sample size is a minimum of 3000 patients. The SPAC will provide real-life data on children visiting the Swiss healthcare system for common respiratory problems and will provide a research platform for health services research and nested clinical and translational studies.
Keyphrases
- end stage renal disease
- newly diagnosed
- ejection fraction
- chronic kidney disease
- mental health
- prognostic factors
- young adults
- emergency department
- primary care
- peritoneal dialysis
- oxidative stress
- metabolic syndrome
- type diabetes
- electronic health record
- dna damage
- physical activity
- patient reported outcomes
- body composition
- big data
- weight loss
- dna repair
- combination therapy
- data analysis
- psychometric properties
- drug induced