Globally, there has been a steep rise in diabetes between 1980 and 2014, with the prevalence among adults over this time period nearly doubling from 108 million (4.7%) to 422 million (8.5%). Type 2 diabetes mellitus (T2DM) accounts for most diabetes cases reported and is a major public health concern in the United States, affecting approximately 28 million adults and costing $245 billion annually.1,2 To place this number in context, every 17 seconds, an American is diagnosed with this chronic condition, a sobering and alarming fact of American life today.2,3 The high prevalence of T2DM is partially attributable to increases in the prevalence of obesity, and estimates predict that by 2050, 1 in 3 Americans will have diabetes if no measures are taken.2,4 A similar high prevalence and rapid rise in rates of diabetes have been reported in middle- and low-income countries.1

Diabetes is a major risk factor for cardiovascular disease (CVD) and stroke, increasing the risk of developing CVD or cerebrovascular disease (stroke) 2- to 4-fold.5 Among adults 65 years or older who have diabetes, current estimates are that 68% will die of CVD and 16% will die of stroke.5 Early detection, diagnosis, and management of diabetes are important in the prevention of CVD; however, many cases of diabetes go undetected and undiagnosed.1 Globally, the prevalence of undiagnosed diabetes and prediabetes (impaired glucose tolerance) continues to rise, with resource-limited settings reporting the highest rates of undetected diabetes (65%).3,6 Of particular concern, estimates indicate that 90% of individuals with prediabetes are unaware of their condition.2,3 This is important because without prevention efforts, 15% to 30% of individuals with prediabetes will progress to T2DM within 5 years.2

These worrisome trends in the high prevalence of undetected/undiagnosed T2DM and prediabetes prompted the American Heart Association (AHA) and American Diabetes Association (ADA) to revise the current screening recommendations for diabetes to add glycated hemoglobin (A_1c) as a diagnostic criterion.7 Previously, A_1c had been a guide to management but the addition of this common clinical measure to screening was deemed important to identify more new cases of diabetes and to treat individuals with diabetes earlier in the course of the disease. Early screening and detection has been shown to be effective.8 In a randomized control trial-The Anglo-Danish-Dutch Study of Intensive Treatment in People With Screen-Detected Diabetes in Primary Care (ADDITION-Europe)-screening followed by treatment of T2DM led to a significant reduction in the development of CVD or death in a 5-year follow-up study.8 However, screening for T2DM and prediabetes using traditional serum-based methods such as fasting plasma glucose (FPG), oral glucose tolerance test (OGTT), or A_1c is not always feasible in low-income settings because of lack of access and the costs associated with testing. Alternatively, the use of simple, noninvasive, and cost-effective screening tools has been proposed as an effective strategy for detecting undiagnosed diabetes and glucose intolerance.9

TABLE No Caption Available

These screening tests/tools are used to detect risk factors or diagnose diseases at the preclinical stage and have a vital role in preventing the future occurrence of disease or complications. The ADA recommends screening for asymptomatic T2DM under the following circumstances: (1) the disease imposes significant burden on the population; (2) the natural history of the disease is understood; (3) there is a recognizable preclinical stage of the disease that can be diagnosed; (4) acceptable and reliable tests exist for detecting preclinical stage of disease; (5) the initiation of treatment after the diagnosis yields superior benefits than if the initiation is delayed; (6) the costs of case finding and treatment are reasonable with the resources available; and (7) screening will be an ongoing process.10 In some settings, it is difficult to obtain invasive laboratory screening tests because they are expensive, less acceptable to patients, and require fasting blood samples.11 Noninvasive tools that can be used in the clinical and/or community setting to identify or detect the individual's risk of having undiagnosed T2DM or prediabetes offer a more cost effective and personally acceptable alternative. Given the prevalence of undiagnosed/undetected diabetes and prediabetes globally and the higher burden of disease borne by resource-constrained populations, the World Health Organization has declared the identification of cost-effective screening tools and equitable access to screening and prevention as strategic priorities to reduce CVD-related morbidity and mortality.12

In the screening tools discussed in this article, the 2016 ADA diabetes guidelines for diagnosis of diabetes were used as standards for diabetes screening as follows13:

Fifteen noninvasive screening tools were identified through a review of the literature, and of those 15 tools, 7 were chosen for inclusion in this article. Although it is not within the scope of this article to fully summarize the systematic review of the literature that was conducted, it is important to note that rigorous methods were used in the search strategy and in the critique of existing tools.14,15 The tools included in the Table were chosen because they demonstrated high performance or internal validity as measured by sensitivity (true positive rate; >=70%) and specificity (true negative rate; >=60%) and utilized at least 5 risk factors for predicting the probability of having undiagnosed diabetes and/or prediabetes. The EZSCAN electronic device, which evaluates sweat gland function, used 4 screening variables, yet it had an impressive performance.

TABLE Characteristics of 7 High-Performing Noninvasive Tools for Screening Prediabetes and Undiagnosed Diabetes

Three screening tools, Diabetes Risk Calculator, Finnish Diabetes Risk Score (FINDRISC), and EZSCAN system device, had the highest sensitivity scores (>=80%), while maintaining an acceptable specificity (>=60%). Noteworthy is that the best performing screening tools were developed and validated using large sample sizes representative of the respective populations. In addition, tools developed with innovative methodology or computer technology had a higher performance than most of the other tools, while maintaining the ease of use. For instance, the Diabetes Risk Calculator was developed using a new classification and regression tree method, a powerful tool for analysis of nonlinear parameters. The classification and regression tree technique separates data into mutually exclusive groups and detects complex nonlinear relationships between multiple predictors for a disease, similar to mechanisms used in machine learning modeling in development of algorithms.16,17 Innovative technologies such as machine learning modeling and EZSCAN performed better than most of the screening tools. This illustrates the need to use newer technologies in the development of screening tools.

Collective results suggest that screening tools for undiagnosed T2DM and prediabetes are available and have adequate sensitivity and specificity to detect prediabetes and diabetes. These tools have applicability both in the clinical area and at the community level and have the potential to reduce the current barriers to screening for diabetes especially among low-income populations. It is worth noting that most of the screening tools were developed in high-resource populations; the performance of these tools remains unknown in many low-resource settings, where a high prevalence of diabetes and CVD has been observed. However, that said, the potential benefit of implementing screening tools in resource-constrained settings outweighs the risk and seems prudent until more population-specific evidence is available. The tools presented in the Table are simple to use, noninvasive, inexpensive, and feasible for populations in dire need of diabetes screening services.

In primary care settings as well as specialized CVD and metabolic clinics, nurses and nurse practitioners assess and manage patients with or at-risk for cardiometabolic conditions. The screening tools presented in this article add value to the nurse-led prevention visit by providing a simple, noninvasive, and low-cost way to identify individuals with prediabetes and undetected diabetes, often asymptomatic at this stage, earlier in the trajectory of the disease. This in turn provides the opportunity for early guideline concordant pharmacologic and nonpharmacologic treatment, which is critical to reducing the development of comorbid diabetes and CVD. As noted, these tools are particularly needed, and useful, in resource-constrained settings, where the burden of disease and rates of undetected disease are alarmingly high. Nurses are among the largest healthcare workforce globally and often have greater access to underserved populations. Using the simple noninvasive screening tools described in the Table has immense potential to reach individuals with undiagnosed glucose intolerance or diabetes who might otherwise go undiagnosed and untreated. Future research should focus on developing and evaluating the most appropriate tools for detecting undiagnosed T2DM and/or prediabetes in resource-constrained settings and performing more rigorous cost-effectiveness analysis to measure their impact on CVD prevention.

Acknowledgments

The authors acknowledge insightful and scholarly suggestions contributed by Drs Mary Cooley and Laura Hayman to this manuscript.

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