Effectiveness of a chronic cough management algorithm at the transitional stage from acute to chronic cough in children: A multicenter, nested, single-blind, randomised controlled trial

Kerry-Ann O'Grady, Keith Grimwood, Paul Torzillo, Sheree Rablin, Yolanda G. Lovie-Toon, Michelle Kaus, Daniel Arnold, Jack Roberts, Helen Buntain, Don Adsett, Alex King, Scott Markich, Jennie Anderson, Anne Chang, Maree Toombs

Research output: Contribution to journalArticlepeer-review

22 Citations (Scopus)

Abstract

Background: Chronic (lasting at least 4 weeks) cough in children is an important cause of morbidity. An algorithmic approach to the management of coughs in children evaluated in observational studies and a randomised controlled trial (RCT) enrolled children referred with median cough duration of 16 weeks to specialist centres. We investigated whether applying an evidence-based cough management algorithm in non-specialist settings earlier, once cough persisted for more than 4 weeks, improved cough resolution compared with usual care.

Methods: We undertook a multicentre, single-blind RCT nested within a prospective cohort study of children (<15 years) in Australia presenting to three primary care or three hospital emergency departments with an acute respiratory illness with cough. Children were excluded if they had a known diagnosis of an underlying chronic medical condition (excluding asthma) or had an immunosuppressive illness or were taking immunomodulating drugs for more than 2 weeks in the preceding 30 days, or had severe symptoms requiring inpatient hospitalisation. Children were followed up for 8 weeks; those with a persistent cough at day 28 were randomly assigned to the cough management algorithm or to usual care. Randomisation was stratified by reason for presentation, study site, and cough duration (4 weeks to <6 weeks vs ≥6 weeks) using computer-generated permuted blocks (block size of four) with a 1:1 allocation. The primary outcome was the proportion of children with cough resolution at day 56 (defined as resolved if the child did not cough for at least 3 days and nights since day 28 or a more than 75% reduction in their average day and night cough score). Absolute risk differences (RD absolute) were calculated by modified intention-to-treat analysis (ITT). This trial is registered with the Australia New Zealand Clinical Trials Registry, ACTRN12615000132549.

Findings: Between July 7, 2015, and Oct 31, 2018, 1018 children were screened, 509 were enrolled in the cohort study, and of 115 children in the ITT analysis, 57 were randomly assigned to the intervention group and 58 to the control group. Children had a median age of 1·6 years (IQR 1·0–4·5); 45 (39%) of 115 were Indigenous, and 59 (51%) were boys. By day 56, 33 (58%) of 57 children in the intervention group achieved cough resolution compared with 23 (40%) 58 in the control group; cough resolution was unknown in 12 (21%) of 57 children receiving the intervention and in 13 (22%) of 58 receiving the control. The RD absolute assuming children with an unknown cough outcome were still coughing at day 56 was 18·3% (95% CI 0·3–36·2); the number needed-to-treat for benefit was five (95% CI 3–364); the adjusted odds ratio was 1·5 (95% CI 1·3–1·6), favouring the intervention group.

Interpretation: This study suggests an evidence-based cough management algorithm improves cough resolution in community-based children in the early phases of chronic cough. However, larger studies to confirm these findings in primary care are required.

Funding: National Health and Medical Research Council.
Original languageEnglish
Pages (from-to)889-898
Number of pages10
JournalThe Lancet Child and Adolescent Health
Volume3
Issue number12
Early online date18 Oct 2019
DOIs
Publication statusPublished - Dec 2019

Fingerprint

Dive into the research topics of 'Effectiveness of a chronic cough management algorithm at the transitional stage from acute to chronic cough in children: A multicenter, nested, single-blind, randomised controlled trial'. Together they form a unique fingerprint.

Cite this