It is estimated that one quarter of those with diabetes in the US, a staggering 7 million individuals, are not aware of their condition, and that almost half of those with known diabetes do not achieve optimal glycemic control. Individuals with undiagnosed or poorly controlled diabetes are at increased risk for many health complications, including periodontitis. Dental care settings have untapped potential for identifying undiagnosed dysglycemia, as well as contributing to the care of patients with known diabetes. Previously, co-investigators Lalla, Lamster, Kunzel, and Cheng conducted the first prospective study on dysglycemia detection in a dental clinic, and demonstrated that a simple model of 2 dental variables correctly identified 73% of undiagnosed pre- diabetes/diabetes cases among dental patients at-risk. Secondary use of the rich data held in the Marshfield Clinic's electronic medical and dental record will allow rapid evaluation of the external validity of that model while extendin the work longitudinally and to other considerations in the dental care of those with diabetes. At Marshfield, over 50,000 adults have been seen at both the Marshfield Medical Center and the affiliated dental clinics, and over 4,500 of these individuals are known to have diabetes. To the end of improving the care of diabetic patients in dental settings, this project will leverage the vast Marshfield clinical data warehouse to accomplish two specific aims: (1) To find the best model(s) to identify existing undiagnosed diabetes and prediabetes, and to forecast incident disease over a 5-year period, among dental patients, based on oral/periodontal health information as well as other patient information that is or could easily be available in a dental care setting; and (2) To determine the burden of a diabetic patient's level of glycemic control, disease duration, presence of other complications and comorbidities on his/her oral/periodontal status over time, response to non-surgical periodontal therapy, and healing following oral/periodontal surgery and/or tooth extractions. The proposed aims will explore heretofore un- and under-studied aspects of the oral health - diabetes relationship, and will be the first to examine the longitudinal relationship between important diabetes variables and oral/periodontal health measures, including response to periodontal therapy and healing following oral surgery and dental extractions. Through this strategic investment in the secondary analysis of medico-dental clinical data, our nation can rapidly and cost-efficiently advance our ability to detect diabetes and its complications, and to lessen their burden. Secondary use of clinical data is an essential part of a learning healthcare system lifecycle, and the investigators thus anticipate tha this work will provide dentistry with significant tools to complete the cycle thereby meeting the Institute of Medicine's charge to quicken our efforts to position evidence development and application as natural outgrowths of clinical care - to foster health care that learns.
Diabetes is a common chronic illness that can lead to serious complications, including severe gum disease. This project will (1) help to identify people with undiagnosed diabetes or at-risk for diabetes, and (2) determine the impact of certain diabetes parameters on oral health and on the response to (and recovery from) dental procedures. Because of the tremendous health and financial burden diabetes places on our nation, the proposed work is highly relevant to our public health.
| Acharya, A; Cheng, B; Koralkar, R et al. (2018) Screening for Diabetes Risk Using Integrated Dental and Medical Electronic Health Record Data. JDR Clin Trans Res 3:188-194 |
