Adaptive selection at G6PD and disparities in diabetes complications.

Diabetes complications occur at higher rates in individuals of African ancestry. Glucose-6-phosphate dehydrogenase deficiency (G6PDdef), common in some African populations, confers malaria resistance, and reduces hemoglobin A1c (HbA1c) levels by shortening erythrocyte lifespan. In a combined-ancestry genome-wide association study of diabetic retinopathy, we identified nine loci including a G6PDdef causal variant, rs1050828 -T (Val98Met), which was also associated with increased risk of other diabetes complications. The effect of rs1050828 -T on retinopathy was fully mediated by glucose levels. In the years preceding diabetes diagnosis and insulin prescription, glucose levels were significantly higher and HbA1c significantly lower in those with versus without G6PDdef. In the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial, participants with G6PDdef had significantly higher hazards of incident retinopathy and neuropathy. At the same HbA1c levels, G6PDdef participants in both ACCORD and the Million Veteran Program had significantly increased risk of retinopathy. We estimate that 12% and 9% of diabetic retinopathy and neuropathy cases, respectively, in participants of African ancestry are due to this exposure. Across continentally defined ancestral populations, the differences in frequency of rs1050828 -T and other G6PDdef alleles contribute to disparities in diabetes complications. Diabetes management guided by glucose or potentially genotype-adjusted HbA1c levels could lead to more timely diagnoses and appropriate intensification of therapy, decreasing the risk of diabetes complications in patients with G6PDdef alleles.

Type 1 Diabetes Genetic Risk in 109,954 Veterans With Adult-Onset Diabetes: The Million Veteran Program (MVP).

OBJECTIVE: To characterize high type 1 diabetes (T1D) genetic risk in a population where type 2 diabetes (T2D) predominates. RESEARCH DESIGN AND METHODS: Characteristics typically associated with T1D were assessed in 109,594 Million Veteran Program participants with adult-onset diabetes, 2011-2021, who had T1D genetic risk scores (GRS) defined as low (0 to <45%), medium (45 to <90%), high (90 to <95%), or highest (≥95%). RESULTS: T1D characteristics increased progressively with higher genetic risk (P < 0.001 for trend). A GRS ≥90% was more common with diabetes diagnoses before age 40 years, but 95% of those participants were diagnosed at age ≥40 years, and their characteristics resembled those of individuals with T2D in mean age (64.3 years) and BMI (32.3 kg/m2). Compared with the low-risk group, the highest-risk group was more likely to have diabetic ketoacidosis (low GRS 0.9% vs. highest GRS 3.7%), hypoglycemia prompting emergency visits (3.7% vs. 5.8%), outpatient plasma glucose <50 mg/dL (7.5% vs. 13.4%), a shorter median time to start insulin (3.5 vs. 1.4 years), use of a T1D diagnostic code (16.3% vs. 28.1%), low C-peptide levels if tested (1.8% vs. 32.4%), and glutamic acid decarboxylase antibodies (6.9% vs. 45.2%), all P < 0.001. CONCLUSIONS: Characteristics associated with T1D were increased with higher genetic risk, and especially with the top 10% of risk. However, the age and BMI of those participants resemble those of people with T2D, and a substantial proportion did not have diagnostic testing or use of T1D diagnostic codes. T1D genetic screening could be used to aid identification of adult-onset T1D in settings in which T2D predominates.

Racial differences in measures of glycemia in the Vitamin D and Type 2 Diabetes (D2d) Study: a secondary analysis of a randomized trial.

INTRODUCTION: Understanding how race may influence the association between A1c and glycemia can improve diabetes screening. We sought to determine whether, for a given A1c level, glucose levels during an oral glucose tolerance test (OGTT) differed by race. RESEARCH DESIGN AND METHODS: From data collected at 22 US clinical sites, we conducted a cross-sectional study of concurrently measured A1c and OGTT and observational longitudinal follow-up of the subset with high-risk pre-diabetes. Numerical integration methods were used to calculate area under the glycemic curve (AUCglu) during OGTT and least squares regression model to estimate A1c for a given AUCglu by race, controlling for potential confounders. RESULTS: 1016 black, 2658 white, and 193 Asian persons at risk of diabetes were included in cross-sectional analysis. Of these, 2154 with high-risk pre-diabetes were followed for 2.5 years. For a given A1c level, AUCglu was lower in black versus white participants. After adjustment for potential confounders, A1c levels for a given AUCglu quintile were 0.15-0.20 and 0.02-0.19 percentage points higher in black and Asian compared with white participants, respectively (p<0.05). In longitudinal analyses, black participants were more likely to be diagnosed with diabetes by A1c than white participants (28% vs 10%, respectively; p<0.01). Black and Asian participants were less likely to be diagnosed by fasting glucose than white participants (16% vs 15% vs 37%, respectively; p<0.05). Black participants with A1c levels in the lower-level quintiles had greater increase in A1c over time compared with white participants. CONCLUSIONS: Use of additional testing beyond A1c to screen for diabetes may better stratify diabetes risk in the diverse US population.

Development of Portable Electronic Health Record Based Algorithms to Identify Individuals with Diabetic Retinopathy.

Objectives: To develop, validate and implement algorithms to identify diabetic retinopathy (DR) cases and controls from electronic health care records (EHR)s. Methods : We developed and validated EHR-based algorithms to identify DR cases and individuals with type I or II diabetes without DR (controls) in three independent EHR systems: Vanderbilt University Medical Center Synthetic Derivative (VUMC), the VA Northeast Ohio Healthcare System (VANEOHS), and Massachusetts General Brigham (MGB). Cases were required to meet one of three criteria: 1) two or more dates with any DR ICD-9/10 code documented in the EHR, or 2) at least one affirmative health-factor or EPIC code for DR along with an ICD9/10 code for DR on a different day, or 3) at least one ICD-9/10 code for any DR occurring within 24 hours of an ophthalmology exam. Criteria for controls included affirmative evidence for diabetes as well as an ophthalmology exam. Results: The algorithms, developed and evaluated in VUMC through manual chart review, resulted in a positive predictive value (PPV) of 0.93 for cases and negative predictive value (NPV) of 0.97 for controls. Implementation of algorithms yielded similar metrics in VANEOHS (PPV=0.94; NPV=0.86) and lower in MGB (PPV=0.84; NPV=0.76). In comparison, use of DR definition as implemented in Phenome-wide association study (PheWAS) in VUMC, yielded similar PPV (0.92) but substantially reduced NPV (0.48). Implementation of the algorithms to the Million Veteran Program identified over 62,000 DR cases with genetic data including 14,549 African Americans and 6,209 Hispanics with DR. Conclusions/Discussion: We demonstrate the robustness of the algorithms at three separate health-care centers, with a minimum PPV of 0.84 and substantially improved NPV than existing high-throughput methods. We strongly encourage independent validation and incorporation of features unique to each EHR to enhance algorithm performance for DR cases and controls.

Potential misclassification of diabetes and prediabetes in the U.S.: Mismatched HbA1c and glucose in NHANES 2005-2016.

AIMS: To assess the prevalence and clinical implications of "mismatches" between HbA1c and glucose levels in the United States across the life course. METHODS: Participants ages 12-79 years from U.S. National Health and Nutrition Examination Survey (NHANES) 2005-2016 without known diagnosis of diabetes and who had a 75 g oral glucose tolerance test were included. Previously undiagnosed diabetes (DM), prediabetes, and normal glucose metabolism (NGM) were defined using American Diabetes Association cut-points. Mismatches were defined by the hemoglobin glycation index (HGI). RESULTS: In 10,361 participants, 5% and 41% had diabetes and prediabetes, respectively, by fasting or 2-hour glucose criteria. By HbA1c criteria, the high HGI tertile consisted of mostly abnormal classification (3% DM, 52% prediabetes) and the low HGI tertile contained mostly normal classification (78% NGM). Across all ages, 15% (weighted: 30 million individuals) had clinically significant mismatches of HGI magnitude ≥+0.5% (i.e., high mismatch) or ≤-0.5% (low mismatch). Mismatch was most common in older adults and non-Hispanic Black participants. CONCLUSIONS: Mismatches of clinically significant magnitude could lead to HbA1c-related misdiagnosis or inappropriate management in up to 30 million Americans. Older adults, non-Hispanic Black individuals, and others with high mismatches may benefit from complementing HbA1c with additional diagnostic and management strategies.

Increased Risk of Incident Diabetes Among Individuals With Latent Tuberculosis Infection.

OBJECTIVE: In cross-sectional U.S. studies, patients with diabetes had twice the prevalence of latent tuberculosis infection (LTBI) compared with those without diabetes. However, whether LTBI contributes to diabetes risk is unknown. We used longitudinal data to determine if LTBI is associated with increased diabetes incidence. RESEARCH DESIGN AND METHODS: We conducted a retrospective cohort study among U.S. Veterans receiving care in the Veterans Health Administration from 2000 to 2015. Eligibility included all patients without preexisting diabetes who received a tuberculin skin test (TST) or interferon-γ release assay (IGRA). We excluded patients with a history of active TB and those diagnosed with diabetes before or within 2 years after LTBI testing. Patients were followed until diabetes diagnosis, death, or 2015. LTBI was defined as TST or IGRA positive. Incident diabetes was defined by use of ICD-9 codes in combination with a diabetes drug prescription. RESULTS: Among 574,113 eligible patients, 5.3% received both TST/IGRA, 79.1% received TST only, and 15.6% received IGRA only. Overall, 6.6% had LTBI, and there were 2,535,149 person-years (PY) of follow-up after LTBI testing (median 3.2 years). The diabetes incidence rate (per 100,000 PY) was greater in patients with LTBI compared with those without (1,012 vs. 744; hazard ratio [HR] 1.4 [95% CI 1.3-1.4]). Increased diabetes incidence persisted after adjustment for covariates (adjusted HR [aHR] 1.2 [95% CI 1.2-1.3]) compared with those without LTBI. Among patients with LTBI, diabetes incidence was similar in those treated for LTBI compared with those who were not treated (aHR 1.0 [95% CI 0.9-1.1]). CONCLUSIONS: Comprehensive longitudinal data indicate that LTBI is associated with increased diabetes incidence. These results have implications for people with LTBI, ∼25% of the global population.

Differences in complications, cardiovascular risk factor, and diabetes management among participants enrolled at veterans affairs (VA) and non-VA medical centers in the glycemia reduction approaches in diabetes: A comparative effectiveness study (GRADE).

AIMS: We evaluated differences in participants with type 2 diabetes (T2DM) enrolled in the GRADE study at VA vs non-VA sites, focusing on cardiovascular risk factors and rates of diabetes care target achievements. METHODS: We compared baseline characteristics between participants at VA (n = 1216) and non-VA (n = 3831) sites, stratifying analyses by cardiovascular disease (CVD) history. RESULTS: VA and non-VA participants had similar diabetes duration (4.0 years), HbA1c (7.5%), and BMI (34 kg/m2); however, VA participants had more individuals ≥ 65 years (37.3% vs 19.8%, p < 0.001), men (90.0% vs 55.2%, p < 0.001), hypertension (75.8% vs 63.6%, p < 0.001), hyperlipidemia (76.6% vs 64.6%, p < 0.001), current smokers (19.0% vs 12.1%, p < 0.001), nephropathy (20.4% vs 17.0%, p < 0.05), albuminuria (18.4% vs 15.1%, p < 0.05), and CVD (10.4% vs 5.2%, p < 0.001). In those without CVD, more VA participants were treated with lipid (70.8% vs 59.5%, p < 0.001) and blood pressure (74.9% vs 65.4%, p < 0.001) lowering medications, and had LDL-C < 70 mg/dl (32.9% vs 24.2%, p < 0.05). Among those with CVD, more VA participants had BP < 140/90 (80.2% vs 70.1%, p < 0.05) after adjusting for demographics. CONCLUSION: GRADE participants at VA sites had more T2DM complications, greater CVD risk and were more likely to be treated with medications to reduce it, leading to more LDL-C at goal than non-VA participants, highlighting differences in diabetes populations and care.

Long-term metformin treatment and risk of peripheral neuropathy in older Veterans.

AIM: Our objective was to assess whether increased duration of metformin therapy is associated with incident peripheral neuropathy (PN) in older Veterans with diabetes. METHODS: Using national Veterans Affairs registry data from 2002 to 2015, we examined Veterans (50 + years) with diabetes. Long-term metformin therapy was defined as prescription ≥ 500 mg/day, filled for ≥ 6 consecutive months. Metformin therapy duration was examined both as continuous and categorical measures. Incident PN was defined by medical chart review. We estimated unadjusted and adjusted (variables selecteda priori)odds ratios (OR) and 95% confidence intervals (CI) using logistic regression. RESULTS: The study included n = 210,004 individuals (mean ± SD: age: 66.2 ± 8.4 yrs, 96% male) prescribed metformin for 47.0 ± 34.0 months. Nineteen percent developed PN during follow-up. After adjusting for age, body mass index, duration of time receiving health care within the VA, smoking status, alcohol abuse, and vitamin B12 testing and treatment, the number of months of metformin treatment was associated with elevated odds for incident PN (aOR (metformin treatment - continuous) = 1.009 (95% CI = 1.009, 1.010); aOR (metformin treatment - categorical (ref: 6-<18 months): 18-<44.1 months = 1.57 (1.51-1.63), 44.1-<61 months = 2.05 (1.97-2.14), 61 + months = 2.69 (2.58-2.79), all p-values < 0.0001). CONCLUSION: Our study suggests that Veterans treated for at least 18 months with metformin are approximately 2-3 times more likely to develop PN than those treated at least six, but<18 months. Future studies are needed to determine whether the association we found may be due to a decline in vitamin B12 status following metformin initiation.

Association Between Early Hypertension Control and Cardiovascular Disease Incidence in Veterans With Diabetes.

OBJECTIVE: Guidelines for hypertension treatment in patients with diabetes diverge regarding the systolic blood pressure (SBP) threshold at which treatment should be initiated and treatment goal. We examined associations of early SBP treatment with atherosclerotic cardiovascular disease (ASCVD) events in U.S. adults with diabetes. RESEARCH DESIGN AND METHODS: We studied 43,986 patients with diabetes who newly initiated antihypertensive therapy between 2002 and 2007. Patients were classified into categories based on SBP at treatment initiation (130-139 or ≥140 mmHg) and after 2 years of treatment (100-119, 120-129, 130-139, 140-159, and ≥160 mmHg). The primary outcome was composite ASCVD events (fatal and nonfatal myocardial infarction and stroke), estimated using inverse probability of treatment-weighted Poisson regression and multivariable Cox proportional hazards regression. RESULTS: Relative to individuals who initiated treatment when SBP was 130-139 mmHg, those with pretreatment SBP ≥140 mmHg had higher ASCVD risk (hazard ratio 1.10 [95% CI 1.02, 1.19]). Relative to those with pretreatment SBP of 130-139 mmHg and on-treatment SBP of 120-129 mmHg (reference group), ASCVD incidence was higher in those with pretreatment SBP ≥140 mmHg and on-treatment SBP 120-129 mmHg (adjusted incidence rate difference [IRD] 1.0 [-0.2 to 2.1] events/1,000 person-years) and in those who achieved on-treatment SBP 130-139 mmHg (IRD 1.9 [0.6, 3.2] and 1.1 [0.04, 2.2] events/1,000 person-years for those with pretreatment SBP 130-139 mmHg and ≥140 mmHg, respectively). CONCLUSIONS: In this observational study, patients with diabetes initiating antihypertensive therapy when SBP was 130-139 mmHg and those achieving on-treatment SBP <130 mmHg had better outcomes than those with higher SBP levels when initiating or after 2 years on treatment.

Random plasma glucose predicts the diagnosis of diabetes.

AIMS/HYPOTHESIS: Early recognition of those at high risk for diabetes as well as diabetes itself can permit preventive management, but many Americans with diabetes are undiagnosed. We sought to determine whether routinely available outpatient random plasma glucose (RPG) would be useful to facilitate the diagnosis of diabetes. METHODS: Retrospective cohort study of 942,446 U.S. Veterans without diagnosed diabetes, ≥3 RPG in a baseline year, and ≥1 primary care visit/year during 5-year follow-up. The primary outcome was incident diabetes (defined by diagnostic codes and outpatient prescription of a diabetes drug). RESULTS: Over 5 years, 94,599 were diagnosed with diabetes [DIAB] while 847,847 were not [NONDIAB]. Baseline demographics of DIAB and NONDIAB were clinically similar, except DIAB had higher BMI (32 vs. 28 kg/m2) and RPG (150 vs. 107 mg/dl), and were more likely to have Black race (18% vs. 15%), all p<0.001. ROC area for prediction of DIAB diagnosis within 1 year by demographic factors was 0.701, and 0.708 with addition of SBP, non-HDL cholesterol, and smoking. These were significantly less than that for prediction by baseline RPG alone (≥2 RPGs at/above a given level, ROC 0.878, p<0.001), which improved slightly when other factors were added (ROC 0.900, p<0.001). Having ≥2 RPGs ≥115 mg/dl had specificity 77% and sensitivity 87%, and ≥2 RPGs ≥130 mg/dl had specificity 93% and sensitivity 59%. For predicting diagnosis within 3 and 5 years by RPG alone, ROC was reduced but remained substantial (ROC 0.839 and 0.803, respectively). CONCLUSIONS: RPG levels below the diabetes "diagnostic" range (≥200 mg/dl) provide good discrimination for follow-up diagnosis. Use of such levels-obtained opportunistically, during outpatient visits-could signal the need for further testing, allow preventive intervention in high risk individuals before onset of disease, and lead to earlier identification of diabetes.

Nurse Practitioners, Physician Assistants, and Physicians Are Comparable in Managing the First Five Years of Diabetes.

BACKGROUND: Increasing use of nurse practitioners and physician assistants is a possible solution to the shortage of primary care providers in the United States, but the quality of care they provide is not well understood. METHODS: Because the scope of practice of the 3 provider types is similar in the Veterans Health Administration, we determined whether patients managed by primary care nurse practitioners, physician assistants, or physicians had similar hemoglobin A1c levels at comparable times in the natural history of diabetes. Our retrospective cohort study examined veterans with newly diagnosed diabetes in 2008, continuous primary care from 2008 to 2012, and more than 75% of primary care visits with nurse practitioner, physician assistant, or physician. RESULTS: Of the 19,238 patients, 95.3% were male, 77.7% were white, and they had a mean age 68.5 years; 14.7%, 7.1%, and 78.2% of patients were managed by nurse practitioners, physician assistants, and physicians, respectively. Median hemoglobin A1c was comparable at diagnosis (6.6%, 6.7%, 6.7%, P > .05) and after 4 years (all 6.5%, P > .5). Hemoglobin A1c levels at initiation of the first (7.5%-7.6%) and second (8.0%-8.2%) oral medications for patients of nurse practitioners and physician assistants compared with that of physicians was also similar after adjusting for patient characteristics (all P > .05). Nurse practitioners started insulin at a lower hemoglobin A1c (9.4%) than physicians (9.7%), which remained significant after adjustment (P < .05). CONCLUSIONS: At diagnosis and during 4 years of follow-up, diabetes management by nurse practitioners and physician assistants was comparable to management by physicians. The Veterans Health Administration model for roles of nurse practitioners and physician assistants may be broadly useful to help meet the demand for primary care providers in the United States.

Inpatient Glucose Values: Determining the Nondiabetic Range and Use in Identifying Patients at High Risk for Diabetes.

BACKGROUND: Many individuals with diabetes remain undiagnosed, leading to delays in treatment and higher risk for subsequent diabetes complications. Despite recommendations for diabetes screening in high-risk groups, the optimal approach is not known. We evaluated the utility of inpatient glucose levels as an opportunistic screening tool for identifying patients at high risk for diabetes. METHODS: We retrospectively examined 462,421 patients in the US Department of Veterans Affairs healthcare system, hospitalized on medical/surgical services in 2000-2010, for ≥3 days, with ≥2 inpatient random plasma glucose (RPG) measurements. All had continuity of care: ≥1 primary care visit and ≥1 glucose measurement within 2 years before hospitalization and yearly for ≥3 years after discharge. Glucose levels during hospitalization and incidence of diabetes within 3 years after discharge in patients without diabetes were evaluated. RESULTS: Patients had a mean age of 65.0 years, body mass index of 29.9 kg/m2, and were 96% male, 71% white, and 18% black. Pre-existing diabetes was present in 39.4%, 1.3% were diagnosed during hospitalization, 8.1% were diagnosed 5 years after discharge, and 51.3% were never diagnosed (NonDM). The NonDM group had the lowest mean hospital RPG value (112 mg/dL [6.2 mmol/L]). Having at least 2 RPG values >140 mg/dL (>7.8 mmol/L), the 95th percentile of NonDM hospital glucose, provided 81% specificity for identifying incident diabetes within 3 years after discharge. CONCLUSIONS: Screening for diabetes could be considered in patients with at least 2 hospital glucose values at/above the 95th percentile of the nondiabetic range (141 mg/dL [7.8 mmol/L]).

Participation in a National Lifestyle Change Program is associated with improved diabetes Control outcomes.

AIMS: Clinical trials show lifestyle change programs are beneficial, yet large-scale, successful translation of these programs is scarce. We investigated the association between participation in the largest U.S. lifestyle change program, MOVE!, and diabetes control outcomes. METHODS: This longitudinal, retrospective cohort study used Veterans Health Administration databases of patients with diabetes who participated in MOVE! between 2005 and 2012, or met eligibility criteria (BMI ≥25kg/m2) but did not participate. Main outcomes were diabetic eye disease, renal disease, and medication intensification. RESULTS: There were 400,170 eligible patients with diabetes, including 87,366 (22%) MOVE! PARTICIPANTS: Included patients were 96% male, 77% white, with mean age 58years and BMI 34kg/m2. Controlling for baseline measurements and age, race, sex, BMI, and antidiabetes medications, MOVE! participants had lower body weight (-0.6kg), random plasma glucose (-2.8mg/dL), and HbA1c (-0.1%) at 12months compared to nonparticipants (each p<0.001). In multivariable Cox models, MOVE! participants had lower incidence of eye disease (hazard ratio 0.80, 95% CI 0.75-0.84) and renal disease (HR 0.89, 95% CI 0.86-0.92) and reduced medication intensification (HR 0.82, 95% CI 0.80-0.84). CONCLUSIONS: If able to overcome participation challenges, lifestyle change programs in U.S. health systems may improve health among the growing patient population with diabetes.

Reduced Cardiovascular Disease Incidence With a National Lifestyle Change Program.

INTRODUCTION: Lifestyle change programs implemented within healthcare systems could reach many Americans, but their impact on cardiovascular disease (CVD) remains unclear. The MOVE! program is the largest lifestyle change program implemented in a healthcare setting in the U.S. This study aimed to determine whether MOVE! participation was associated with reduced CVD incidence. METHODS: This retrospective cohort study, analyzed in 2013-2015, used national Veterans Health Administration databases to identify MOVE! participants and eligible non-participants for comparison (2005-2012). Patients eligible for MOVE!-obese or overweight with a weight-related health condition, and no baseline CVD-were examined (N=1,463,003). Of these, 169,248 (12%) were MOVE! PARTICIPANTS: Patients were 92% male, 76% white, with mean age 52 years and BMI of 32. The main outcome was incidence of CVD (ICD-9 and procedure codes for coronary artery disease, cerebrovascular disease, peripheral vascular disease, and heart failure). RESULTS: Adjusting for age, race, sex, BMI, statin use, and baseline comorbidities, over a mean 4.9 years of follow-up, MOVE! participation was associated with lower incidence of total CVD (hazard ratio [HR]=0.83, 95% CI=0.80, 0.86); coronary artery disease (HR=0.81, 95% CI=0.77, 0.86); cerebrovascular disease (HR=0.87, 95% CI=0.82, 0.92); peripheral vascular disease (HR=0.89, 95% CI=0.83, 0.94); and heart failure (HR=0.78, 95% CI=0.74, 0.83). The association between MOVE! participation and CVD incidence remained significant when examined across categories of race/ethnicity, BMI, diabetes, hypertension, smoking status, and statin use. CONCLUSIONS: Although participation was limited, MOVE! was associated with reduced CVD incidence in a nationwide healthcare setting.

Sitagliptin for Type 2 diabetes: a 2015 update.

Sitagliptin, a dipeptidyl peptidase 4 inhibitor, was the first in its class to receive approval from the US FDA in 2006 for the treatment of Type 2 diabetes mellitus. It has been evaluated in numerous clinical trials and has several attractive features as an antidiabetic agent, including a low risk for hypoglycemia, a neutral effect on weight, and an ability to be used in chronic kidney disease and more. This article provides an up-to-date discussion of the pharmacokinetics/pharmacodynamics, clinical efficacy, safety and tolerability of sitagliptin.

Translating What Works: A New Approach to Improve Diabetes Management.

BACKGROUND: The most efficacious strategies to improve diabetes control include case management, health care team changes, patient education, and facilitated transmission of patient data to clinicians ("facilitated relay"), but these strategies have not been translated to permit general use in clinical practice. METHODS: A web-based decision support program was developed to include these features, and assessed in patients who had A1c ≥7.0% despite using metformin with/without sulfonylureas or insulin. Staff entered patients' glucose data, obtained management recommendations, reviewed the plan with a clinician, and discussed the new plan with patients. RESULTS: 113 subjects were 96% male and 32% black, with average age 65.6 years and BMI 32.8. During prior primary care, A1c averaged 8.32 ± 0.16% (SEM). In all patients, baseline A1c was 8.18 ± 0.11%, and decreased to 7.54 ± 0.12%, 7.16 ± 0.13%, and 7.54 ± 0.16% at 3, 6, and 12 months, respectively, all P < .001. In 42 subjects who provided glucose data and made requested changes in medications, A1c was 8.12 ± 0.09% at baseline and fell to 7.29 ± 0.11%, 6.98 ± 0.10%, and 7.05 ± 0.10% at 3, 6, and 12 months, respectively, all P < .001. Chart review of 16 subjects followed for 12 months demonstrated that hypoglycemia (symptoms and/or glucose <70 mg/dl) averaged less than 1 episode/patient/month, and there was no severe hypoglycemia. CONCLUSIONS: A novel decision support program improved A1c with little hypoglycemia. Use of this approach should allow primary care teams to keep patients well controlled, and reduce the need for specialist referrals.

Weight loss and incidence of diabetes with the Veterans Health Administration MOVE! lifestyle change programme: an observational study.

BACKGROUND: Programmes for lifestyle change are aimed at improving health but little is known about their effectiveness in clinical settings. The Veterans Health Administration (VA) MOVE! lifestyle change programme is the largest in the USA. We investigated whether participation in MOVE! is associated with reduced incidence of diabetes. METHODS: We did a retrospective observational analysis of data from VA databases in overweight patients and obese patients with a weight-related disorder who had undergone at least 3 years of continuous outpatient care in 2005-12. We used generalised estimating equations to assess characteristics associated with MOVE! participation, and Cox's proportional hazards regression to analyse the association between participation and diabetes incidence. FINDINGS: Of 1·8 million eligible individuals, 238 540 (13%) participated in the MOVE! programme. 19 367 (1% overall, 8% of participants) met criteria for intense and sustained participation (at least eight sessions within 6 months over at least a 4-month span), which was associated with greater weight loss at 3 years than low-intensity or no participation (-2·2% vs -0·64% or 0·46%). Compared with non-participation, incidence of diabetes was reduced by intense and sustained participation (hazard ratio 0·67, 95% CI 0·61-0·74) and low-intensity participation (0·80, 0·77-0·83) in MOVE!. These patterns were consistent across sex, ethnic origin, and age. Participation was most beneficial in patients with high BMI or high random glucose concentrations at baseline (both pinteraction<0·0001). INTERPRETATION: Participation in the MOVE! programme was associated with weight loss and reduced incidence of diabetes, but the rate of participation was low and, therefore, selection bias could have exaggerated these effects. FUNDING: US Department of Veterans Affairs, National Institutes of Health.

Increased cardiovascular disease, resource use, and costs before the clinical diagnosis of diabetes in veterans in the southeastern U.S.

IMPORTANCE: Screening for diabetes might be more widespread if adverse associations with cardiovascular disease (CVD), resource use, and costs were known to occur earlier than conventional clinical diagnosis. OBJECTIVE: The purpose of this study was to determine whether adverse effects associated with diabetes begin prior to clinical diagnosis. DESIGN: Veterans with diabetes were matched 1:2 with controls by follow-up, age, race/ethnicity, gender, and VA facility. CVD was obtained from ICD-9 codes, and resource use and costs from VA datasets. SETTING: VA facilities in SC, GA, and AL. PARTICIPANTS: Patients with and without diagnosed diabetes. MAIN OUTCOME MEASURES: Diagnosed CVD, resource use, and costs. RESULTS: In this study, the 2,062 diabetic patients and 4,124 controls were 63 years old on average, 99 % male, and 29 % black; BMI was 30.8 in diabetic patients vs. 27.8 in controls (p<0.001). CVD prevalence was higher and there were more outpatient visits in Year -4 before diagnosis through Year +4 after diagnosis among diabetic vs. control patients (all p<0.01); in Year -2, CVD prevalence was 31 % vs. 24 %, and outpatient visits were 22 vs. 19 per year, respectively. Total VA costs/year/veteran were higher in diabetic than control patients from Year -4 ($4,083 vs. $2,754) through Year +5 ($8,347 vs. $5,700) (p<0.003) for each, reflecting underlying increases in outpatient, inpatient, and pharmacy costs (p<0.05 for each). Regression analysis showed that diabetes contributed an average of $1,748/year to costs, independent of CVD (p<0.001). CONCLUSIONS AND RELEVANCE: VA costs per veteran are higher--over $1,000/year before and $2,000/year after diagnosis of diabetes--due to underlying increases in outpatient, inpatient, and pharmacy costs, greater number of outpatient visits, and increased CVD. Moreover, adverse associations with veterans' health and the VA healthcare system occur early in the natural history of the disease, several years before diabetes is diagnosed. Since adverse associations begin before diabetes is recognized, greater consideration should be given to systematic screening in order to permit earlier detection and initiation of preventive management. Keeping frequency of CVD and marginal costs in line with those of patients before diabetes is currently diagnosed has the potential to save up to $2 billion a year.

Medication reconciliation: comparing a customized medication history form to a standard medication form in a specialty clinic (CAMPII 2).

BACKGROUND: Medication history forms completed by patients are an essential part of the medication reconciliation process. OBJECTIVE: In a crossover prospective study, investigators compared the accuracy and acceptability of a "fill-in-the blank" medication history form (USUAL) to a customized form (CUSTOM) that contained a checklist of the 44 most frequently prescribed diabetes clinic medications. METHODS: The content of both forms was compared to a "gold-standard" medication list compiled by a clinical pharmacist who conducted a medication history and reviewed pharmacy profiles and medical chart. Subject preference and time to complete the forms were also determined. Accurate was defined as complete and correct (name, dose, and frequency) relative to the gold standard. RESULTS: A total of 77 subjects completed both forms. Complete list accuracy was poor; there was no difference in the accuracy between CUSTOM (6.5%) and USUAL (9.1%) (odds ratio [OR], 0.33; P = 0.62). Out of a total of 648 medications, subjects accurately listed 43.7% of medications on CUSTOM and 45.5% on USUAL (OR, 0.88; P = 0.41). The 44 medications on the checklist were more than twice as likely to be accurately reported using CUSTOM than with USUAL (OR, 2.1; P = 0.0002). More subjects preferred CUSTOM (65.7%) compared with USUAL (32.8%, P = 0.007). CONCLUSION: Medication self-report is very poor, and few subjects created an accurate list on either form. Subjects were more likely to report the drugs on the checklist using CUSTOM than when they used USUAL; however, there was no difference in the overall accuracy between CUSTOM and USUAL.