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Derivation and validation of an asthma diagnosis prediction model for children and young people in primary care

Dr. Luke Daines (Edinburgh University) has recently published in Wellcome Open Research on an asthma diagnosis prediction model for children and young people in primary care.  The logistic regression based prediction model was derived using the Avon Longitudinal Study of Parents and Children (ALSPAC) data linked to electronic health records, and validated in the Optimum Patient Care Research Database (OPCRD).   Predictors included in the final model were wheeze, cough, breathlessness, hay-fever, eczema, food allergy, social class, maternal asthma, childhood exposure to cigarette smoke, prescription of a short acting beta agonist and the past recording of lung function/reversibility testing. In the external validation dataset the C-statistic was 0.85, 95% CI 0.83–0.88.  Following further evaluation of clinical effectiveness, the prediction model could be implemented as a decision support software.

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