Phenotypes of cough in children: A latent class analysis

Author:

Mallet Maria Christina12ORCID,Pedersen Eva S. L.1,Makhoul Ronny12,Blanchon Sylvain3,Hoyler Karin4,Jochmann Anja5,Latzin Philipp6,Moeller Alexander7,Regamey Nicolas8,Goutaki Myrofora16,Spycher Ben D.1,Kuehni Claudia E.16,

Affiliation:

1. Institute of Social and Preventive Medicine University of Bern Bern Switzerland

2. Graduate School for Health Sciences University of Bern Bern Switzerland

3. Pediatric Pulmonology and Cystic Fibrosis Unit, Service of Pediatrics, Department Woman‐Mother‐Child, Lausanne University Hospital University of Lausanne Lausanne Switzerland

4. Kinderpneumologie Horgen Private Practice for Pediatric Pneumology Horgen Switzerland

5. Department of Paediatric Pulmonology University Children's Hospital Basel Basel Switzerland

6. Division of Paediatric Respiratory Medicine and Allergology, Department of Paediatrics, Inselspital, Bern University Hospital University of Bern Bern Switzerland

7. Department of Respiratory Medicine, University Children's Hospital Zurich and Children's Research Centre University of Zurich Zurich Switzerland

8. Division of Paediatric Pulmonology Children's Hospital, Cantonal Hospital Lucerne Lucerne Switzerland

Abstract

AbstractIntroductionDistinguishing phenotypes among children with cough helps understand underlying causes. Using a statistical data‐driven approach, we aimed to identify and validate cough phenotypes based on measurable traits, physician diagnoses, and prognosis.MethodsWe used data from the Swiss Paediatric Airway Cohort and included 531 children aged 5–16 years seen in outpatient clinics since 2017. We included children with any parent‐reported cough (i.e. cough without a cold, cough at night, cough more than other children, or cough longer than 4 weeks) without current wheeze. We applied latent class analysis to identify phenotypes using nine symptoms and characteristics and selected the best model using the Akaike information criterion. We assigned children to the most likely phenotype and compared the resulting groups for parental atopy history, comorbidities, spirometry, fractional exhaled nitric oxide (FeNO), skin prick tests and specific IgE, physician diagnoses, and 1‐year prognosis.ResultsWe identified four cough phenotypes: non‐specific cough (26%); non‐allergic infectious and night cough with snoring and otitis (4%); chronic allergic dry night cough with snoring (9%); and allergic non‐infectious cough with rhino‐conjunctivitis (61%). Children with the allergic phenotype often had family or personal history of atopy and asthma diagnosis. FeNO was highest for the allergic phenotype [median 17.9 parts per billion (ppb)] and lowest for the non‐allergic infectious phenotype [median 7.0 parts per billion (ppb)]. Positive allergy test results differed across phenotypes (p < .001) and were most common among the allergic (70%) and least common among the non‐specific cough (31%) phenotypes. Subsequent wheeze was more common among the allergic than the non‐specific phenotype.ConclusionWe identified four clinically relevant cough phenotypes with different prognoses. Although we excluded children with current wheeze, most children with cough belonged to allergy‐related phenotypes.

Funder

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung

Publisher

Wiley

Subject

Immunology,Immunology and Allergy

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