Lopez‐Jimenez, Francisco

Background: Decreased testosterone (TTST) and sex hormone binding globin (SHBG) contribute to development of cardiometabolic disorders in obese men. We aimed to determine the effect of weight gain and weight loss on TTST and SHBG in healthy men and to examine their relationship with endothelial function. Method: 25 normal weight healthy men underwent an overfeeding protocol to gain 5% body weight over 8 weeks. Following weight gain, they underwent 8 weeks of weight loss. TTST, SHBG and endothelial function (brachial artery flow‐mediated dilation, FMD) were measured at baseline (T1), after weight gain (T2) and after weight loss (T3). Results: Volunteers gained 4 ± 1.3 kg and subsequently lost 3.2 ± 1.5 kg of body weight. TTST levels did not change (T1: 18.85 ± 6.2 nmol/L, T2: 19.3 ± 6.9 nmol/L, T3: 20.3 ± 7.6 nmol/L). However, SHBG decreased during weight gain (p=0.04) and increased during weight loss (p=0.0005) (T1: 22.8 ± 10.5 nmol/L, T2: 20.8 ± 11.1 nmol/L, T3: 25.58 ± 11.5 nmol/L). Furthermore, SHBG reduction during weight gain tended to correlate with decreases in FMD (p=0.06; R 2 =0.15). During weight loss, increases in SHBG correlate negatively with changes in FMD (p=0.008; R 2 =0.32). Conclusion : In normal weight healthy men, SHBG decreases with modest weight gain and increases with weight loss. TTST does not change. Changes in SHBG partly predict improvements in endothelial function with weight loss. Grant Funding Source : Supported by AHA 11SDG7260046, R21 DK81014, AHA 13POST16420009

Abstract Background The term arterial stiffness (ArSt) describes the reduced capability of an artery to expand and contract in response to pressure changes and is recognized as an independent predictor of cardiovascular diseases (CVD). The evidence relating ArSt and triglycerides (TG) shows contradictory results. The aim of this paper is to assess the association between high TG and ArSt, using the cardio-ankle vascular index (CAVI).Methods Subjects aged between 25 and 64 years from a random population-based sample were evaluated between 2013–2016. Data from questionnaires, blood pressure, anthropometric measures and blood samples were collected to identify the metabolic syndrome (MetS). CAVI was measured using VaSera VS-1500N devise (Fukuda Denshi Co., Ltd., Japan). Subjects with history of CVD or chronic renal disease were excluded.Results 1934 participants, 44.7% males, were included. Median age was 48 (Interquartile Range [IQR] 19) years, TG levels were 1.05 (0.793) mmol/L, and CAVI 7.24 (1.43) points. Prevalence of high CAVI was 10.0% (14.5% in males and 6.4% in females; p < 0.001). Correlation between TG and CAVI was 0.136 (p < 0.001). High CAVI values were more prevalent among participants with MetS, high blood pressure, dysglycemia, abdominal obesity, and high total cholesterol. Using binary regression analysis, high TG were associated with high CAVI, even after adjustment for other MetS components, age, gender, smoking status and cholesterol (OR = 1.630, 95% CI = 1.061–2.505, p = 0.026).Conclusion TG levels were correlated with ArSt, measured as CAVI. High TG was associated with high CAVI independent of multiple cardiometabolic risk factors.

AbstractObjectivesWe sought to validate a deep learning algorithm designed to predict an ejection fraction (EF) less than or equal to 35% based on the 12‐lead electrocardiogram (ECG) in a large prospective cohort.BackgroundPatients undergoing routine ECG may have undetected left ventricular (LV) dysfunction that warrants further echocardiographic assessment. However, identification of these patients can be challenging.MethodsWe applied the algorithm to all ECGs interpreted by the Mayo Clinic ECG laboratory in September 2018. The performance of the algorithm was tested among patients with recent echocardiographic assessments of LV function. We also applied the algorithm in patients with no recent echocardiographic assessments of LV function to determine the rate of new “positive screens.”ResultsAmong 16 056 adult patients who underwent routine ECG, 8600 (age 67.1 ± 15.2 years, 45.6% male), had a transthoracic echocardiogram (TTE) and 3874 patients had a TTE and ECG less than 1 month apart. Among these patients, the algorithm was able to detect an EF less than or equal to 35% with 86.8% specificity, 82.5% sensitivity, and 86.5% accuracy, (area under the curve, 0.918). Among 474 “false‐positives screens,” 189 (39.8%) had an EF of 36% to 50%. Among patients with no prior TTE, the algorithm identified 3.5% of the patients with suspected EF less than or equal to 35%. Exploratory analysis suggests false positives could be reduced by assessing NT‐pro‐BNP after the initial “positive screen.”ConclusionsA deep learning algorithm detected depressed LV function with good accuracy in routine practice. Further studies are needed to validate the algorithm in patients with no prior echocardiogram and to assess the impact on echocardiography utilization, cost, and clinical outcomes.

Objectives To identify geriatric obesity interventions that can guide clinical recommendations. Design Systematic review using Medline (PubMed), Cochrane Central Register of Controlled Trials, Web of Science, CINAHL , EMBASE (Ovid), and Psyc INFO (Proquest) from January 1, 2005, to October 12, 2015, to identify English‐language randomized controlled trials. Participants Individuals aged 60 and older (mean age ≥65) and classified as having obesity (body mass index ≥30 kg/m 2 ). Interventions Behavioral weight loss interventions not involving pharmacological or procedural therapies lasting 6 months or longer. Measurements Two investigators performed the systematic review using the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses criteria and achieved a high concordance rate (97.3%) in summarizing the primary outcomes. The three primary outcomes were weight loss, physical performance, and quality of life. Results Of 5,741 citations, 19 were included. (Six studies were unique, and the remaining 13 were based on the same study population.) Duration ranged from 6 to 18 months (n = 405 participants, age range 66.7–71.1). Weight loss in the intervention groups ranged from 0.5 to 10.7 kg (0.1–9.3%). Five studies had a resistance exercise program accompanying a dietary component. Greater weight loss was observed in groups with a dietary component than those with exercise alone. Exercise alone led to better physical function but no significant weight loss. Combined dietary and exercise components led to the greatest improvement in physical performance measures and quality of life and mitigated reductions in muscle and bone mass observed in diet‐only study arms. Heterogeneous outcomes were observed, which limited the ability to synthesize the data quantitatively. Conclusions The evidence supporting geriatric obesity interventions to improve physical function and quality of life is of low to moderate quality. Well‐designed trials are needed in this population.

Abstract Aims Left ventricular systolic elastance (Ees) and diastolic elastance (Eed) correlate with arterial elastance (Ea), but it is unknown how chronic changes in arterial compliance and resistance, which determine Ea, might differentially affect cardiac properties with ageing. We sought to characterize chronic changes in pulsatile and resistive arterial load and correlate them with longitudinal changes in LV structure and function in a prospective, community-based study. Methods and results Comprehensive echocardiography was performed in 722 subjects participating in a randomly selected community-based study at two examinations separated by 4 years, allowing for assessment of LV Ees, Eed, and end-diastolic volume (EDV), Ea, total arterial compliance, and systemic vascular resistance at both examinations. Chronic changes in resistance and heart rate were the dominant contributors to change in Ea. Changes in arterial compliance had little impact on changes in Ea, but were strongly associated with changes in Ees. The combination of increased resistance and decreased compliance was associated with the largest increase in LV diastolic stiffness, an effect that was mediated by a decrease in LVEDV. In contrast, subjects with both improved arterial compliance and decreased resistance displayed an increase in LVEDV over time, with no increase in LV Eed. Conclusion Increases in pulsatile arterial load with ageing contribute more to LV systolic stiffening, while combined pulsatile and resistive loading changes are associated with positive and negative chamber remodelling and diastolic stiffness. Therapies designed to improve arterial resistance and particularly to enhance aortic compliance may hold promise to prevent or reverse cardiac ageing and its sequelae.

SummaryBackgroundThe ideal means of identifying obesity in children and adolescents has not been determined although body mass index (BMI) is the most widely used screening tool.ObjectiveWe performed a systematic review and meta‐analysis of studies assessing the diagnostic performance of BMI to detect adiposity in children up to 18 years.MethodsData sources were EMBASE, MEDLINE, Cochrane, Database of Systematic Reviews Cochrane CENTRAL, Web of Science and SCOPUS up to March 2013. Studies providing measures of diagnostic performance of BMI and using body composition technique for body fat percentage measurement were included.ResultsThirty‐seven eligible studies that evaluated 53 521 patients, with mean age ranging from 4 to 18 years were included in the meta‐analysis. Commonly used BMI cut‐offs for obesity showed pooled sensitivity to detect high adiposity of 0.73 (confidence interval [CI] 0.67–0.79), specificity of 0.93 (CI 0.88–0.96) and diagnostic odds ratio of 36.93 (CI 20.75–65.71). Males had lower sensitivity. Moderate heterogeneity was observed (I2 = 48%) explained in meta‐regression by differences across studies in race, BMI cut‐off, BMI reference criteria (Center for Disease Control vs. International Obesity Task Force) and reference standard method assessing adiposity.ConclusionBMI has high specificity but low sensitivity to detect excess adiposity and fails to identify over a quarter of children with excess body fat percentage.