Phenotypes of cough in children: A latent class analysis

Distinguishing 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. We 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. We 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