Evidence-Based Project Paper on Diabetes

Evidence-Based Project Paper on Diabetes

Grand Canyon University

AMP-450V

Diabetes is a lifetime disease that can affect people from all walks of life. In fact, it does, in yearly dramatic increased numbers. According to the National Institute of Diabetes and Digestive and Kidney Diseases (NIH), in the United States alone, there are over 30 million people that have diabetes. Moreover, “an estimated 84.1 million Americans aged 18 years or older have prediabetes” (Control, 2017, para. 4). Prediabetics are disposed to most of the identical risks as diabetics. It is typical that a prediabetic will progress to a diabetic due to the lack of lifestyle change. Consequently, adding to the rising numbers of diagnosed diabetes.

The risk factors of diabetes include high blood sugar, also referred to as blood glucose, levels in urine. These high levels of blood glucose may be caused in the pancreas, which produces “little or no insulin” in type 1 diabetics or if the body does not react normally to insulin in type 2 diabetics (Swartout-Corbeil & Oberleitner, 2018, p. 1134). Although there are several risk factors to consider, the major threats are high blood pressure, inactivity, and obesity. Genetics is also considered a great risk factor of diabetes among obese people. The Center for Disease and Control Prevention (CDC) explains that “genetic changes in human populations occur too slowly to be responsible for the obesity epidemic;” however, the disparities in how people react to similar environments propose that genes “do play a role in the development of obesity” (Public Health Genomics, 2018, para. 2).Thus, without a proper diet and lifestyle change, diabetics are prone to risk factors, such as heart attacks and high blood pressure.

Not only is there a huge emotional and physical burden on diabetics and their families but also a financial hardship. The American Diabetes Association reports “the total estimated cost of diagnosed diabetes in 2017 is $327 billion, including $237 billion in direct medical costs and $90 billion in reduced productivity” (Petersen, 2018, 921). Consequently, treatment for diabetics has progressed to many forms throughout the years. Researchers at the University of Exteter have established new method to effectively diagnose and treat patients with diabetes (Oram et. al., 2015, p. 337). Published in the journal Diabetes Care, researchers explain their study establishes genetic testing can be a valuable diagnostic tool for diabetes. A genetic test, in fact, can be helpful to doctors in precisely discriminating between type 1 and 2 diabetes and determining how to properly manage a patient’s diabetes (Oram et. al., 2015, p. 339). Thus, the discussion will focus on the practice of genetic testing and the functioning of the test as a diagnostic method for diabetes.

Research Method

According to the American Diabetes Association (ADA), “one in five Americans incorrectly believe that ‘eating too much sugar’ is a major risk factor for diabetes (Anderson-Parrado, 2008, p. 16). The reality is that history has determined that diabetes and obesity are closely related and occurs simultaneously. With disturbing increasing rates of obesity, the medical profession has found it progressively more challenging to discern diagnosing type 1 (T1D) diabetes and type 2 (T2D) diabetes in adults (Bellatorre & Choi, 2017, pg. 3-4). Researchers at the University of Exteter “developed genetic risk scores (GRSs) from published T1D- and T2D-associated variants” by initially testing if the scores worked well differentiate “clinically defined T1D and T2D from the Wellcome Trust Case Control Consortium (WTCCC) study, which included a sample size of 3,887 participants” (Oram et. al., 2015, p. 339).

The researchers at the University of Exteter evaluated “a cross-sectional cohort” of 223 participants between twenty to forty years old from “white European from Devon and Cornwall in South West England” who were diagnosed with diabetes no less than three years. The participants had their body mass index (BMI), GADA (GAD autoantibodies), and IA-2 (antigen 2) calculated and recorded. After assessing for the existence or non-existence of considerable insulin deficit, participants were classified accordingly. GRSs were then created for T1D and T2D implementing aggressively related genetic variants from other published research. To evaluate the results, the Exteter team formed a test which examines thirty genetic variations in participants’ deoxyribonucleic acid (DNA). Determined was that every one of the thirty genetic variations held a minute threat of T1D. Moreover, the test merged all the risks into a distinct score that characterized a summary of a participant’s genetic risk for T1D. Thus, a high score determined the participant to have T1D, while a low score determined a participant to have T2D. The University of Exteter study successfully produced a diabetes typology model to accurately discern between T1D and T2D via genetic testing.

Research Results

The University of Exteter is renowned worldwide for its leading edge research center focused on genetic risk factors of T1D and T2D. The research team has studied the clinical methods for diagnosing T1D and T2D among patients between twenty and forty years of age. Their findings concluded that it is frequently challenging for medical professionals to distinguish between T1D and T2D. Furthermore, current methods for diagnosing and testing for T1D and T2D are not always accurate or useful with the correct diagnosis among this age group. The Exteter team asserts that it is extremely critical to properly diagnosis diabetics as T1D or T2D as each type of diabetes is treated differently. While T2D can be controlled with medication, T1D necessitates insulin treatments. The team’s lead research, Dr. Oram, emphasizes “There is often no going back once insulin treatment starts. This may save people with Type 2 diabetes from being treated with insulin unnecessarily, but also stop the rare but serious occurrence of people with Type 1 being initially treated with tablets inappropriately and running of the risk of severe illness” (Oram et. al., 2015, p. 343).

The Exteter study also determined the nearly 15% of adults between twenty and forty have been mistakenly diagnosed and wrongly treated for T1D and T2D (Oram et. al., 2015, p. 339). Consequently, the initial misdiagnosis has accrued an unnecessary increase in treatment, monitoring, and drug costs. This does not include the life-threatening risks patients are suffering due to the erroneous diagnosis. According to Oram and his team, the diagnostic test currently in use to diagnose diabetes types has limitations as it only focus on the presence of one or a few autoantibodies in identify T1D. However, autoantibodies are imperfect discriminators as they can also be present in T2D patients. A research study supported by “National Human Genome Research Institute grant, National Institute of Mental Health grant, Young Investigator Award from the National Alliance for Research on Schizophrenia and Depression, and the Robert Wood Johnson Foundation,” using a nationwide sample from United States participants determined the worth of using “genes for understanding individual differences in a series of broad domains: physical illness, serious mental illness, intelligence, personality, and success in life (Shostak et. al., 2009, p. 82).

Conclusion

The results of the Exteter study found that genetic testing is the better method to accurately diagnose the difference between T1D and T2D. Subsequently, the Exteter research provides a modern method to provide accurate diagnosis that will provide patients with better quality of life benefits and may even save millions of newly diagnosed diabetics’ lives. The method of using genetic testing to avoid misdiagnosis for diabetes may very well benefit other diseases, such as heart disease, cancer, and, possibly, Alzheimer’s. The CDC reports that in 2011, one of the “ten leading causes of death in the United States” was diabetes (Johnson et. al., 2014, para. 6). The employment of genetic testing by medical professions to determine the difference between T1D and T2D will certainly help decrease the negative impact misdiagnosis of diabetes have for adults.

Reference

Anderson-Parrado, P. (2008). Type II diabetes and obesity: an all-too-common combination.

Bellatorre, A., Jackson, S. H., & Choi, K. (2017). Development of the diabetes typology model for discerning Type 2 diabetes mellitus with national survey data. PloS one, 12(3), 1-13.e0173103. doi:10.1371/journal.pone.0173103

Better Nutrition, 60(4), 14+. Retrieved from http://link.galegroup.com/apps/doc/A20471628/HWRC?u=cclc_trade&sid=HWRC&xid=149903e2

Control, P. A. (2017). CDC: 100 Million Have Diabetes or Prediabetes. Retrieved from http://www.diabetesincontrol.com/cdc-100-million-have-diabetes-or-prediabetes/

Johnson, N. B., MPH, Hayes, L. D., MBA, Hoo, E. C., MPH, & Ethier, K. A., PhD. (2014). CDC National Health Report: Leading Causes of Morbidity and Mortality and Associated Behavioral Risk and Protective Factors-United States, 2005–2013. Retrieved from https://www.cdc.gov/mmwr/preview/mmwrhtml/su6304a2.htm

Oram, Richard A., Kashyap Patel, Anita Hill, Beverley Shields, Timothy J. McDonald, Angus Jones, Andrew T. Hattersley, and Michael N. Weedon. (2015). A Type 1 diabetes genetic risk score can aid discrimination between Type 1 and Type 2 diabetes in young adults. Diabetes Care, 39(3), 337-344. DOI: 10.2337/dc15-1111

Petersen, Matthew P. (2018). Economic costs of diabetes in the U.S. in 2017. American Diabetes Association, 41(5), 917-928. https://doi.org/10.2337/dci18-0007

Public Health Genomics. (2018). Retrieved from https://www.cdc.gov/genomics/resources/diseases/obesity/index.htm

Shostak, S., Freese, J., Link, B. G., & Phelan, J. C. (2009). The Politics of the Gene: Social Status and Beliefs about Genetics for Individual Outcomes. Social Psychology Quarterly, 72(1), 77–93.

Swartout-Corbeil, D. M., R, & Oberleitner, M. G., DNS, RN. (2018). Diabetes Mellitus. In J. L. Longe (Ed.), The Gale Encyclopedia of Nursing and Allied Health (4th ed., Vol. 2, pp. 1131-1138). Farmington Hills, MI: Gale. Retrieved from http://link.galegroup.com/apps/doc/CX3662600342/HWRC?u=cclc_trade&sid=HWRC&xid=513cdbd1