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UK data driving real-world evidence
Bibliography
Research using CPRD data has informed drug safety guidance and clinical practice and resulted in over 2,700 peer-reviewed publications. The CPRD bibliography is updated on a monthly basis (last updated 6 April 2021) and papers are listed below and in the PDF below.
If you have published papers using CPRD data which are not included in this list, please contact us at enquiries@cprd.com so that we can update the bibliography.
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(PDF, 5MB, 226 pages)This work uses data provided by patients and collected by the NHS as part of their care and support. CPRD encourages researchers to use this citation in all publications using CPRD data. Find out more about acknowledging the use of patient data at the Understanding Patient Data website.
“Improving identification of familial hypercholesterolaemia in primary care: derivation and validation of the familial hypercholesterolaemia case ascertainment tool (FAMCAT)”, Atherosclerosis, vol. 238, pp. 336-43, 2015.
, “The value of aspartate aminotransferase and alanine aminotransferase in cardiovascular disease risk assessment”, Open Heart, vol. 2, p. e000272, 2015.
, “Can machine-learning improve cardiovascular risk prediction using routine clinical data?”, PLoS One, vol. 12, p. e0174944, 2017.
, “Venous thromboembolism in adults screened for sickle cell trait: a population-based cohort study with nested case-control analysis”, BMJ Open, vol. 7, p. e012665, 2017.
, “Does bone mineral density improve the predictive accuracy of fracture risk assessment? A prospective cohort study in Northern Denmark”, BMJ Open, vol. 8, p. e018898, 2018.
, , “The comorbidity burden of type 2 diabetes mellitus: patterns, clusters and predictions from a large English primary care cohort”, BMC Med, vol. 17, p. 145, 2019.
, , “Development and validation of the DIabetes Severity SCOre (DISSCO) in 139 626 individuals with type 2 diabetes: a retrospective cohort study”, BMJ Open Diabetes Res Care, vol. 8, 2020.
, “Performance and clinical utility of supervised machine-learning approaches in detecting familial hypercholesterolaemia in primary care”, NPJ Digit Med, vol. 3, p. 142, 2020.
, “Sex, Age, and Socioeconomic Differences in Nonfatal Stroke Incidence and Subsequent Major Adverse Outcomes”, Stroke, vol. 52, pp. 396-405, 2021.
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