QResearch

QDiabetes​ Risk of complications in people with diabetes

Title

Diabetes treatments and risk of cardiovascular disease, all-cause mortality, amputation, blindness, severe kidney failure, hyperglycaemia and hypoglycaemia: cohort study in primary care

What is the aim of the study and why is it important?

This project includes two aspects: 1.   To quantify the risk of each complication associated with different diabetes treatments. There are many different treatments for patients with diabetes. Clinical trials have generally shown that these treatments will lower blood glucose but information on the effect oncomplications of diabetes is usually not available.  In this observational study, we will quantify the effects of different types of hypoglycaemic drugs, alone and in combination, in order to assess the risks and benefits associated with each. This is likely to help inform prescribing practices for patients.  2.   To develop and validate a risk prediction algorithm which calculates an individual’s risk of diabetes complications such as cardiovascular disease, all-cause mortality, amputation, blindness, severe kidney failure, hyperglycaemia and hypoglycaemia taking account of their individual risk factors such as age, sex, ethnicity, clinical values and diagnoses. The complications are identified according to clinical codes recorded on the primary care record or the linked mortality or hospital record. The research describing the derivation and validation of the algorithms has been published in the BMJ. The algorithm is used to quantify an individual’s risk in order to prioritise and inform decisions regarding interventions to lower risk. It will be updated annually to ensure the algorithms remain calibrated to the current population since the incidence of disease and the prevalence of risk factors changes over time. The updates also enable the algorithm to take account of improvements to data quality (for example increases in the completeness of recording of risk factors such as ethnicity or laboratory values) and also allows adaptations to any changes which might be required to improve the predictive power of the tool or the population to which is applied.

Funding Source

No external funding

Research Team

Professor Julia Hippisley-Cox, Professor Carol Coupland

Website

QDiabetes​

Publications

  • Development and validation of risk prediction equations to estimate future risk of heart failure in patients with diabetes: prospective cohort study
    Authors: Hippisley-Cox J, Coupland CA.
    Ref: BMJ Open 2015;5; 9; e008503. doi:10.1136/bmjopen-2015-008503
    http://bmjopen.bmj.com/content/5/9/e008503.full
  • Development and validation of risk prediction equations to estimate future risk of blindness and lower limb amputation in patients with diabetes: cohort study
    Authors: Hippisley-Cox J, Coupland CA.
    Ref: BMJ 2015;351:h5441.
    http://www.bmj.com/content/351/bmj.h5441
  • Diabetes treatments and risk of heart failure, cardiovascular disease and all-cause mortality: cohort study in primary care
    Authors: Hippisley-Cox J, Coupland CA.
    Ref: BMJ 2016; 354; i3477
    http://www.bmj.com/content/bmj/354/bmj.i3477.full.pdf
  • Diabetes treatments and risk of amputation, blindness, severe kidney failure, hyperglycaemia and hypoglycaemia: cohort study in primary care
    Authors: Hippisley-Cox J, Coupland CA
    Ref: BMJ 2016;352:i1450
    http://www.bmj.com/content/bmj/352/bmj.i1450.full.pdf
  • Predicting risk of type 2 diabetes in England and Wales: prospective derivation and validation of the QDScore
    Authors: Hippisley-Cox J, Coupland C, Robson J, Sheikh A, Brindle P
    Ref: BMJ 2009;338:b880
    https://www.bmj.com/content/338/bmj.b880

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