Dynamic prediction of cardiovascular risk from linked primary care records in New South Wales, Australia: protocol for a retrospective prognostic modelling study.

Nicholas I-Hsien Kuo¹, Heidi Welberry¹, Sanja Lujic¹, Anna Campain², Daniel Wilson³, Katie Harris², Michael Kidd^4,5, Patricia Correll³, David Peiris², Louisa Jorm⁶

¹Centre for Big Data Research in Health, University of New South Wales, Sydney, Australia.

²The George Institute for Global Health, University of New South Wales, Sydney, Australia.

³NSW Ministry of Health, Sydney, Australia.

⁴International Centre for Future Health Systems, University of New South Wales, Sydney, Australia.

⁵Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.

⁶Centre for Big Data Research in Health, University of New South Wales, Sydney, Australia l.jorm@unsw.edu.au.

PubMed DOI

Abstract

INTRODUCTION: Cardiovascular disease (CVD) remains a leading cause of preventable morbidity and mortality. Most existing CVD prediction tools use a baseline survival modelling framework, in which each predictor is represented by a single value recorded at the start of follow-up. Although risk calculators can be re-run using updated values, these models do not explicitly use the longitudinal, irreg…

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