Validation of a clinical rule to predict complications of acute cough in preschool children: a prospective study in primary care.
BACKGROUND
Few clinical rules have been derived let alone validated in primary care. A rule was derived to predict complications of acute cough in preschool children presenting to primary care. The clinical rule used the presence/absence of fever and/or chest signs to distinguish children at low, medium, and high risk of complications.


OBJECTIVE
To validate a clinical rule for predicting complications of acute cough in preschool children in primary care.


METHODS
Prospective cohort study.


METHODS
Thirteen general practices in Bristol and Tayside, UK.


METHODS
Preschool children with cough up to 28 days and without asthma were recruited. The same sociodemographic, clinical history, examination, and complications data as for the derivation study were collected. First, univariable logistic regression was used to explore the associations with complications, and then predictors with stronger relationships (P<0.2) were modelled using multivariable logistic regression. These predictors were compared with derivation predictors with respect to their strength of association with complications. The derivation predictors were used in the validation dataset to allow comparison of the post-test probabilities of complications between derivation and validation studies.


RESULTS
The presence of fever and chest signs in the validation study tended to be protective for complications, with univariable odds ratios (ORs) of 0.37 and 0.81 respectively, compared with ORs of 4.86 and 2.72 in the derivation study. However, 95% confidence limits were wide and evidence for two other possible reasons for these results were found: spectrum bias and confounding by indication.


CONCLUSIONS
No evidence was found to validate the clinical rule for predicting complications of acute cough, possibly as a result of spectrum bias, confounding by indication, and/or chance. As paediatric infectious illness is costly and associated with high rates of antibiotic use, further research is needed to derive and validate prediction rules.
Hay
Alastair D
AD
Academic Unit of Primary Health Care, University of Bristol, Bristol. alastair.hay@bristol.ac.uk
Gorst
Catharine
C
Montgomery
Alan
A
Peters
Tim J
TJ
Fahey
Tom
T
D000208:Acute Disease; D002675:Child, Preschool; D015331:Cohort Studies; D003371:Cough / Q000150:complications* / Q000175:diagnosis; D003625:Data Collection; D018450:Disease Progression; D004739:England; D005194:Family Practice; D005260:Female; D005334:Fever / Q000175:diagnosis / Q000209:etiology*; D006801:Humans; D007223:Infant; D008297:Male; D015999:Multivariate Analysis; D011237:Predictive Value of Tests; D011379:Prognosis; D011446:Prospective Studies; D012307:Risk Factors