Αρχειοθήκη ιστολογίου

Αλέξανδρος Γ. Σφακιανάκης
ΩτοΡινοΛαρυγγολόγος
Αναπαύσεως 5
Άγιος Νικόλαος Κρήτη 72100
2841026182
6032607174

Σάββατο 17 Νοεμβρίου 2018

Individual Risk Assessment Tool for School Age Asthma Prediction in UK Birth Cohort

Abstract

Background

Current published asthma predictive tools have moderate positive likelihood ratios (LR+) but high negative likelihood ratios (‐LR) based on their recommended cut‐offs, which limit their clinical usefulness.

Objective

To develop a simple clinically applicable asthma prediction tool within a population‐based birth cohort.

Method

Children from the Manchester Asthma and Allergy Study (MAAS) attended follow‐up at ages 3, 8 and 11 years. Data on pre‐school wheeze was extracted from primary‐care records. Parents completed validated respiratory questionnaires. Children were skin prick tested (SPT). Asthma at 8/11 years (school ‐age) was defined as parentally‐reported (1) physician‐diagnosed asthma and wheeze in the previous 12 months or (2) ≥3 wheeze attacks in the previous 12 months. An asthma prediction tool (MAAS APT) was developed using logistic regression of characteristics at age 3 years to predict school‐age asthma.

Results

Of 336 children with physician‐confirmed wheeze by age 3 years, 117(35%) had school‐age asthma. Logistic regression selected 5 significant risk factors which formed the basis of the MAAS APT: wheeze after exercise; wheeze causing breathlessness; cough on exertion; current eczema and SPT sensitisation(maximum score 5). A total of 281(84%) children had complete data at age 3 years and were used to test the MAAS APT. Children scoring ≥3 were at high risk of having asthma at school‐age(PPV>75%; +LR 6.3,‐LR 0.6), whereas children who had a score of 0 had very low risk(PPV 9.3%; LR 0.2).

Conclusion

MAAS APT is a simple asthma prediction tool which could easily be applied in clinical and research settings.

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