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May 07, 2021 02:38pm
By Skylar Kenney, Assistant Editor
Two recently-created algorithms could provide retail clinicians with a new tool to evaluate a patient's risk of developing complications from diabetes.
Two recently-created algorithms could provide retail clinicians with a new tool to evaluate a patient’s risk of developing complications from diabetes.
The algorithms were developed by researchers at the University of Nottingham, who sought to devise a method by which practitioners could predict the absolute risk of blindness and amputation among patients with diabetes.
The research team designed the tools by analyzing data on approximately 455,000 diabetic patients ages 25 to 84 across 763 general practices in England. They then used mathematical models to calculate risk equations for blindness and amputation over a 10-year period, accounting for risk factors such as ethnicity, body mass index, blood pressure, and cholesterol levels.
After validating their models using data from a total of 611 practices, the researchers determined that their algorithms could explain 41% and 32% of the variation in time to amputation and blindness in men, respectively, and 38% and 31% of this variation in women, respectively.
These are the first tools capable of predicting the 10-year risk of blindness and amputation among diabetic patients, according to the researchers, who developed a Web-basedcalculatoralongside the algorithms that clinicians can use to estimate the 10-year risk of diabetes-related blindness and amputation.
The research team noted that the individualized risk estimates provided by their tools could help both patients and practitioners make more informed choices about how best to prevent diabetes-related complications.
“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 study authors wrote.
In an accompanying editorial published inBMJ, Azeem Majeed, MD, and Mariam Molokhia, MD, wrote that these tools “can help to provide the basis of a more individualized and holistic method of tackling these complications in patients.”
However, Drs. Majeed and Molokhia added that the models should be tested in actual practice, as well as in countries outside of the United Kingdom with a high prevalence of diabetes.
“We have some study weaknesses, including the lack of formal adjudication of diagnoses and the potential for bias due to missing data,” study author Julia Hippisley-Cox, MD, acknowledged in a press release. “But more accurate individualized information on the risk of complications may help patients to make more informed decisions about the balance of risks and benefits of treatment options reflecting their own values and choices.”