Researchers have generated an equation to estimate the probable life expectancies of patients with diabetes who experience a major complication.
“The equation is based on age, sex and commonly collected clinical information and thereby provides further stratification of a patient’s prognosis after the occurrence of a life-threatening event”, study author Philip Clarke (University of Melbourne, Victoria, Australia) and co-workers write in Diabetic Medicine.
They used data from 20,836 patients in the Swedish National Diabetes Register who were assessed during at least one clinic visit prior to having a major complication: myocardial infarction; stroke; heart failure; amputation or renal failure.
Life expectancy varied according to the specific complication and time since the event, with myocardial infarction and stroke imparting the highest mortality risk in the first week after the event, but heart failure, amputation and renal failure predominating after 1 month. In general, a patient experiencing one of these complications at the age of 70 years could expect to live about 3 years after renal failure, rising to about 6 years after a stroke.
Notably, life expectancy was not influenced by the “classic” risk factors of high body mass index (BMI), systolic blood pressure or glycated haemoglobin levels.
Instead, smoking and macroalbuminuria had the strongest adverse effect on life expectancy, with other significant factors including male gender, low estimated glomerular filtration rate, low BMI and low systolic blood pressure.
As a specific example, the team says that a 70-year-old man with an average risk factor profile could expect to live for 6.7 years after a myocardial infarction. Smoking would take about 2 years off this life expectancy and having macroalbuminuria would reduce it by 0.7 years, with other factors having smaller effects.
The researchers say that their equation “could be programmed into a life expectancy or mortality calculator to provide information on prognosis for both doctor and patient.”
In addition, they say that the ability to calculate life expectancy with greater accuracy would also assist the calculation of annuities and life insurance for diabetes patients, “which have been shown often to be actuarily unfair” and would help in simulation models to evaluate diabetes treatments.
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