American society of echocardiography report. Clinical application of noninvasive vascular ultrasound in cardiovascular risk stratification: a report from the American Society of Echocardiography and the Society for Vascular Medicine and Biology

Noninvasive measures of atherosclerosis have emerged as adjuncts to standard cardiovascular disease (CVD) risk factors in an attempt to refine risk stratification and the need for more aggressive preventive strategies. Two such approaches, carotid artery imaging and brachial artery reactivity testing (BART), are ultrasound based. Numerous carotid artery imaging protocols have been used, and methodologic aspects are described in detail in this review. The panel recommends that protocols: (1) use end-diastolic (minimum dimension) images for intimal-medial thickness (IMT) measurements; (2) provide separate categorization of plaque presence and IMT; (3) avoid use of a single upper limit of normal for IMT because the measure varies with age, sex, and race; and (4) incorporate lumen measurement, particularly when serial measurements are performed to account for changes in distending pressure. Protocols may vary in the number of segments wherein IMT is measured, whether near wall is measured in addition to far wall, and whether IMT measurements are derived from B-mode or M-mode images, depending on the application. BART is a technique that requires meticulous attention to patient preparation and methodologic detail. Its application is substantially more challenging than is carotid imaging and remains largely a research technique that is not readily translated into routine clinical practice.     

Is serum copeptin a modifiable biomarker in autosomal dominant polycystic kidney disease?

The availability of disease-modifying drugs for the management of autosomal dominant polycystic kidney disease (ADPKD) has accelerated the need to accurately predict renal prognosis and/or treatment response in this condition. Arginine vasopressin (AVP) is a critical determinant of postnatal kidney cyst growth in ADPKD. Copeptin (the C-terminal glycoprotein of the precursor AVP peptide) is an accurate surrogate marker of AVP release that is stable and easily measured by immunoassay. Cohort studies show that serum copeptin is correlated with disease severity in ADPKD, and predicts future renal events [decline in renal function and increase in total kidney volume (TKV)]. However, serum copeptin is strongly correlated with creatinine, and its additional value as a prognostic biomarker over estimated glomerular filtration rate and TKV is not certain. It has also been suggested that copeptin could be a predictive biomarker to select ADPKD patients who are most likely to benefit from AVP-modifying therapies, but prospective data to validate this assumption are required. In this regard, long-term randomised clinical trials evaluating the effect of prescribed water intake on renal cyst growth may contribute to addressing this hypothesis. In conclusion, although serum copeptin is aligned with the basic pathogenesis of ADPKD, further rigorous studies are needed to define if it will contribute to enabling the delivery of personalised care in ADPKD.     

Can myocardial remodeling be a useful surrogate predictor of myocardial iron load? A 3D echocardiographic multicentric study

The relationship between myocardial iron load and eccentric myocardial remodeling remains an under‐investigated area; it was thought that remodeling is rather linked to fibrosis. This study aims to determine whether or not measures of remodeling can be used as predictors of myocardial iron. For this purpose, 60 patients with thalassemia were studied with 3D echocardiography and myocardial relaxometry (T2*) by Cardiac MRI. 3D derived sphericity index was significantly higher in patients with myocardial iron load. It was correlated with T2* with a 100% sensitivity and specificity (cut‐off value of 0.34) to discriminate between patients with and without myocardial iron overload.     

Cerebral Small Vessel Disease Burden and All-Cause Mortality: Mayo Clinic Florida Familial Cerebrovascular Diseases Registry

Goal: Cerebral small vessel disease (CSVD) leads to cognitive decline, gait disturbances, mood changes, and an increased risk of stroke. The goal of this study is to describe the relationship between a composite radiographic CSVD score and all-cause mortality. Materials and Methods: Data were collected from a prospective registry of patients with and without cerebrovascular disease from November 2010 through April 2018. The radiographic Total CSVD Score (tSVD) ranges from 0 (minimal disease) to 4 (severe disease), based on detection of lacunar infarcts, cerebral microbleeds, perivascular spaces, and subcortical or periventricular white matter hyperintensities. All-cause mortality served as the primary endpoint. The independent relationship between CSVD burden and all-cause mortality was assessed using Cox regression models with significance being P < .05. Findings: Four hundred and forty-nine patients were included (mean age, 63 years; 50.1% [225 of 449] women). The hazard ratio for mortality significantly increased with advancing score (1.92, P = .014 score 1; 2.92, P < .001 score 2; 4.23, P < .001 combined scores 3 and 4). Significance remained despite adjustment for coexistent cerebrovascular risk factors aside from age. Conclusions: The clinically practical tSVD score may serve as a predictor for all-cause mortality in populations with high disease prevalence. Continued investigations are needed to better understand the effects of risk factor modification on mortality and pathogenesis with the goal of developing disease modifying therapies.     

Interval estimation of risk difference for data sampled from clusters

Risk difference (RD) is an important measure in epidemiological studies where the probability of developing a disease for individuals in an exposed group, for example, is compared with that in a control group. There are varying cluster sizes in each group and the binary responses within each cluster cannot be assumed independent. Under the cluster sampling scenario, Lui (Statistical Estimation of Epidemiological Risk. Wiley: CA, 2004; 7-27) discusses four methods for the construction of a confidence interval for the RD. In this paper we introduce two very simple methods. One method is based on an estimator of the variance of a ratio estimator (Sampling Techniques (3rd edn). Wiley: New York, 1977; 30-67) and the other method is based on a sandwich estimator of the variance of the regression estimator using the generalized estimating equations approach of Zeger and Liang (Biometrics 1986; 42:121-130). These two methods are then compared, by simulation, in terms of maintaining nominal coverage probability and average coverage length, with the four methods discussed by Lui (Statistical Estimation of Epidemiological Risk. Wiley: CA, 2004; 7-27). Simulations show at least as good properties of these two methods as those of the others. The method based on an estimate of the variance of a ratio estimator performs best overall. It involves a very simple variance expression and can be implemented with a very few computer codes. Therefore, it can be considered as an easily implementable alternative.