Abstract
Objective
To derive a clinical prediction rule to predict pneumonia in patients with acute febrile
respiratory illness to emergency departments.
Method
This was a prospective multicentre study. 537 adults were recruited. Those requiring
resuscitation or were hypoxaemic on presentation were excluded. Pneumonia was defined
as new onset infiltrates on chest X-ray (CXR), or re-attendance within 7 days and
diagnosed clinically as having pneumonia. A predictive model, the Acute Febrile Respiratory
Illness (AFRI) rule was derived by logistic regression analysis based on clinical
parameters. The AFRI rule was internally validated with bootstrap resampling and was
compared with the Diehr and Heckerling rule.
Results
In the 363 patients who underwent CXR, 100 had CXR confirmed pneumonia. There were
7 weighted factors within the ARFI rule, which on summation, gave the AFRI score:
age ≥ 65 (1 point), peak temperature within 24 h ≥ 40 °C (2 points), fever duration
≥3 days (2 points), sore throat (−2 points), abnormal breath sounds (1 point), history
of pneumonia (1 point) and SpO2 ≤ 96% (1 point). With the bootstrap resampling, the
AFRI rule was found to be more accurate than the Diehr and Heckerling rule (area under
ROC curve 0.816, 0.721 and 0.566 respectively, p < 0.001). At a cut-off of AFRI≥0, the rule was found to have 95% sensitivity, with
a negative predictive value of 97.2%. Using the AFRI score, we found CXR could be
avoided for patients having a score of <0.
Conclusion
AFRI score could assist emergency physicians in identifying pneumonia patients among
all adult patients presented to ED for acute febrile respiratory illness.
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Article Info
Publication History
Published online: October 20, 2018
Accepted:
October 18,
2018
Received in revised form:
October 17,
2018
Received:
July 3,
2018
Identification
Copyright
© 2018 Elsevier Inc. All rights reserved.
