Prognosis

Abhishek, A., Grainge, M., Card, T., Williams, H. C., Taal, M. W., Aithal, G. P., et al. (2024). Risk-stratified monitoring for sulfasalazine toxicity: prognostic model development and validation. Rmd Open, 10. http://doi.org/10.1136/rmdopen-2023-003980
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Bellanca, L., Linden, S., & Farmer, R. (2023). Incidence and prevalence of heart failure in England: a descriptive analysis of linked primary and secondary care data - the PULSE study. Bmc Cardiovasc Disord, 23, 374. http://doi.org/10.1186/s12872-023-03337-1
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Nakafero, G., Grainge, M. J., Williams, H. C., Card, T., Taal, M. W., Aithal, G. P., et al. (2023). Risk stratified monitoring for methotrexate toxicity in immune mediated inflammatory diseases: prognostic model development and validation using primary care data from the UK. Bmj, 381, e074678. http://doi.org/10.1136/bmj-2022-074678
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Chudasama, Y. V., Khunti, K., Coles, B., Gillies, C. L., Islam, N., Rowlands, A. V., et al. (2023). Life expectancy following a cardiovascular event in individuals with and without type 2 diabetes: A UK multi-ethnic population-based observational study. Nutr Metab Cardiovasc Dis. http://doi.org/10.1016/j.numecd.2023.04.003
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Banerjee, A., Dashtban, A., Chen, S., Pasea, L., Thygesen, J. H., Fatemifar, G., et al. (2023). Identifying subtypes of heart failure from three electronic health record sources with machine learning: an external, prognostic, and genetic validation study. Lancet Digit Health, 5, e370-e379. http://doi.org/10.1016/s2589-7500(23)00065-1
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Dashtban, A., Mizani, M. A., Pasea, L., Denaxas, S., Corbett, R., Mamza, J. B., et al. (2023). Identifying subtypes of chronic kidney disease with machine learning: development, internal validation and prognostic validation using linked electronic health records in 350,067 individuals. Ebiomedicine, 89, 104489. http://doi.org/10.1016/j.ebiom.2023.104489
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Wambua, S., Crowe, F., Thangaratinam, S., O'Reilly, D., McCowan, C., Brophy, S., et al. (2022). Protocol for development and validation of postpartum cardiovascular disease (CVD) risk prediction model incorporating reproductive and pregnancy-related candidate predictors. Diagn Progn Res, 6, 23. http://doi.org/10.1186/s41512-022-00137-7
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Archer, L., Koshiaris, C., Lay-Flurrie, S., Snell, K. I. E., Riley, R. D., Stevens, R., et al. (2022). Development and external validation of a risk prediction model for falls in patients with an indication for antihypertensive treatment: retrospective cohort study. Bmj, 379, e070918. http://doi.org/10.1136/bmj-2022-070918
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Rapsomaniki, E., Shah, A., Perel, P., Denaxas, S., George, J., Nicholas, O., et al. (2014). Prognostic models for stable coronary artery disease based on electronic health record cohort of 102 023 patients. Eur Heart J, 35, 844-52. http://doi.org/10.1093/eurheartj/eht533
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