Abstract
Predictions, risk assessment and risk profiling are among the various decision support techniques that medical professionals increasingly rely on to provide early diagnose in patients with elevated risks and to slow down the rapid increase in prevalence of chronic diseases. The introduction of risk assessment tools and applications for chronic diseases in large scale longitudinal clinical studies, presents many challenges due to the nature of the data (studies last around a decade) and the complexity of the models. In this paper, we give an overview of research work on risk assessment tools and applications for diabetes complications. We also introduce the REACTION project and its vision in the field of risk assessment for diabetes complications.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
The Diabetes Control and Complications Trial Research Group: The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. N. Engl. J. Med. 329(14), 977–986 (1993)
Hippisley-Cox, J., Coupland, C., Vinogradova, Y., et al.: Derivation and validation of QRISK, a new cardiovascular disease risk score for the United Kingdom: prospective open cohort study. BMJ, June 27 (2007)
UKPDS Group: UK Prospective Diabetes Study VIII: Study design, progress and performance. Diabetologia 34, 877–890 (1991)
Epidemiology of Diabetes Interventions and Complications (EDIC): design, implementation, and preliminary results of a long-term follow-up of the Diabetes Control and Complications Trial cohort. Diabetes Care 22, 99–111 (1999)
Eddy, D.M., Schlessinger, L.: Validation of the Archimedes Diabetes Model. Diabetes Care 26, 3102–3110 (2003)
Schlessinger, L., Eddy, D.M.: Archimedes: a new model for simulating health care systems - the mathematical formulation. Journal of Biomedical Informatics 35, 37–50 (2002)
Hippisley-Cox, J., Coupland, C., Vinogradova, Y., Robson, J., Minhas, R., Sheikh, A., Brindle, P.: Predicting cardiovascular risk in England and Wales: prospective derivation and validation of QRISK2. BMJ 336, 1475 (2008) doi: 10.1136/bmj.39609.449676.25
D’Agostino, R.B., Wolf, P.A., Belanger, A.J., Kannel, W.B.: Stroke Risk Profile: Adjustment for Antihypertensive Medication, Stroke (1994)
Pocock, S., McCormack, V., Gueyffier, F., Boutitie, F., Fagard, R., Boissel, J.-P.: A Score for Predicting Risk of Cardiovascular Death in Adults with Elevated Blood Pressure. British Medical Journal 323(7304), 75–81 (2001)
The Mount Hood 4 Modeling Group: Computer modeling of diabetes and its complications. The Mount Hood modeling group, Diabetes Care 30, 638–1646 (2007)
http://clearinghouse.adma.org.au/browse-resources/assessment-tool/2.html
Green, C., Hoppa, R.D., Young, T.K., Blanchard, J.F.: Geographic analysis of diabetes prevalence in an urban area. Soc. Sci. Med. 57(3), 551–560 (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Koumakis, L., Chiarugi, F., Lagani, V., Kouroubali, A., Tsamardinos, I. (2012). Risk Assessment Models for Diabetes Complications: A Survey of Available Online Tools. In: Nikita, K.S., Lin, J.C., Fotiadis, D.I., Arredondo Waldmeyer, MT. (eds) Wireless Mobile Communication and Healthcare. MobiHealth 2011. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 83. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29734-2_7
Download citation
DOI: https://doi.org/10.1007/978-3-642-29734-2_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-29733-5
Online ISBN: 978-3-642-29734-2
eBook Packages: Computer ScienceComputer Science (R0)