Background : Hypertension and dyslipidemia are considered reversible risk factors for cardiovascular disease. The purpose of this study was to explore the impact of traditional and nontraditional blood lipid profiles ...Background : Hypertension and dyslipidemia are considered reversible risk factors for cardiovascular disease. The purpose of this study was to explore the impact of traditional and nontraditional blood lipid profiles on the risk of left ventricular hypertrophy(LVH) and to explore the superposition effect of dyslipidemia combined with hypertension.Methods : Data on 9134 participants(53.5 ±10.3 years old) from the Northeast China Rural Cardiovascular Health Study(NCRCHS) were statistically analyzed. The blood lipid profile was measured by total cholesterol(TC), low-density lipoprotein cholesterol(LDL-C), high-density lipoprotein cholesterol(HDL-C), total glyceride(TG), and calculated nontraditional blood lipid indices including non-HDL-C, atherosclerosis index(AI), TC/HDL-C, and residual cholesterol(RC).Results : After the adjustment of age and gender, the odds ratios(ORs) of LVH in patients with hypertension, high LDL-C, high non-HDL-C, high AI, and high TC/HDL-C were 3.97(3.31– 4.76), 1.27(1.02– 1.59), 1.21(1.04– 1.39), 1.33(1.15– 1.53), and 1.42(1.22– 1.65), respectively. After full adjustment of potential confounding factors, high AI and TC/HDL-C were associated with LVH rather than traditional blood lipid indices.The combination of hypertension and nontraditional dyslipidemia(defined by high AI and TC/HDL-C) was associated with the highest risk of LVH, especially in participants under 45 years of age. The risk was more significant in men, 5.09-fold and 6.24-fold,respectively, compared with 3.66-fold and 4.01-fold in women.Conclusions : People with dyslipidemia defined by nontraditional blood lipid indices(high AI and high TC/HDL-C) and hypertension were more likely to develop LVH.展开更多
With the fast-growing graphical user interface(GUI)development workload in the Internet industry,some work attempted to generate maintainable front-end code from GUI screenshots.It can be more suitable for using user ...With the fast-growing graphical user interface(GUI)development workload in the Internet industry,some work attempted to generate maintainable front-end code from GUI screenshots.It can be more suitable for using user interface(UI)design drafts that contain UI metadata.However,fragmented layers inevitably appear in the UI design drafts,which greatly reduces the quality of the generated code.None of the existing automated GUI techniques detects and merges the fragmented layers to improve the accessibility of generated code.In this paper,we propose UI layers merger(UILM),a vision-based method that can automatically detect and merge fragmented layers into UI components.Our UILM contains the merging area detector(MAD)and a layer merging algorithm.The MAD incorporates the boundary prior knowledge to accurately detect the boundaries of UI components.Then,the layer merging algorithm can search for the associated layers within the components’boundaries and merge them into a whole.We present a dynamic data augmentation approach to boost the performance of MAD.We also construct a large-scale UI dataset for training the MAD and testing the performance of UILM.Experimental results show that the proposed method outperforms the best baseline regarding merging area detection and achieves decent layer merging accuracy.A user study on a real application also confirms the effectiveness of our UILM.展开更多
文摘Background : Hypertension and dyslipidemia are considered reversible risk factors for cardiovascular disease. The purpose of this study was to explore the impact of traditional and nontraditional blood lipid profiles on the risk of left ventricular hypertrophy(LVH) and to explore the superposition effect of dyslipidemia combined with hypertension.Methods : Data on 9134 participants(53.5 ±10.3 years old) from the Northeast China Rural Cardiovascular Health Study(NCRCHS) were statistically analyzed. The blood lipid profile was measured by total cholesterol(TC), low-density lipoprotein cholesterol(LDL-C), high-density lipoprotein cholesterol(HDL-C), total glyceride(TG), and calculated nontraditional blood lipid indices including non-HDL-C, atherosclerosis index(AI), TC/HDL-C, and residual cholesterol(RC).Results : After the adjustment of age and gender, the odds ratios(ORs) of LVH in patients with hypertension, high LDL-C, high non-HDL-C, high AI, and high TC/HDL-C were 3.97(3.31– 4.76), 1.27(1.02– 1.59), 1.21(1.04– 1.39), 1.33(1.15– 1.53), and 1.42(1.22– 1.65), respectively. After full adjustment of potential confounding factors, high AI and TC/HDL-C were associated with LVH rather than traditional blood lipid indices.The combination of hypertension and nontraditional dyslipidemia(defined by high AI and TC/HDL-C) was associated with the highest risk of LVH, especially in participants under 45 years of age. The risk was more significant in men, 5.09-fold and 6.24-fold,respectively, compared with 3.66-fold and 4.01-fold in women.Conclusions : People with dyslipidemia defined by nontraditional blood lipid indices(high AI and high TC/HDL-C) and hypertension were more likely to develop LVH.
基金Project supported by the National Key R&D Program of China(No.2018AAA0100703)the National Natural Science Foundation of China(Nos.62006208 and 62107035)+1 种基金the Ng Teng Fong Charitable Foundation in the form of ZJU-SUTD IDEA Grantthe Alibaba-Zhejiang University Joint Research Institute of Frontier Technologies。
文摘With the fast-growing graphical user interface(GUI)development workload in the Internet industry,some work attempted to generate maintainable front-end code from GUI screenshots.It can be more suitable for using user interface(UI)design drafts that contain UI metadata.However,fragmented layers inevitably appear in the UI design drafts,which greatly reduces the quality of the generated code.None of the existing automated GUI techniques detects and merges the fragmented layers to improve the accessibility of generated code.In this paper,we propose UI layers merger(UILM),a vision-based method that can automatically detect and merge fragmented layers into UI components.Our UILM contains the merging area detector(MAD)and a layer merging algorithm.The MAD incorporates the boundary prior knowledge to accurately detect the boundaries of UI components.Then,the layer merging algorithm can search for the associated layers within the components’boundaries and merge them into a whole.We present a dynamic data augmentation approach to boost the performance of MAD.We also construct a large-scale UI dataset for training the MAD and testing the performance of UILM.Experimental results show that the proposed method outperforms the best baseline regarding merging area detection and achieves decent layer merging accuracy.A user study on a real application also confirms the effectiveness of our UILM.
