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Equation predicts blindness, amputation risk in diabetes

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Algorithm promotes patient-centered care

The risk factors in these final models – such as age, ethnicity, blood pressure, deprivation, glycated hemoglobin, and smoking for the amputation risk model – are what we might expect on the basis of previous research on complications of diabetes, but it is very useful to have the effect of each of these risk factors quantified.

People with diabetes can for the first time be given individualized risk scores based on their own characteristics and can also be shown how changes in their lifestyle or diabetes management affect their risk – for example, stopping smoking or tightening their blood glucose control – thus promoting more patient-centered care for people with diabetes.

Dr. Azeem Majeed is professor of primary care at Imperial College London and Dr. Mariam Molokhia is clinical reader in epidemiology and primary care at King’s College London. These comments are taken from an accompanying editorial (BMJ. 2015 Nov 11. doi: 10.1136/bmj.h5643). Neither author declared any conflicts of interest.


 

FROM BMJ

References

Researchers have developed and validated a set of algorithms to predict the likelihood that a patient with diabetes will develop blindness or require a limb amputation within 10 years, according to a paper published online Nov. 11 in the BMJ.

Using data from a British prospective cohort study of 454,575 primary care patients with diabetes, researchers looked at a large selection of risk factors for vascular disease, used these to develop risk prediction equations for men and women, then validated the equations in two separate cohorts totaling 348,469 patients.

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They found that for men in one of the two validation cohorts, the equations explained 40.6% of the variation in the time to amputation and 31.9% in time to blindness, with similar results for women (BMJ. 2015 Nov 11. doi: 10.1136/bmj.h5441).

“To our knowledge, these are the first tools for predicting the 10-year risk of both blindness and amputation, two of the complications that most concern patients with diabetes and affect quality of life,” wrote Dr. Julia Hippisley-Cox, professor of clinical epidemiology and general practice, Faculty of Medicine & Health Sciences, and Carol Coupland, Ph.D., both from the University of Nottingham (England).

“For clinicians and the health service, more accurate methods for stratifying patients according to their absolute risk of complications could enable screening programs to be tailored to an individual’s level of risk and support the more rational use of scarce resources.”

The authors declared a directorship or consultancy with ClinRisk, which produces software for the implementation of clinical risk equations within clinical computer systems.

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