Diabetes Population Trends Worrisome
A recent study examined trends in the prevalence of diabetes and control of risk factors over an 18-year span. Researchers included 28,143 participants using data from National Health and Nutrition Examination Survey. Here are the researchers’ top conclusions.
Prevalence on the Rise
Observations of the data showed that the prevalence of diabetes has increased significantly in recent years, from 9.8% in 1999-2000 to 14.3% in 2017-2018. Researchers estimated a 3.3% increase every two years. Of the subjects with diabetes, prevalence was highest in these groups:
Undiagnosed Cases Remains High
The study found that 11.2% of participants had diagnosed diabetes, while 3.4% had undiagnosed diabetes. This means that nearly one in four adults with diabetes were undiagnosed. Among young adults specifically, 40% were undiagnosed. Researchers reported that these numbers have not decreased significantly over time, except among non-Hispanic white individuals.
Only One in Five Adequately Reduce RiskFrom 2015 to 2018, only about 21% of diabetic adults were able to achieve all three risk factor goals: individualized hemoglobin A1c (HbA1c) targets, blood pressure under 130/80mm Hg and a low-density lipoprotein cholesterol level under 100mg/dL.
HbA1c targets were specified as follows:
• below 6.5% for young adults aged 18 to 41 without complications
• below 7% for both young adults with complications and middle-aged adults aged 45 to 64 without complications
• below 8% for both middle-aged adults and older adults aged 65 or older with complications
• below 7.5% for older adults without complications.
Among adults with diagnosed diabetes, 66.8% were able to reach their targeted HbA1c in the more recent 2015-2018 assessment as opposed to just 58.9% in 1999-2002. Overall, HbA1c levels are improving across the board as time goes on.
Wang L, Li X, Wang Z, et al. Trends in prevalence of diabetes and control of risk factors in diabetes among us adults, 1999-2018. JAMA. June 25, 2021. [Epub ahead of print].
Diabetic eye disease screenings are critically important in detecting retinopathy and maculopathy and preserving patient vision. Unfortunately, the reality is that many people with diabetes fail to meet screening recommendations because they have to see so many different providers for eye and general care. The option of telemedical screenings could mean better patient turn-out and sooner disease detection, but does accuracy suffer? A recent study shows that when done in a primary care office, telemedical screenings for diabetic eye disease can suffice, though image analysis can be lacking.
Seventy-two diabetic patients were included in this study (96% type 2 diabetes). The patients completed telemed screenings in a general practice setting, and retinal images were captured using a 45° non-mydriatic camera. Image quality was evaluated using a six-step scale, with a score of six indicating the image was over 90% evaluable. Each was assessed by a trained grader and an ophthalmologist experienced in retinal image analysis and diabetic retinopathy grading. Images were also analyzed using an automated image analysis software.
A total of 84% of exams were determined to be evaluable, and 83% were given a score of four or better for image quality 8% of patients were given a diagnosis of diabetic eye disease. Of 438 total retinal images captured, 89% matched the actual location determined by manual grading. Screenings were also time-efficient: 85% of patients completed imaging in under 10 minutes, and some were done in as little as three. However, as for image quality, many aspects still have room for improvement.
“Our results are similar to other studies evaluating automated retinal image analysis for [diabetic eye disease] screening, in which between 14% and 36% of images were rated non-evaluable by the algorithm and led to additional referrals for an ophthalmologist checkup,” the researchers wrote in their paper on the study. “Thus, manual grading might still be required for the foreseeable future for challenging images or cases classified as nonevaluable by existing [automated image analysis] algorithms as well as for quality control.”
As for now, manual grading remains the most accurate method of evaluating the ocular health of diabetes patients; however, artificial intelligence innovations in eye care continue to expand and improve, leading to better visual outcomes and more accessible, efficient screenings for diabetic patients and eye care providers.
Wintergerst MWM, Bejan V, Hartmann V, et al. Telemedical diabetic retinopathy screening in a primary care setting: quality of retinal photographs and accuracy of automated image analysis. Ophthalmic Epidemiology. 2021. [Epub ahead of print].