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OBJECTIVE The effect of therapeutic strategies on cardiovascular (CV) disease can be evaluated by monitoring changes in CV risk biomarkers. This study investigated the effect of a structured self-monitoring of blood glucose (SMBG) protocol and the resulting improvements in glycemic control on changes in high-sensitivity C-reactive protein (hs-CRP) in insulin-naïve patients with type 2 diabetes. RESEARCH DESIGN AND METHODS The Structured Testing Program (STeP) study was a prospective, cluster-randomized, multicenter trial in which 483 poorly controlled, insulin-naïve patients with type 2 diabetes were randomized to active control (ACG) or structured testing (STG) that included quarterly structured SMBG. Changes in A1C, hs-CRP, and glycemic variability (STG subjects only) were measured at baseline and quarterly. RESULTS Reductions in geometric mean hs-CRP values were significantly greater in the STG group at months 3 (P = 0.005), 6 (P = 0.0003), and 12 (P = 0.04) than in the ACG group. STG patients at high CV risk (>3 mg/L) showed significantly greater reductions in hs-CRP levels than ACG patients at high CV risk: −3.64 mg/dL (95% CI −4.21 to −3.06) versus −2.18 mg/dL (−2.93 to −1.43), respectively (P = 0.002). There was a strong correlation between reductions in hs-CRP and A1C in both groups: standardized coefficient (β) was 0.25 for the entire cohort (P < 0.0001), 0.31 for STG (P < 0.0001), and 0.16 for ACG (P = 0.02). CONCLUSIONS Reductions in hs-CRP level are associated with reductions in A1C but not reductions in lipids or glycemic variability. Comprehensive structured SMBG-based interventions that lower A1C may translate into improvements in CV risk, as evidenced by levels of the biomarker hs-CRP.

The primary aim of this study was to compare the results of HbA1c measurements with those of an OGTT for early diagnosis of ‘silent diabetes’ in patients with coronary artery disease (CAD) undergoing angiography without prediagnosed diabetes. A secondary aim was to investigate the correlation between the extent of CAD and the glycaemic status of the patient. Data from 1,015 patients admitted for acute (n = 149) or elective (n = 866) coronary angiography were analysed. Patients with known diabetes were excluded from the study. Using the OGTT results, patients were classified as having normal glucose tolerance (NGT), impaired fasting glucose (IFG), impaired glucose tolerance (IGT) or diabetes. According to the results of the HbA1c measurements, patients were classified into three groups: normal (HbA1c

Background: This study aimed to evaluate the effects of information management system (IMS) use with individuals with type 1 and type 2 diabetes who were treated in outpatient settings. Methods: In this 7-month, prospective, observational study, 965 adults with diabetes, mean (SD) baseline HbA1c 8.61(1.2)% (70.6[13.1] mmol/mol), were recruited from 132 outpatient care centers in Germany and Denmark. HbA1c was measured at baseline, month 4, and month 7. IMS reports were generated from uploaded self-monitored blood glucose data and therapy adjustments were documented at months 1 and 4. Hypoglycemic events were documented. Results: Mean (SD) HbA1c decreased from baseline in type 1 and type 2 diabetes patients at month 4 (–0.61[1.03]% (–6.7[11.3] mmol/mol), n = 213; –0.88[1.22]% (–9.6[13.3] mmol/mol), n = 589, respectively) and month 7 (–0.64[1.02]% (–7.0[11.1] mmol/mol), n = 219; –0.93[1.27]% (–10.2[13.9] mmol/mol), n = 594, respectively), all P < .0001, with no increase in hypoglycemic events. Therapy was adjusted in 106(42.7)% type 1 and 349(52.4)% type 2 diabetes patients at months 1 and 105(42.3)% type 1 and 282(42.3)% type 2 diabetes patients at month 4. Physicians used IMS reports to make therapy adjustments in 90% of patients at month 1 and 86% of patients at month 4. Conclusions: Integration of the IMS into outpatient care facilitates significant improvements in glycemic control.

Background: Neither profiles nor prognostic value of cardiac N-terminal proBNP (NT-proBNP) have been prospectively evaluated in a sufficient number of patients with severe chronic heart failure (CHF) treated with carvedilol or placebo. Methods: Baseline and follow-up plasma concentrations of NT-proBNP were measured in the European part of the COPERNICUS Trial. This study enrolled patients with an ejection fraction

Background— β-Blocking agents improve functional status and reduce morbidity in mild-to-moderate heart failure, but it is not known whether they produce such benefits in severe heart failure. Methods and Results— We randomly assigned 2289 patients with symptoms of heart failure at rest or on minimal exertion and with an ejection fraction P =0.00002) and the combined risk of death or hospitalization for heart failure by 31% ( P =0.000004). Patients in the carvedilol group also spent 27% fewer days in the hospital for any reason ( P =0.0005) and 40% fewer days in the hospital for heart failure ( P P =0.0009). Carvedilol-treated patients were also less likely than placebo-treated patients to experience a serious adverse event ( P =0.002), especially worsening heart failure, sudden death, cardiogenic shock, or ventricular tachycardia. Conclusion— In euvolemic patients with symptoms at rest or on minimal exertion, the addition of carvedilol to conventional therapy ameliorates the severity of heart failure and reduces the risk of clinical deterioration, hospitalization, and other serious adverse clinical events.

Aims: We investigated the impact of using an integrated, strip-free system compared to the use of singlestrip systems on testing frequency and glycemic control in individuals with insulin-treated diabetes. Methods: This multinational, comparative, cluster-randomized, observational study included 311 patients with type 1 and insulin-treated type 2 diabetes who were performing SMBG at suboptimal frequencies. Sites were cluster-randomized to “integrated strip-free” system (EXP group) or any “single-strip” system (CNL group). Testing frequency and HbA1c were measured at baseline, 12 weeks and 24 weeks. Results: At week 24, the EXP group showed an increase in SMBG frequency from baseline of 4.17 tests/ week (95% CI 2.76, 5.58) compared with an increase of 0.53 tests/week (95% CI � 0.73, 1.79) among CNL patients, resulting in a between-group difference of 3.63 tests/week (p < 0.0002). Mixed-effects models for repeated measurements (MMRM) controlling for baseline frequency of testing, country and clinical site confirmed a higher SMBG testing frequency in the EXP group compared to the CNL group, with a betweengroup difference of 2.70 tests/week (p < 0.01). Univariate analysis showed greater HbA1c reductions in the EXP group than CNL group: � 0.44% (95% CI � 0.59, � 0.29) vs. � 0.13% (95% CI � 0.27, 0.01), respectively, p < 0.0002. MMRM analyses confirmed these HbA1c reductions. A greater percentage of EXP than CNL patients achieved HbA1c reductions of � 0.5%: 45.1% vs. 29.1%, respectively, p < 0.01. Conclusions: The use of an integrated, strip-free SMBG system improved testing adherence and was associated with improvements in glycemic control.

Objective: Adiponectin is produced by adipose tissue and regarded as protective hormone for diabetes and coronary heart disease (CHD). Its role in heart failure is discussed controversially. Methods: In this study, 1015 consecutive patients admitted for acute ( n = 149) or elective ( n = 866) coronary angiography were enrolled. Patients with known diabetes mellitus (DM) were excluded. All patients were classified by oral glucose tolerance test (oGTT) according to World Health Organization (WHO) criteria and by the results of coronary angiography as no/minor coronary heart disease (CHD), single-vessel disease (1-VD), double-vessel disease (2-VD) or triple-vessel disease (3-VD), by New York Heart Association (NYHA) criteria and by echocardiography for heart failure. Adiponectin and N-terminal pro-brain natriuretic peptide (NT-proBNP) levels were measured in all patients. Results: Adiponectin was higher in patients with normal glucose tolerance (NGT) (13.65 ± 10.31 mg/l) compared to impaired glucose tolerance (IGT) (11.12 ± 7.5, p < 0.001) or diabetes (11.22 ± 7.63, p < 0.001). There was a stepwise decrease in adiponectin from no CHD (18.16 ± 12.49 mg/L) to minor CHD (16.01 ± 11.42) to 1-VD (12.18 ± 8.8, p < 0.001 to no/minor CHD) to 2- and 3-VD (10.68 ± 7.5, p < 0.001 to no/minor CHD, p = 0.004 to 1-VD). Patients with heart failure NYHA III (17.4 ± 10.27) had higher adiponectin levels compared to NYHA II (12.94 ± 9.41, p < 0.001 to NYHA III) and NYHA I (10.3 ± 7.75, p < 0.001 to NYHA III/II). In this line, adiponectin levels were positively correlated to NT-proBNP levels ( r = 0.303), and patients with ejection fraction (EF) < 50% had higher adiponectin levels than those with EF > 50% (14.96 ± 4.35 to 11.78 ± 3.71, p = 0.006). Conclusion: Adiponectin levels are inversely correlated to progressing CHD and glucose intolerance but positively correlated to increasing heart failure.

We have reported findings from a 3-month, noncontrolled, interventional study that used a modified version of the Structured Testing Program study intervention, demonstrating that this approach can be effectively adapted for use in general medical practice to improve hemoglobin A1c (HbA1c) levels.10 At study end, participants showed significant reductions in mean [standard deviation (SD)] HbA1c levels compared to baseline from 9.2% (1.6%) to 8.0% (1.4%), p < .001). Improvements in average blood glucose, body mass index, lipids, and blood pressure were also highly significant (p < .001). To further determine the efficacy of the intervention, we analyzed 6-month follow-up data from participants enrolled in our prior study and assessed changes in their glycemic control compared with that of participants who did not use structured SMBG. In our 6-month retrospectively controlled study, 526 diabetes patients (99 type 1, 423 type 2) were asked to generate a blood glucose profile before their 3-month and 6-month clinic visits, using a paper-based tool (ACCU-CHEK® 360° View Blood Glucose Analysis System, Roche Diagnostics, Mannheim, Germany). Measurements were taken before and 2 h after main meals and before bedtime on three consecutive days. End points included change from baseline in HbA1c and other parameters of diabetes complications. Data were also obtained from an additional 122 patients (control subjects) who did not use structured SMBG during the same time period. Baseline HbA1c values for the active and control groups were 9.5 (1.6%) and 9.1 (1.1%), respectively. At 6 months, paired HbA1c values were obtained for 281 active and 122 control group participants. Active group participants showed significantly greater reductions in mean (SD) HbA1c levels at 6 months compared with control group patients: -1.9% (2.0) vs -0.3% (0.1); p < .0001. The percentage of participants who reported at least one severe hypoglycemic event was significantly greater in the control group than in the active group: 34.4% (n = 42) vs 3.9% (n = 21). Our findings suggest that use of structured SMBG results in greater HbA1c improvement with markedly less hypoglycemia than use of nonstructured SMBG in poorly controlled type 1 diabetes mellitus and type 2 diabetes mellitus patients and that structured SMBG is practical in real-world clinical settings. Moreover, our results are consistent with findings from several trials in which structured SMBG was used as a component of treatment.2–9 Given the increasing prevalence of diabetes worldwide, it is important that treatment tools and approaches are used effectively to facilitate improved clinical outcomes and to reduce the costs associated with poorly managed diabetes. Contrary to random or unfocused glucose monitoring, structured SMBG has been shown to be a valuable, practical component of effective diabetes management in real-world clinical settings. Additional studies are needed to elucidate how structured SMBG can be used most effectively in various patient populations and practice settings.

The Structured Testing Program (STeP) study, a cluster-randomized, controlled trial, showed that a structured self-monitoring of blood glucose (SMBG)-based intervention improves clinical outcomes. It is important to determine whether this intervention can be adapted for use in general medical practice. This study examined the feasibility and effects of a modified version of the STeP intervention on clinical and attitudinal outcomes in real world clinical settings.In this 3-month, observational, multinational study, 375 type 1 and type 2 diabetes patients in 11 countries were asked to generate a blood glucose (bG) profile once per month for 3 consecutive months, using a paper-based bG analysis tool (Accu-Chek® 360° View® bG analysis system, Roche Diagnostics, Mannheim, Germany). Measurements were to be performed before and 2 h after main meals and before bedtime on 3 consecutive days. End points included change from baseline in glycated hemoglobin (HbA1c) and other parameters of diabetes complications. Patient and physician attitudes toward use of the structured testing form were also assessed.Reductions in mean (SD) HbA1c from baseline were significant, from 9.2% (1.6%) to 8.0% (1.4%) (Δ -1.2% [1.6%], P0.001). Reductions in mean (SD) average bG from baseline were significant, from 189.5 mg/dL (55.5 mg/dL) to 153 mg/dL (39.6 mg/dL) (Δ-36.4 mg/dL [52.5 mg/dL], P0.001). Significant (P0.001) improvements in body mass index, lipids, and blood pressure were also observed. Patients and physicians were generally positive about the utility of the structured testing form.Use of the structured SMBG intervention is practical in real world clinical settings and is associated with improved diabetes management.

Background: Daily routine for insulin-treated patients with diabetes mellitus requires correct performance of self-monitoring of blood glucose and insulin injections several times a day. Dexterity skills may play an important role in the performance efficacy of these procedures. Methods: We collected data of insulin-treated (>10 years) patients with different age ranges [healthy controls, 14 female/11 male, age (mean ± standard deviation) 55 ± 7 years; type 1 diabetes mellitus (T1DM) patients, 12/13, 45 ± 9 years, disease duration 23.9 ± 6.5 years; T2DM patients, 8/17, 64 ± 6 years, 16.2 ± 6.9 years; T2DM patients (>70 years of age), 9/16, 75 ± 4 years, 19.7 ± 7.0 years]. After assessment of neuropathy (temperature, pain, and vibration perception), the patients participated in two dexterity test batteries [Jebsen–Taylor hand-function test (JHFT) and motoric performance series (MPS)]. Results: Patients with type 2 diabetes showed disturbed vibration perception as compared to the other groups. The dexterity results were influenced by age to a large extent. Older T2DM patients performed worst in the majority of the subtests (e.g., JHFT, writing nondominant hand: control, 40.8 ± 11.7 s; T1DM, 46.3 ± 50.9 s, not significant versus control; old T2DM, 68.1 ± 29.5 s, p < .05; young T2DM, 52.5 ± 26.2 s, p < .05). Patients with type 1 diabetes showed similar JHFT and MPS results than the 10-year-older control subjects and performed outside of the age-dependent normal reference range. Conclusions: Manual skills and dexterity differed between the groups, and age-corrected reduced skills were common in both T1DM and T2DM patients in this study. Our findings underline the importance of considering dexterity and manual skills when designing medical devices for patients with diabetes mellitus.

Background— The utility of N-terminal proBNP (NT-proBNP) to predict the occurrence of death and hospitalization was prospectively evaluated in the COPERNICUS study, which enrolled patients with an ejection fraction Methods and Results— Baseline plasma concentrations of NT-proBNP were measured in a subgroup of 814 men and 197 women with symptoms at rest or on minimal exertion who were enrolled in the COPERNICUS study and were randomized to placebo (n=506) or carvedilol (n=505). Values of NT-proBNP were markedly increased despite the requirement that patients be euvolemic before the start of treatment (mean±SD, 3235±4392 pg/mL; median, 1767 pg/mL). By univariate Cox regression analysis, NT-proBNP was found to be a powerful predictor of subsequent all-cause mortality (relative risk [RR], 2.7; 95% CI, 1.7 to 4.3; P =0.0001 for above versus below median) and all-cause mortality or hospitalization for heart failure (RR, 2.4; 95% CI, 1.8 to 3.4; P =0.0001 for above versus below median). The predictive value of NT-proBNP was similar when both placebo and carvedilol patients were analyzed separately. No significant interaction was found between NT-proBNP and treatment group ( P =0.93 for above- versus below-median NT-proBNP). Conclusions— NT-proBNP was consistently associated with increased risk for all-cause mortality and for all-cause mortality or hospitalization for heart failure in patients with severe congestive heart failure, even in those who were clinically euvolemic. This marker therefore may be a useful tool in risk stratification of patients with severe congestive heart failure.