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      Clinical Care Among Individuals with Prediabetes in Primary Care: a Retrospective Cohort Study

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          Abstract

          Background

          The incidence of diabetes in the general US population (6.7 per 1000 adults in 2018) has not changed significantly since 2000, suggesting that individuals with prediabetes are not connecting to evidence-based interventions.

          Objective

          We sought to describe the clinical care of individuals with prediabetes, determine patient factors associated with this care, and evaluate risk for diabetes development.

          Design

          Retrospective cohort study using linked claims and electronic health record data.

          Participants

          We created a cohort of adults with prediabetes based on laboratory measures. We excluded patients with a prior history of diabetes, pregnancy in prior 6 months, or recent steroid use.

          Main Measures

          We measured ordering and completion of clinical services targeting prediabetes management and diabetes incidence within 12 months following cohort entry. We tested the strength of the association between individuals’ characteristics and outcomes of interest using bivariate and multiple logistic regression.

          Results

          Our cohort included 3888 patients with a laboratory diagnosis of prediabetes (incident or prevalent prediabetes). Within 12 months, 63.4% had repeat glycemic testing, yet only 10.4% had coded diagnoses of prediabetes, 1.0% were referred for nutrition services, and 5.4% were prescribed metformin. Most patients completed labs and nutrition visits when referred and filled metformin when prescribed. Individuals with a higher glycemic level or BMI were more likely to receive prediabetes clinical care. Six percent of individuals developed diabetes within 12 months of cohort entry and had higher glycemic levels and BMI ≥ 30 kg/m 2. In the adjusted model, Black individuals had 1.4 times higher odds of developing diabetes than White individuals.

          Conclusions

          Rates of prediabetes clinical care activities are low and have not improved. Strategies are urgently needed to improve prediabetes care delivery thereby preventing or delaying incident diabetes.

          Supplementary Information

          The online version contains supplementary material available at 10.1007/s11606-022-07412-9.

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          Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin.

          Paul Nathan, Elizabeth Barrett, John M. Lachin … (2002)
          Type 2 diabetes affects approximately 8 percent of adults in the United States. Some risk factors--elevated plasma glucose concentrations in the fasting state and after an oral glucose load, overweight, and a sedentary lifestyle--are potentially reversible. We hypothesized that modifying these factors with a lifestyle-intervention program or the administration of metformin would prevent or delay the development of diabetes. We randomly assigned 3234 nondiabetic persons with elevated fasting and post-load plasma glucose concentrations to placebo, metformin (850 mg twice daily), or a lifestyle-modification program with the goals of at least a 7 percent weight loss and at least 150 minutes of physical activity per week. The mean age of the participants was 51 years, and the mean body-mass index (the weight in kilograms divided by the square of the height in meters) was 34.0; 68 percent were women, and 45 percent were members of minority groups. The average follow-up was 2.8 years. The incidence of diabetes was 11.0, 7.8, and 4.8 cases per 100 person-years in the placebo, metformin, and lifestyle groups, respectively. The lifestyle intervention reduced the incidence by 58 percent (95 percent confidence interval, 48 to 66 percent) and metformin by 31 percent (95 percent confidence interval, 17 to 43 percent), as compared with placebo; the lifestyle intervention was significantly more effective than metformin. To prevent one case of diabetes during a period of three years, 6.9 persons would have to participate in the lifestyle-intervention program, and 13.9 would have to receive metformin. Lifestyle changes and treatment with metformin both reduced the incidence of diabetes in persons at high risk. The lifestyle intervention was more effective than metformin.
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            Prediabetes: a high-risk state for diabetes development

            Adam G. Tabak, Christian Herder, Wolfgang Rathmann … (2012)
            Prediabetes (intermediate hyperglycaemia) is a high-risk state for diabetes that is defined by glycaemic variables that are higher than normal, but lower than diabetes thresholds. 5-10% of people per year with prediabetes will progress to diabetes, with the same proportion converting back to normoglycaemia. Prevalence of prediabetes is increasing worldwide and experts have projected that more than 470 million people will have prediabetes by 2030. Prediabetes is associated with the simultaneous presence of insulin resistance and β-cell dysfunction-abnormalities that start before glucose changes are detectable. Observational evidence shows associations between prediabetes and early forms of nephropathy, chronic kidney disease, small fibre neuropathy, diabetic retinopathy, and increased risk of macrovascular disease. Multifactorial risk scores using non-invasive measures and blood-based metabolic traits, in addition to glycaemic values, could optimise estimation of diabetes risk. For prediabetic individuals, lifestyle modification is the cornerstone of diabetes prevention, with evidence of a 40-70% relative-risk reduction. Accumulating data also show potential benefits from pharmacotherapy. Copyright © 2012 Elsevier Ltd. All rights reserved.
            Article 0 comments Cited 576 times – based on 0 reviews     Review now
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              A modification of the Elixhauser comorbidity measures into a point system for hospital death using administrative data.

              P. Austin, Alison Jennings, Hude Quan … (2009)
              Comorbidity measures are necessary to describe patient populations and adjust for confounding. In direct comparisons, studies have found the Elixhauser comorbidity system to be statistically slightly superior to the Charlson comorbidity system at adjusting for comorbidity. However, the Elixhauser classification system requires 30 binary variables, making its use for reporting and analysis of comorbidity cumbersome. Modify the Elixhauser classification system into a single numeric score for administrative data. For all hospitalizations at the Ottawa Hospital, Canada, between 1996 and 2008, we determined if International Classification of Disease codes for chronic diagnoses were in any of the 30 Elixhauser comorbidity groups. We then used backward stepwise multivariate logistic regression to determine the independent association of each comorbidity group with death in hospital. Regression coefficients were modified into a scoring system that reflected the strength of each comorbidity group's independent association with hospital death. Hospitalizations that were included were 345,795 (derivation: 228,565; validation 117,230). Twenty-one of the 30 groups were independently associated with hospital mortality. The resulting comorbidity score had an equivalent discrimination in the derivation and validation groups (overall c-statistic 0.763, 95% CI: 0.759-0.766). This was similar to models having all Elixhauser groups (0.760, 95% CI: 0.756-0.764) or significant groups only (0.759, 95% CI: 0.754-0.762), but significantly exceeded discrimination when comorbidity was expressed using the Charlson score (0.745, 95% CI: 0.742-0.749). When analyzing administrative data, the Elixhauser comorbidity system can be condensed to a single numeric score that summarizes disease burden and is adequately discriminative for death in hospital.
              Article 0 comments Cited 389 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Eva Tseng:
                ORCID: http://orcid.org/0000-0003-4001-2869
                etseng3@jhmi.edu
                Journal
                Journal ID (nlm-ta): J Gen Intern Med
                Journal ID (iso-abbrev): J Gen Intern Med
                Title: Journal of General Internal Medicine
                Publisher: Springer International Publishing (Cham )
                ISSN (Print): 0884-8734
                ISSN (Electronic): 1525-1497
                Publication date (Electronic): 2 March 2022
                Pages: 1-8
                Affiliations
                [1 ]GRID grid.21107.35, ISNI 0000 0001 2171 9311, Division of General Internal Medicine, , Johns Hopkins University School of Medicine, ; Baltimore, MD USA
                [2 ]GRID grid.21107.35, ISNI 0000 0001 2171 9311, Welch Center for Prevention, Epidemiology, & Clinical Research, , Johns Hopkins University, ; Baltimore, MD USA
                [3 ]GRID grid.21107.35, ISNI 0000 0001 2171 9311, Department of Epidemiology, , Johns Hopkins University Bloomberg School of Public Health, ; Baltimore, MD USA
                [4 ]GRID grid.21107.35, ISNI 0000 0001 2171 9311, Department of Health Policy and Management, , Johns Hopkins University Bloomberg School of Public Health, ; Baltimore, MD USA
                [5 ]GRID grid.21107.35, ISNI 0000 0001 2171 9311, Center for Drug Safety and Effectiveness, , Johns Hopkins University, ; Baltimore, MD USA
                Author information
                http://orcid.org/0000-0003-4001-2869
                Article
                Publisher ID: 7412
                DOI: 10.1007/s11606-022-07412-9
                PMC ID: 8890680
                PubMed ID: 35237886
                SO-VID: 10c2a4b4-2d69-4075-b7b4-46226cf80fdd
                Copyright © © The Author(s) under exclusive licence to Society of General Internal Medicine 2022
                License:

                This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.

                History
                Date received : 6 October 2021
                Date accepted : 7 January 2022
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000062, National Institute of Diabetes and Digestive and Kidney Diseases;
                Award ID: K23DK118205
                Award Recipient :
                Categories
                Subject: Original Research

                ScienceOpen disciplines: Internal medicine
                Keywords: prediabetes,diabetes prevention,primary care,electronic health record data,claims data,diabetes
                Data availability:
                ScienceOpen disciplines: Internal medicine
                Keywords: prediabetes, diabetes prevention, primary care, electronic health record data, claims data, diabetes

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