A1C predicts type 2 diabetes and impaired glucose tolerance in a population at risk: the community diabetes prevention project.

AIMS: In a population at risk for type 2 diabetes (T2DM), we assessed early physical and metabolic markers that predict progression from normal to impaired glucose tolerance (IGT) and T2DM. METHODS: A total of 388 individuals (22% male, age 46 + 11 years) at risk for T2DM were randomized to Standard (n = 182) or Intervention (n = 206) care and evaluated at baseline and 5 annual follow-up visits, including blood pressure, BMI, A1C, lipids, urine albumin/creatinine ratio, VO2max, fasting glucose, insulin and C-peptide. The Standard group received results of annual lab tests and quarterly newsletters, while the Intervention group received quarterly newsletters and detailed discussions of lab results, routine self-directed activities, semi-annual group meetings and monthly telephone calls for ongoing support. RESULTS: Overall, 359 (93%) returned for at least one follow-up visit and 272 (70%) completed the final 5-year assessment. Return rates, changes in measures and incidence of IGT/T2DM were similar between groups. Low cardiorespiratory fitness (VO2max) was the most prevalent baseline abnormality. A1C and BMI were significant predictors of IGT/T2DM after controlling for other factors. The risk of IGT/T2DM within 5 years was 17.16 (95% CL: 6.169, 47.736) times greater for those with baseline A1C>=5.8% as compared to those <5.8% (p < 0.0001). CONCLUSION: Baseline A1C>=5.8% was a significant predictor of IGT/T2DM within 5 years in a population at high risk for T2DM. A1C is routinely performed among patients with diabetes, however these data and other evidence suggest that it may also be a useful tool for risk assessment and screening.

Evaluation of admission blood glucose levels in the intensive care unit.

OBJECTIVE: To assess the availability and clinical value of blood glucose (BG) testing at the time of admission to the intensive care unit (ICU) after such testing was implemented as routine care in the ICU. METHODS: We studied ICU admission BG testing rates and the prevalence of hyperglycemia. In this effort, we assessed the frequency of baseline BG testing in 330 consecutive patients during a period of 3 months and then implemented routine BG monitoring in 1,147 consecutive ICU patients during a 7-month period. RESULTS: Of the total study population, 25% had previously diagnosed diabetes (PDD). At baseline, 70% had BG measured within 4 hours before or after ICU admission (99% of patients with and 60% of patients without PDD). After implementation of routine BG monitoring, there was a significant increase in testing (70% before versus 87% after, P<0.001; 70% during the baseline 3-month period versus 93% in the final 3 months of the study, P<0.001). In patients without PDD, 41% had BG levels < or =140 mg/dL, and 8% had BG concentrations < or =200 mg/dL. Overall in the ICU setting, 57% of BG values < or =140 mg/dL and 33% of BG levels < or =200 mg/dL were in patients without PDD. Frequencies of BG testing by admission diagnosis included the following (at baseline and during the final 3 months after implementation of routine BG tests): postsurgical status (46%, 85%), peripheral vascular disease (51%, 90%), neurologic disease (52%, 83%), gastrointestinal disease (58%, 91%), infection (69%, 100%), and diabetes (100%, 100%). CONCLUSION: Rates of routine BG testing are low in ICU patients without PDD. Elevations in BG levels were detected in 41% of our study patients without PDD, suggesting that routine implementation of BG monitoring in an ICU will identify patients at increased risk for hyperglycemia-associated higher morbidity and mortality.

Integrated tobacco cessation counseling in a diabetes self-management training program: a randomized trial of diabetes and reduction of tobacco.

PURPOSE: The purpose of this study was to evaluate the impact of a tobacco cessation intervention using motivational interviewing on smoking cessation rates during diabetes self-management training (DSMT). METHODS: A randomized controlled trial was conducted with subjects recruited from an ongoing type 2 diabetes adult education program at a large diabetes center. A total of 114 subjects were randomized to intervention (n = 57; face-to-face motivational interviewing plus telephone counseling and offering of medication) or standard care (n = 57). Outcome measures included tobacco cessation rates, mean number of cigarettes smoked, A1C, weight, blood pressure, and lipids. RESULTS: Intensive intervention using motivational interviewing integrated into a standard DSMT program resulted in a trend toward greater abstinence at 3 months of follow-up in those receiving the intervention. However, this same trend was not observed at 6 months. The addition of this structured smoking cessation intervention did not negatively affect either diabetes education or other measures of diabetes management, including A1C values. CONCLUSIONS: Structured tobacco cessation efforts can be readily integrated into established diabetes education programs without a negative impact on diabetes care or delivery of diabetes education. However, an intervention of moderate intensity for smoking cessation was no more effective than usual care in assisting patients with tobacco cessation after 6-month follow-up. Whether a more intensive intervention, targeting patients expressing a readiness to discontinue tobacco use, and/or a longer duration or a more cumulative effect of treatment will be more effective must be evaluated.

Impact of modem-transferred blood glucose data on clinician work efficiency and patient glycemic control.

BACKGROUND: Communication of blood glucose (BG) results between patients and health care providers (HCPs) is of established benefit and remains a critical part of the diabetes management process. Currently, HCPs typically receive BG data from patients at the time of clinic visits or by telephone. The Accu-Chek Acculink modem (Roche Diagnostics Corp., Indianapolis, IN) provides an additional and attractive option that can potentially facilitate this communication. METHODS: To assess the impact of modem transfer of BG, we studied 47 participants with diabetes enrolled in a diabetes education program. Subjects were randomized to weekly communication of BG data to their HCP by either telephone (n = 23) or modem (n = 24) for 4 weeks. Mean age (+/- SD) was 44 +/- 15 years, 62% were female, 74% used insulin, 53% had type 1 diabetes, and mean baseline glycosylated hemoglobin (A1C) was 8.8% (range 5.2-13.2%). RESULTS: There were no differences between groups in the amount of time the HCP spent analyzing BG data and communicating with patients (12.6 +/- 6.1 min/week in the telephone group and 11.5 +/- 5.1 min/week in the modem group) or in the number of patient and HCP attempts needed to make contact. There were similar improvements in A1C between groups (change of -0.4 +/- 0.7% in the telephone group and -0.9 +/- 1.4% in the modem group, P = 0.18). BG data provided by telephone had a 6% error rate, in contrast to modem-sent data, which were transmitted without error. CONCLUSIONS: Modem transfer of BG data can provide an accurate and clinically useful option for communication between patients and their HCP and has comparable effects on A1C.

Clinical impact of prandial state, exercise, and site preparation on the equivalence of alternative-site blood glucose testing.

OBJECTIVE: To determine whether clinically significant differences exist in fasting blood glucose (BG) at the forearm, palm, and thigh relative to the fingertip; to assess the impact of prandial status by comparing BG between alternative sites and the fingertip at several time intervals after carbohydrate intake; to assess the effects of moderate brief exercise on site-to-site differences in BG; to evaluate the impact of site preparation by local rubbing on alternative-site testing (AST) equivalence; and to determine levels of perceived pain and satisfaction associated with AST. RESEARCH DESIGN AND METHODS: Fasting BG was measured using the One Touch Ultra (LifeScan, Milpitas, CA) at the fingertip, palm, thigh, and each forearm (with local rubbing) in 86 patients with type 2 diabetes. A 40-g carbohydrate meal was consumed and BG was again measured from each site at 60, 90, and 120 min postmeal, with an additional forearm test at 90 min without local rubbing. Patients then exercised for 15 min with repeat BG at each site. Differences in BG between sites were assessed using repeated-measures ANOVA and regression analyses. RESULTS: Significant differences in BG at alternative sites were found 60 min postmeal (P = 0.0003) and postexercise (P = 0.037). Specifically, clinically significant differences (expressed as percent difference from the fingertip) at 60 min include -8.8 +/- 10.8% at the forearm and -13.7 +/- 10.7% at the thigh, and postexercise +19.1 +/- 19.1% at the forearm and +15.6 +/- 22.6% at the thigh. However, no significant differences were observed between sites in either the fasting state or at 90 and 120 min postmeal. The dynamic results suggest a time lag in equilibration of forearm and thigh BG during periods of rapid glucose change. Palm and fingertip BG test results were similar at all time points. CONCLUSIONS: AST results are consistent with fingertip BG results in both the fasting state and 2 h postmeal; no benefit from site preparation by local rubbing was noted. However, testing at sites other than the hand cannot be recommended 1 h postmeal or immediately after exercise. AST is equivalent and appropriate for use at testing times commonly used in clinical practice.