Background
Carotid ultrasound screening (CUS) has been recommended for cardiovascular disease (CVD) risk prediction; however, its effectiveness in clinical practice is unknown. The purpose of this study was to prospectively determine the effects of office-based CUS on physician decision-making and patient health-related behaviors (HRBs).
Methods
Physicians from 5 non-academic, community practices recruited patients ≥40 years old with ≥1 CVD risk factor. Abnormal carotid ultrasound screening (AbnlCUS) was defined as carotid intima-media thickness >75th percentile or carotid plaque presence. Subjects completed questionnaires before and immediately after CUS, then 30 days later to determine self-reported behavioral changes. Odds ratios (OR) for changes in physician management and patient HRBs were determined from multivariate hierarchical logistic regression models.
Results
There were 355 subjects (mean [standard deviation] 53.6 [7.9] years old, 2.3 [0.9] risk factors, 58% women); 266 (74.9%) had AbnlCUS. Presence of AbnlCUS altered physicians’ prescription of aspirin (p<0.001) and cholesterol medications (p<0.001). Immediately after CUS, subjects reported increased ability to change HRBs (p=0.002), regardless of their test results. Subjects with AbnlCUS reported increased CVD risk perception (OR 4.14, p<0.001), intentions to exercise (OR 2.28, p=0.008), make dietary changes (OR 2.95, p<0.001), and quit smoking (OR 4.98, p=0.022). After 30 days, 34% increased exercise frequency and 37% reported weight loss; but these changes were not predicted by the CUS results. AbnlCUS modestly predicted reduced dietary sodium (OR 1.45, p=0.002) and increased fiber (OR 1.55, p=0.022) intake.
Conclusions
Finding abnormal results on CUS had major effects on physician but not patient behaviors.
ObjectiveSerum α-hydroxybutyrate (α-HB) is elevated in insulin resistance and diabetes. We tested the hypothesis that the α-HB level predicts abnormal 1 h glucose levels and β-cell dysfunction inferred from plasma insulin kinetics during a 75 g oral glucose tolerance test (OGTT).Research design and methodsThis cross-sectional study included 217 patients at increased risk for diabetes. 75 g OGTTs were performed with multiple postload glucose and insulin measurements over a 30–120 min period. OGTT responses were analyzed by repeated measures analysis of variance (ANOVA). Multivariable logistic regression was used to predict 1 h glucose ≥155 mg/dL with α-HB added to traditional risk factors.ResultsMean±SD age was 51±15 years (44% male, 25% with impaired glucose tolerance). Fasting glucose and insulin levels, but not age or body mass index (BMI), were significantly higher in the second/third α-HB tertiles (>3.9 µg/mL) than in the first tertile. Patients in the second/third α-HB tertiles exhibited a higher glucose area under the receiver operating characteristics curve (AUC) and reduced initial slope of insulin response during OGTT. The AUC for predicting 1 h glucose ≥155 mg/dL was 0.82 for a base model that included age, gender, BMI, fasting glucose, glycated hemoglobin (HbA1c), and insulin, and increased to 0.86 with α-HB added (p=0.015), with a net reclassification index of 52% (p<0.0001).ConclusionsFasting serum α-HB levels predicted elevated 1 h glucose during OGTT, potentially due to impaired insulin secretion kinetics. This association persisted even in patients with an otherwise normal insulin–glucose homeostasis. Measuring serum α-HB could thus provide a rapid, inexpensive screening tool for detecting early subclinical hyperglycemia, β-cell dysfunction, and increased risk for diabetes.
The incidence of type 2 diabetes mellitus (T2DM) has reached epidemic levels, and current trends indicate that its prevalence will continue to rise. The development of T2DM can be delayed by several years, and may even be prevented, by identifying individuals at risk for T2DM and treating them with lifestyle modification and/or pharmacological therapies. There are a number of methods available for assessing the insulin resistance (IR) that characterizes, and is the precursor to, T2DM. However, current clinical methods for assessing IR, based on measures of plasma glucose and/or insulin are either laborious and time-consuming or show a low specificity. IR manifests its earliest measurable abnormalities through changes in lipoproteins, and thus we propose that by examining lipoprotein subclass profile, it may be possible to alert physicians and patients to a heightened risk of developing diabetes. This will allow us to institute appropriate lifestyle changes and treatment potentially to delay the onset or possibly prevent the progression to diabetes.
Discordance between apoB and LDL-PNMR in routine clinical practice is more widespread than currently recognized and may be associated with insulin resistance.
Blood-based biomarker testing of insulin resistance (IR) and beta cell dysfunction may identify diabetes risk earlier than current glycemia-based approaches. This retrospective cohort study assessed 1,687 US patients at risk for cardiovascular disease (CVD) under routine clinical care with a comprehensive panel of 19 biomarkers and derived factors related to IR, beta cell function, and glycemic control. The mean age was 53 ± 15, 42 % were male, and 25 % had glycemic indicators consistent with prediabetes. An additional 45 % of the patients who had normal glycemic indicators were identified with IR or beta cell abnormalities. After 5.3 months of median follow-up, significantly more patients had improved than worsened their glycemic status in the prediabetic category (35 vs. 9 %; P < 0.0001) and in the “high normal” category (HbA1c values of 5.5–5.6; 56 vs. 18 %, p < 0.0001). Biomarker testing can identify IR early, enable and inform treatment, and improve glycemic control in a high proportion of patients.Electronic supplementary materialThe online version of this article (doi:10.1007/s12265-014-9577-1) contains supplementary material, which is available to authorized users.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.