Sleep duration, baseline cardiovascular risk, inflammation and incident cardiovascular mortality in ambulatory U.S. Adults: National health and nutrition examination survey

Introduction: The interplay between sleep duration and inflammation on the baseline and incident cardiovascular (CV) risk is unknown. We sought to evaluate the association between sleep duration, C-reactive protein (CRP), baseline CV risk, and incident CV mortality. Methods: We used data from the National Health and Nutrition Examination Survey 2005-2010 linked with the cause of death data from the National Center for Health Statistics for adults aged ≥18 years. The associations between self-reported sleep duration and CRP, 10-year atherosclerotic CV disease risk score (ASCVD) and CV mortality were assessed using Linear, Poisson and Cox proportional hazard modeling as appropriate. Results: There were 17,635 eligible participants with a median age of 46 years (interquartile range [IQR] 31, 63). Among them, 51.3% were women and 46.9% were non-Hispanic Whites. Over a median follow-up of 7.5 years (IQR 6.0, 9.1), 350 CV deaths occurred at an incident rate of 2.7 per 1000-person years (IQR 2.4, 3.0). We observed a U-shaped associations between sleep duration and incident CV mortality rate (P-trend=0.011), sleep duration and 10-year ASCVD risk (P-trend \u3c0.001), as well as sleep duration and CRP (P-trend \u3c0.001). A self-reported sleep duration of 6-7 hours appeared most optimal. We observed that those participants who reported \u3c6 or \u3e7 hours of sleep had higher risk of CV death attributable to inflammation after accounting for confounders. Conclusions: There was a U-shaped relationship of incident CV mortality, 10-year ASCVD risk, and CRP with sleep duration. These findings suggest an interplay between sleep duration, inflammation, and CV risk

Relative Predictive Value of Circulating Immune Markers in US Adults Without Cardiovascular Disease: Implications for Risk Reclassification

OBJECTIVE: To investigate the relative predictive value of circulating immune cell markers for cardiovascular mortality in ambulatory adults without cardiovascular disease. METHODS: We analyzed data of participants enrolled in the National Health and Nutrition Examination Survey from January 1, 1999, to December 31, 2010, with the total leukocyte count within a normal range (4000-11,000 cells/μL [to convert to cells ×10 RESULTS: Among 21,599 participants eligible for this analysis, the median age was 47 years (interquartile range, 34-63 years); 10,651 (49.2%) participants were women, and 10,713 (49.5%) were self-reported non-Hispanic white. During a median follow-up of 9.6 years (interquartile range, 6.8-13.1 years), there were 627 cardiovascular deaths. MLR had the best predictive value for cardiovascular mortality. The addition of elevated MLR (≥0.3) to the 10-year ASCVD risk score improved the classification by 2.7%±1.4% (P=.04). Elevated MLR had better predictive value than C-reactive protein and several components of the 10-year ASCVD risk score. CONCLUSION: Among ambulatory US adults without preexisting cardiovascular disease, we found that MLR had the best predictive value for cardiovascular mortality among circulating immune markers. The addition of MLR to the 10-year risk score significantly improved the risk classification of participants

First Report of Field Resistance to Afidopyropen, the Novel Pyropene Insecticide, on Bemisia tabaci Mediterranean (Q Biotype) from China

Afidopyropen, a novel biopesticide, is derived from Aspergillus fumigatus, a fungus, and shows promise as a novel insecticidal agent for the management of the whitefly pest Bemisia tabaci in horticultural and economical crop production. In the present work, we monitored the susceptibilities of B. tabaci to afidopyropen in 18 field populations, sampled from 9 provinces of China, and found that, in comparison with the susceptible strain (MED-S), B. tabaci from most field populations were highly susceptible, except for the Haidian population (HD) which exhibited an approximately 40-fold increase in resistance. The HD population also displayed significant cross-resistance to sulfoxaflor (14.5-fold) but little cross-resistance to cyantraniliprole, flonicamid, imidacloprid, pymetrozine, and thiamethoxam. Afidopyropen resistance of the HD population was determined to be incomplete dominant and autosomal, and synergism assays demonstrated that P450 monooxygenases could contribute to the field-evolved afidopyropen resistance observed in the HD population. These results will further our understanding of the molecular underpinnings of insecticide resistance in B. tabaci and can inform the development of field-based pest control tactics to slow the development of afidopyropen resistance and to control whiteflies more sustainably

ASSOCIATION BETWEEN BASELINE CARDIOVASCULAR RISK AND SLEEP DURATION IN AMBULATORY US ADULTS: INSIGHTS FROM THE NATIONAL HEALTH AND NUTRITION EXAMINATION SURVEY

Background: Baseline CV risk may partially explain the significant variability in sleep duration across a population. We evaluated the association between baseline CV risk and self-reported sleep duration. Methods: We used data from National Health and Nutrition Examination Survey (NHANES) 2005-2010 and linked cause of death from National Center for Health Statistics for adults aged ≥18 years. The 10-year atherosclerotic CV disease risk score (ASCVD) was used to assess baseline CV risk and self-reported sleep duration was the outcome. We excluded participants with prevalent CV disease, defined as self-reported coronary artery disease, heart failure or stroke. Continuous variables were represented as medians with interquartile range (IQR). Non-linearity was accounted for using restricted cubic spline models. Results: There were 14,079 eligible participants. Mean age was 46±19 years with 52% women and 46% non-Hispanic Whites. The median 10-year ASCVD risk was 3.5% (0.5, 14.4). There was a U-shaped relationship with 10-year ASCVD risk score and the sleep duration such that participants with a sleep-duration of 6-7 hours had the lowest risk (P-trend\u3c0.001, Figure). The median 10-year ASCVD risk among participants with \u3c6, 6-7 and \u3e7 hours of sleep were 4.6% (0.9, 15.7), 3.3% (0.6, 12.3) and 3.3% (0.4, 17.3), respectively. Conclusion: Least 10-year ASCVD risk is associated with a self-reported sleep duration of 6-7 hours in ambulatory US adults without prevalent CV disease

Coronary flow abnormalities in chronic kidney disease: A systematic review and meta-analysis

BACKGROUND: Coronary vasomotion abnormalities have been described in small studies but not studied systematically. We aimed to review the present literature and analyze it to improve our understanding of chronic kidney disease (CKD) related-coronary microvascular dysfunction. OBJECTIVE: Coronary flow reserve (CFR) is a well-known measure of coronary vasomotion. We aimed to assess the difference in CFR among participants with and without CKD. METHODS: PubMed, Embase, and Cochrane CENTRAL were systematically reviewed to identify studies that compared CFR in participants with and without CKD. We estimated standardized mean differences in mean CFR reported in these studies. We performed subgroup analyses according to imaging modality, and the presence of significant epicardial coronary artery disease. RESULTS: In 14 observational studies with 5966 and 1410 patients with and without CKD, the mean estimated glomerular filtration rate (eGFR) was 29 ± 04 and 87 ± 25 ml/min/1.73 m2 , respectively. Mean CFR was consistently lower in patients with CKD in all studies and the cumulative mean difference was statistically significant (2.1 ± .3 vs. 2.7 ± .5, standardized mean difference -.8, 95% CI -1.1, -.6, p \u3c .05). The lower mean CFR was driven by both significantly higher mean resting flow velocity (.58 cm/s, 95% CI .17, .98) and lower mean stress flow velocity (-.94 cm/s, 95% CI -1.75, -.13) in studies with CKD. This difference remained significant across diagnostic modalities and even in absence of epicardial coronary artery disease. In meta-regression, there was a significant positive relationship between mean eGFR and mean CFR (p \u3c .05). CONCLUSION: Patients with CKD have a significantly lower CFR versus those without CKD, even in absence of epicardial coronary artery disease. There is a linear association between eGFR and CFR. Future studies are required to understand the mechanisms and therapeutic implications of these findings. KEY POINTS: In this meta-analysis of observational studies, there was a significant reduction in coronary flow reserve in studies with chronic kidney disease versus those without. This difference was seen even in absence of epicardial coronary artery disease. In meta-regression, a lower estimate glomerular filtration rate was a significant predictor of lower coronary flow reserve. Coronary microvascular dysfunction, rather than atherosclerosis-related epicardial disease may underly increase cardiovascular risk in a patient with chronic kidney disease

Data_Sheet_1_DeepHeartCT: A fully automatic artificial intelligence hybrid framework based on convolutional neural network and multi-atlas segmentation for multi-structure cardiac computed tomography angiography image segmentation.docx

Cardiac computed tomography angiography (CTA) is an emerging imaging modality for assessing coronary artery as well as various cardiovascular structures. Recently, deep learning (DL) methods have been successfully applied to many applications of medical image analysis including cardiac CTA structure segmentation. However, DL requires a large amounts of data and high-quality labels for training which can be burdensome to obtain due to its labor-intensive nature. In this study, we aim to develop a fully automatic artificial intelligence (AI) system, named DeepHeartCT, for accurate and rapid cardiac CTA segmentation based on DL. The proposed system was trained using a large clinical dataset with computer-generated labels to segment various cardiovascular structures including left and right ventricles (LV, RV), left and right atria (LA, RA), and LV myocardium (LVM). This new system was trained directly using high-quality computer labels generated from our previously developed multi-atlas based AI system. In addition, a reverse ranking strategy was proposed to assess the segmentation quality in the absence of manual reference labels. This strategy allowed the new framework to assemble optimal computer-generated labels from a large dataset for effective training of a deep convolutional neural network (CNN). A large clinical cardiac CTA studies (n = 1,064) were used to train and validate our framework. The trained model was then tested on another independent dataset with manual labels (n = 60). The Dice score, Hausdorff distance and mean surface distance were used to quantify the segmentation accuracy. The proposed DeepHeartCT framework yields a high median Dice score of 0.90 [interquartile range (IQR), 0.90–0.91], a low median Hausdorff distance of 7 mm (IQR, 4–15 mm) and a low mean surface distance of 0.80 mm (IQR, 0.57–1.29 mm) across all segmented structures. An additional experiment was conducted to evaluate the proposed DL-based AI framework trained with a small vs. large dataset. The results show our framework also performed well when trained on a small optimal training dataset (n = 110) with a significantly reduced training time. These results demonstrated that the proposed DeepHeartCT framework provides accurate and rapid cardiac CTA segmentation that can be readily generalized for handling large-scale medical imaging applications.</p

Effect of Eplontersen on Cardiac Structure and Function in Patients with Hereditary Transthyretin Amyloidosis

BACKGROUND: Hereditary transthyretin amyloidosis (ATTRv) is associated with polyneuropathy, cardiomyopathy, or both. The effects of eplontersen on cardiac structure and function were assessed. METHODS: NEURO-TTRansform was an open-label trial involving 144 adults with ATTRv polyneuropathy (49 patients (34%) with cardiomyopathy) receiving eplontersen throughout and compared to a historical placebo group (n=60, 30 patients (50%) with cardiomyopathy) from the NEURO-TTR trial at Week 65. Treatment effect (eplontersen vs placebo), presented as mean difference (95% confidence interval) was analyzed after adjusting for age, sex, region, baseline value, ATTRv disease stage, previous ATTRv treatment, and V30M transthyretin variant. RESULTS: There were notable differences at baseline between the eplontersen group and historical placebo. In the cardiomyopathy subgroup, 65 weeks of eplontersen treatment was associated with improvement from baseline relative to placebo in left ventricular ejection fraction (LVEF) 4.3% (1.40 to 21.01, p=0.049) and stroke volume 10.64 ml (3.99, 17.29, p=0.002) while the remainder of echocardiographic parameters remained stable. CONCLUSIONS: Eplontersen was associated with stable or improved measures of cardiac structure and function vs historical placebo in patients with ATTRv polyneuropathy and cardiomyopathy. Further investigation into eplontersen's effect on transthyretin amyloid cardiomyopathy is being conducted in the CARDIO-TTRansform trial