Risk prediction

Kallis, C., Calvo, R. A., Schuller, B., & Quint, J. K. (2023). Development of an Asthma Exacerbation Risk Prediction Model for Conversational Use by Adults in England. Pragmat Obs Res, 14, 111-125. http://doi.org/10.2147/por.s424098

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Livingstone, S., Morales, D. R., Fleuriot, J., Donnan, P. T., & Guthrie, B. (2023). External validation of the QLifetime cardiovascular risk prediction tool: population cohort study. Bmc Cardiovasc Disord, 23, 194. http://doi.org/10.1186/s12872-023-03209-8

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Bottle, A., Newson, R., Faitna, P., Hayhoe, B., & Cowie, M. R. (2022). Risk prediction of mortality for patients with heart failure in England: observational study in primary care. Esc Heart Fail. http://doi.org/10.1002/ehf2.14250

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Chung, S. C., O'Brien, B., Lip, G. Y. H., Fields, K. G., Muehlschlegel, J. D., Thakur, A., et al. (2022). Prognostic model for atrial fibrillation after cardiac surgery: a UK cohort study. Clin Res Cardiol. http://doi.org/10.1007/s00392-022-02068-1

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Xu, Z., Arnold, M., Sun, L., Stevens, D., Chung, R., Ip, S., et al. (2022). Incremental value of risk factor variability for cardiovascular risk prediction in individuals with type 2 diabetes: results from UK primary care electronic health records. Int J Epidemiol. http://doi.org/10.1093/ije/dyac140

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Livingstone, S. J., Guthrie, B., Donnan, P. T., Thompson, A., & Morales, D. R. (2022). Predictive performance of a competing risk cardiovascular prediction tool CRISK compared to QRISK3 in older people and those with comorbidity: population cohort study. Bmc Med, 20, 152. http://doi.org/10.1186/s12916-022-02349-6

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Hageman, S. H. J., McKay, A. J., Ueda, P., Gunn, L. H., Jernberg, T., Hagström, E., et al. (2022). Estimation of recurrent atherosclerotic cardiovascular event risk in patients with established cardiovascular disease: the updated SMART2 algorithm. Eur Heart J. http://doi.org/10.1093/eurheartj/ehac056

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