Sodium-glucose cotransporter 2 inhibitor effects on heart failure hospitalization and cardiac function: systematic review

Aims: To systematically review randomized controlled trials assessing effects of sodium–glucose cotransporter 2 inhibitors (SGLT2is) on hospitalization for heart failure (HHF) and cardiac structure/function and explore randomized controlled trial (RCT)-derived evidence for SGLT2i efficacy mechanisms in heart failure (HF). Methods and results: Systematic searches of Medline and Embase were performed. In seven trials [3730–17 160 patients; low risk of bias (RoB)], SGLT2is significantly reduced the relative risk of HHF by 27–39% vs. placebo, including in two studies in patients with HF with reduced ejection fraction with or without type-2 diabetes mellitus (T2DM). Improvements in conventional cardiovascular risk factors, including glycaemic levels, cannot account for these effects. Five trials (56–105 patients; low RoB) assessed the effects of 6–12 months of SGLT2i treatment on left ventricular structure/function; four reported significant improvements vs. placebo, and one did not. Five trials (low RoB) assessed SGLT2i treatment effects on serum N-terminal pro B-type natriuretic peptide levels; significant reductions vs. placebo were reported after 8–12 months (two studies; 3730–4744 patients) but not ≤12 weeks (three studies; 80–263 patients). Limited available RCT-derived evidence suggests various possible cardioprotective SGLT2i mechanisms, including improved haemodynamics (natriuresis and reduced interstitial fluid without blood volume contraction/neurohormonal activation) and vascular function, enhanced erythropoiesis, reduced tissue sodium and epicardial fat/inflammation, decreased sympathetic tone, and beneficial changes in cellular energetics. Conclusions: Sodium–glucose cotransporter 2 inhibitors reduce HHF regardless of T2DM status, and reversal of adverse left ventricular remodelling likely contributes to this efficacy. Hypothesis-driven mechanistic trials remain sparse, although numerous trials are planned or ongoing

Systematic review of the effects of sodium-glucose cotransporter 2 inhibitors on hospitalization for heart failure and cardiac structure or function, and exploratory assessment of potential mechanisms

In the past 5 years, there has been a profound shift in the therapeutic focus of trials of sodium-glucose cotransporter 2 inhibitors (SGLT2is). Although initially explored and introduced as glucose-lowering agents for patients with type 2 diabetes mellitus (T2DM), 1 clinical investigation of these molecules has evolved towards heart failure (HF) and chronic kidney disease (CKD) outcomes in patients with and without T2DM. We systematically reviewed randomized controlled trial (RCT) data assessing the effects of SGLT2 is compared with placebo on hospitalization for HF (HHF), cardiac structure and cardiac function, in a PRISMA-compliant manner. We also reviewed, in an exploratory manner, mechanistic evidence for how SGLT2 is may exert their benefits

Strong genetic influences on the stability of autistic traits in childhood

Objective: Disorders on the autism spectrum, as well as autistic traits in the general population, have been found to be both highly stable across age and highly heritable at individual ages. However, little is known about the overlap in genetic and environmental influences on autistic traits across age and the contribution of such influences to trait stability itself. The present study investigated these questions in a general population sample of twins. Method: More than 6,000 twin pairs were rated on an established scale of autistic traits by their parents at 8, 9, and 12 years of age and by their teachers at 9 and 12 years of age. Data were analyzed using structural equation modeling. Results: The results indicated that, consistently across raters, not only were autistic traits stable, and moderately to highly heritable at individual ages, there was also a high degree of overlap in genetic influences across age. Furthermore, autistic trait stability could largely be accounted for by genetic factors, with the environment unique to each twin playing a minor role. The environment shared by twins had virtually no effect on the longitudinal stability in autistic traits. Conclusions: Autistic traits are highly stable across middle childhood and this stability is caused primarily by genetic factors

Housing Stakeholder Preferences for the "Soft" Features of Sustainable and Healthy Housing Design in the UK.

It is widely recognised that the quantity and sustainability of new homes in the UK need to increase. However, it is important that sustainable housing is regarded holistically, and not merely in environmental terms, and incorporates elements that enhance the quality of life, health and well-being of its users. This paper focuses on the "soft" features of sustainable housing, that is, the non-technological components of sustainable housing and neighbourhood design that can impact occupants' health and well-being. Aims of the study are to ascertain the relative level of importance that key housing stakeholders attach to these features and to investigate whether the opinions of housing users and housing providers are aligned with regards to their importance. An online survey was carried out to gauge the level of importance that the key stakeholders, such as housing users, local authorities, housing associations, and developers (n = 235), attach to these features. Results revealed that while suitable indoor space was the feature regarded as most important by all stakeholders, there were also a number of disparities in opinion between housing users and housing providers (and among the different types of providers). This implies a scope for initiatives to achieve a better alignment between housing users and providers

A framework for power analysis using a structural equation modelling procedure

BACKGROUND: This paper demonstrates how structural equation modelling (SEM) can be used as a tool to aid in carrying out power analyses. For many complex multivariate designs that are increasingly being employed, power analyses can be difficult to carry out, because the software available lacks sufficient flexibility. Satorra and Saris developed a method for estimating the power of the likelihood ratio test for structural equation models. Whilst the Satorra and Saris approach is familiar to researchers who use the structural equation modelling approach, it is less well known amongst other researchers. The SEM approach can be equivalent to other multivariate statistical tests, and therefore the Satorra and Saris approach to power analysis can be used. METHODS: The covariance matrix, along with a vector of means, relating to the alternative hypothesis is generated. This represents the hypothesised population effects. A model (representing the null hypothesis) is then tested in a structural equation model, using the population parameters as input. An analysis based on the chi-square of this model can provide estimates of the sample size required for different levels of power to reject the null hypothesis. CONCLUSIONS: The SEM based power analysis approach may prove useful for researchers designing research in the health and medical spheres

Benefits for Type 2 Diabetes of Interrupting Prolonged Sitting With Brief Bouts of Light Walking or Simple Resistance Activities

OBJECTIVE To determine whether interrupting prolonged sitting with brief bouts of light-intensity walking (LW) or simple resistance activities (SRA) improves postprandial cardiometabolic risk markers in adults with type 2 diabetes (T2D). RESEARCH DESIGN AND METHODS In a randomized crossover trial, 24 inactive overweight/obese adults with T2D (14 men 62 ± 6 years old) underwent the following 8-h conditions on three separate days (with 6–14 days washout): uninterrupted sitting (control) (SIT), sitting plus 3-min bouts of LW (3.2 km · h−1) every 30 min, and sitting plus 3-min bouts of SRA (half-squats, calf raises, gluteal contractions, and knee raises) every 30 min. Standardized meals were consumed during each condition. Incremental areas under the curve (iAUCs) for glucose, insulin, C-peptide, and triglycerides were compared between conditions. RESULTS Compared with SIT, both activity-break conditions significantly attenuated iAUCs for glucose (SIT mean 24.2 mmol · h · L−1 [95% CI 20.4–28.0] vs. LW 14.8 [11.0–18.6] and SRA 14.7 [10.9–18.5]), insulin (SIT 3,293 pmol · h · L−1 [2,887–3,700] vs. LW 2,104 [1,696–2,511] and SRA 2,066 [1,660–2,473]), and C-peptide (SIT 15,641 pmol · h · L−1 [14,353–16,929] vs. LW 11,504 [10,209–12,799] and SRA 11,012 [9,723–12,301]) (all P < 0.001). The iAUC for triglycerides was significantly attenuated for SRA (P < 0.001) but not for LW (SIT 4.8 mmol · h · L−1 [3.6–6.0] vs. LW 4.0 [2.8–5.1] and SRA 2.9 [1.7–4.1]). CONCLUSIONS Interrupting prolonged sitting with brief bouts of LW or SRA attenuates acute postprandial glucose, insulin, C-peptide, and triglyceride responses in adults with T2D. With poor adherence to structured exercise, this approach is potentially beneficial and practical

Is there a female protective effect against ADHD? Evidence from two representative twin samples

OBJECTIVE: Attention-deficit/hyperactivity disorder (ADHD) is more frequent in males than females. The ‘female protective effect’ posits that females undergo greater exposure to etiological factors than males in order to develop ADHD, leading to the prediction that relatives of females with ADHD will display more ADHD behaviors. We thus tested whether co-twins of females displaying extreme ADHD traits would display more ADHD traits than co-twins of males displaying extreme ADHD traits. METHOD: Parents of approximately 7,000 pairs of non-identical twins in Sweden, and around 4,000 pairs of twins in England and Wales, completed dimensional assessments of ADHD traits. Probands were selected on the basis of scoring within the highest 10% of the distribution in each sample. Dimensional scores of co-twins of probands, as well as the categorical recurrence rate, were investigated by proband sex. RESULTS: Co-twins of female probands displayed higher mean ADHD trait scores (x ̅=0.62-0.79) than co-twins of male probands (x ̅=0.38-0.55) in both samples. This trend was significant in the Swedish sample (p<.01) and when the two samples were merged into a single, larger sample (p<.001). When the samples were merged, there was also a significant association between proband sex and co-twin’s categorical status, with more co-twins of female probands also being probands than co-twins of male probands. CONCLUSIONS: These findings support a female protective effect against ADHD behaviors, suggesting that females require greater exposure to genetic and environmental factors associated with ADHD in order to develop the condition

Hierarchical regression analysis in structural Equation Modeling

In a hierarchical or fixed-order regression analysis, the independent variables are entered into the regression equation in a prespecified order. Such an analysis is often performed when the extra amount of variance accounted for in a dependent variable by a specific independent variable is the main focus of interest (e.g., Cohen & Cohen, 1983). For example, in the area of reading achievement, there is a general interest in the specific abilities that predict reading development. Because these specific abilities are often correlated with more general abilities, such as verbal intelligence, the latter abilities are controlled for first (e.g., Wagner, Torgesen, & Rashotte, 1994). An additional reason for performing a hierarchical regression analysis is that, in these research applications, as well as in many others, the independent variables are often highly correlated. When correlated independent variables are included simultaneously in the regression model, multicollinearity arises (Cohen & Cohen, 1983). Though regularly used with observed variables, hierarchical regression analysis has not been performed with latent variables. In most applications of structural equation modeling (SEM), the latent predictors have been entered simultaneously into the regression model, although in several cases hierarchical regression analysis would have been the more appropriate approach (e.g., Guthrie et al., 1998; Normandeau & Guay, 1998; Wagner et al., 1994; Wagner et al., 1997). In this article we describe how a hierarchical regression analysis may be conducted in SEM. The main procedure proposed is to perform a Cholesky or triangular decomposition of the intercorrelations among the latent predictors (Harman, 1976; Loehlin, 1996). First the procedure is described and then an example of a hierarchical regression analysis with latent variables is given. Copyright © 1999, Lawrence Erlbaum Associates, Inc

The Association between Conduct Problems and the Initiation and Progression of Marijuana Use during Adolescence: A Genetic Analysis across Time

The present study used a prospective, longitudinal design to investigate genetic and environmental influences on the association between earlier conduct problems and the initiation and progression of marijuana use during adolescence. Parent- and teacher-reported conduct problems assessed at Time 1 (1996) and self-reported marijuana use assessed at Time 2 (2004) were available for 1088 adolescent twin pairs participating in the Cardiff Study of All Wales and North West of England Twins (CaStANET). Using a novel approach to the modeling of initiation and progression dimensions in substance use, findings suggested that the initiation of marijuana use in adolescence was influenced by genetic, common and unique environmental factors. The progression (or frequency) of marijuana use was influenced by genetic and unique environmental factors. Findings for conduct problems indicated that while the presence or absence of conduct problems was largely heritable, the relative severity of conduct problems appeared to be more strongly environmentally influenced. Multivariate model fitting indicated that conduct problems in childhood and early adolescence made a small but significant contribution to the risk for marijuana use 8 years later