Objective

The Framingham 10-risk of coronary heart disease (CHD) has been a widely studied estimate of cardiovascular risk in the general population. However, few studies have compared the relative risk of developing CHD in antipsychotic-treated patients with different psychiatric disorders, especially in older patients with psychotic symptoms. In this study, we compared the 10-year risk of developing CHD among middle-aged and older patients with psychotic symptoms to that in the general population.

Method

We analyzed baseline data from a study examining metabolic and cardiovascular effects of atypical antipsychotics in patients over age 40 with psychotic symptoms. After excluding patients with prior history of CHD and stroke, 179 subjects were included in this study. Among them, 68 had a diagnosis of schizophrenia, 42 mood disorder, 38 dementia, and 31 PTSD. Clinical evaluations included medical and pharmacologic treatment history, physical examination, and clinical labs for metabolic profiles. Using the Framingham 10–year risk of developing CHD based on the Framingham Heart Study (FHS), we calculated the risk CHD risk for each patient, and then compared relative risk in each psychiatric diagnosis to the risks reported in the FHS.

Results

The mean age of entire sample was 63 (range 40–94) years, 68% were men. The Framingham 10-year risk of CHD was increased by 79% in schizophrenia, 72% in PTSD, 61% in mood disorder with psychosis, and 11% in dementia relative to the risk in general population from the FHS.

Conclusions

In this sample of middle-aged and older patients with psychotic symptoms, we found a significantly increased 10-year risk of CHD relative to the estimated risk from FHS, with the greatest increased risk for patients with schizophrenia and PTSD. Development of optimally tailored prevention and intervention efforts to decrease different risk components in these patients could be an important step to help decrease the risks of CHD and overall mortality in this vulnerable population.

OBJECTIVE

This study investigated the hypothesis that baseline calcified coronary atherosclerosis may determine cardiovascular disease events in response to intensive glycemic control within the Veterans Affairs Diabetes Trial (VADT).

RESEARCH DESIGN AND METHODS

At baseline, 301 type 2 diabetic participants in the VADT, a randomized trial comparing the effects of intensive versus standard glucose lowering on cardiovascular events, had baseline coronary atherosclerosis assessed by coronary artery calcium (CAC) measured by computed tomography. Participants were followed over the 7.5-year study for development of cardiovascular end points.

RESULTS

During a median follow-up duration of 5.2 years, 89 cardiovascular events occurred. Although intensive glucose-lowering therapy did not significantly reduce cardiovascular events in the substudy cohort as a whole, there was evidence that the response was modified by baseline CAC, as indicated by significant P values for treatment by log(CAC + 1) interaction terms in unadjusted and multivariable-adjusted models (0.01 and 0.03, respectively). Multivariable-adjusted hazard ratios (HRs) for the effect of treatment indicated a progressive diminution of benefit with increasing CAC. Subgroup analyses were also conducted for clinically relevant CAC categories: those above and below an Agatston score of 100. Among those randomized to intensive treatment, for the subgroup with CAC >100, 11 of 62 individuals had events, while only 1 of 52 individuals with CAC ≤100 had an event. The multivariable HR for intensive treatment for those with CAC >100 was 0.74 (95% CI 0.46–1.20; P = 0.21), while for the subgroup with CAC ≤100, the corresponding HR was 0.08 (0.008–0.77; P = 0.03), with event rates of 39 and 4 per 1,000 person-years, respectively.

CONCLUSIONS

These data indicate that intensive glucose lowering reduces cardiovascular events in those with less extensive calcified coronary atherosclerosis.

Background

Impaired glucose tolerance (IGT) is a prediabetic state. If IGT can be prevented from progressing to overt diabetes, hyperglycemia-related complications can be avoided. The purpose of the present study was to examine whether pioglitazone (ACTOS®) can prevent progression of IGT to type 2 diabetes mellitus (T2DM) in a prospective randomized, double blind, placebo controlled trial.

Methods/Design

602 IGT subjects were identified with OGTT (2-hour plasma glucose = 140–199 mg/dl). In addition, IGT subjects were required to have FPG = 95–125 mg/dl and at least one other high risk characteristic. Prior to randomization all subjects had measurement of ankle-arm blood pressure, systolic/diastolic blood pressure, HbA1C, lipid profile and a subset had frequently sampled intravenous glucose tolerance test (FSIVGTT), DEXA, and ultrasound determination of carotid intima-media thickness (IMT). Following this, subjects were randomized to receive pioglitazone (45 mg/day) or placebo, and returned every 2–3 months for FPG determination and annually for OGTT. Repeat carotid IMT measurement was performed at 18 months and study end. Recruitment took place over 24 months, and subjects were followed for an additional 24 months. At study end (48 months) or at time of diagnosis of diabetes the OGTT, FSIVGTT, DEXA, carotid IMT, and all other measurements were repeated.

Primary endpoint is conversion of IGT to T2DM based upon FPG ≥ 126 or 2-hour PG ≥ 200 mg/dl. Secondary endpoints include whether pioglitazone can: (i) improve glycemic control (ii) enhance insulin sensitivity, (iii) augment beta cell function, (iv) improve risk factors for cardiovascular disease, (v) cause regression/slow progression of carotid IMT, (vi) revert newly diagnosed diabetes to normal glucose tolerance.

Conclusion

ACT NOW is designed to determine if pioglitazone can prevent/delay progression to diabetes in high risk IGT subjects, and to define the mechanisms (improved insulin sensitivity and/or enhanced beta cell function) via which pioglitazone exerts its beneficial effect on glucose metabolism to prevent/delay onset of T2DM.

Trial Registration

clinical trials.gov identifier: NCT00220961

Background

Many adverse effects of atypical antipsychotic treatment are associated with antagonism of monoamine receptors; however, data indicate that important metabolic effects, such as hypertriglyceridemia and impairment in glucose/insulin homeostasis, may not be related to these mechanisms, leading investigators to explore alternative hypotheses. Promising candidates include a possible impact of antipsychotics on peptide hormonal regulators of metabolic control such as leptin, ghrelin, and adiponectin. The purpose of this review is to summarize recent data on changes in these hormones during atypical antipsychotic treatment.

Methods

A Medline search was performed for papers published from January 1999 to January 2007 using key words antipsychotic, atypical antipsychotic, and individual atypical antipsychotic drug names cross-referenced with leptin, ghrelin, and adiponectin.

Results

The bulk of the published work focused on changes in body weight and serum leptin, with far less data on ghrelin, and adiponectin, and non-weight metabolic changes. Leptin changes were directly related to a medication’s weight gain liability, with no added antipsychotic effects on leptin signaling. Conflicting results emerged for the other markers, but all three long-term studies on ghrelin showed increased levels in patients on atypical antipsychotics with weight gain liabilities.

Conclusions

Leptin increases during antipsychotic treatment are a result of weight gain rather than a direct impact of atypical antipsychotics on leptin physiology. Preliminary long-term data show increased ghrelin levels, but this finding must be replicated. The association with antipsychotic effects on glucose and lipid metabolism and these hormones remains virtually unstudied. Future research should indicate whether ghrelin and other peptide hormones may be useful predictors of weight gain or metabolic changes in patients on antipsychotics.

Objective

The objective of this study was to determine inaccuracies of miscoded blood glucose (BG) meters and potential errors in insulin dose based on values from these meters.

Research Design

Fasting diabetic subjects at three clinical centers participated in a 2-hour meal tolerance test. At various times subjects' blood was tested on five BG meters and on a Yellow Springs Instruments laboratory glucose analyzer. Some meters were purposely miscoded. Using the BG values from these meters, along with three insulin dose algorithms, Monte Carlo simulations were conducted to generate ideal and simulated-meter glucose values and subsequent probability of insulin dose errors based on normal and empirical distribution assumptions.

Results

Maximal median percentage biases of miscoded meters were +29% and −37%, while maximal median percentage biases of correctly coded meters were only +0.64% and −10.45% (p = 0.000, χ2 test, df = 1). Using the low-dose algorithm and the normal distribution assumption, the combined data showed that the probability of insulin error of ±1U, ±2, ±3, ±4, and ±5U for miscoded meters could be as high as 49.6, 50.0, 22.3, 1.4, and 0.04%, respectively. This is compared to manually, correctly coded meters where the probability of error of ±1, ±2, and ±3U could be as high as 44.6, 7.1, and 0.49%, respectively. There was no instance of a ±4 or ±5U insulin dose error with a manually, correctly coded meter. For autocoded meters, the probability of ±1 and ±2U could be as high as 35.4 and 1.4%, respectively. For autocoded meters there were no calculated insulin dose errors above ±2U. The probability of insulin misdosing with either manually, correctly coded or autocoded meters was significantly lower than that with miscoded meters. Results using empirical distributions showed similar trends of insulin dose errors.

Conclusions

Blood glucose meter coding errors may result in significant insulin dosing errors. To avoid error, patients should be instructed to code their meters correctly or be advised to use an autocoded meter that showed superior performance over manually, correctly coded meters in this study.