Background Heart failure is a significant problem leading to repeated hospitalizations. Telemonitoring and hemodynamic monitoring have demonstrated success in reducing hospitalization rates, but not all studies report...Background Heart failure is a significant problem leading to repeated hospitalizations. Telemonitoring and hemodynamic monitoring have demonstrated success in reducing hospitalization rates, but not all studies reported significant effects. The aim of this systematic review and meta-analysis is to examine the effectiveness of telemonitoring and wireless hemodynamic monitoring devices in reducing hospitalizations in heart failure. Methods ＆ Results PubMed and Cochrane Library were searched up to 1st May 2017 for articles that investigated the effects of telemonitoring or hemodynamic monitoring on hospitalization rates in heart failure. In 31,501 patients （mean age： 68 ± 12 years; 61% male; follow-up 11 ± 8 months）, telemonitoring reduced hospitalization rates with a HR of 0.73 （95% CI： 0.65-0.83; P 〈 0.0001） with significant heterogeneity （I2 = 94%）. These effects were observed in the short-term （≤ 6 months： HR = 0.77, 95% CI： 0.65-0.89; P 〈 0.01） and long-term （≥ 12 months： HR = 0.73, 95% CI： 0.62-0.87; P 〈 0.0001）. In 4831 patients （mean age 66 ± 18 years; 66% male; follow-up 13 ± 4 months）, wireless hemodynamic monitoring also reduced hospitalization rates with a HR of 0.60 （95% CI： 0.53-0.69; P 〈 0.001） with significant heterogeneity （I2 = 64%）.This reduction was observed both in the short-term （HR = 0.55, 95% CI： 0.45-0.68; P 〈 0.001; I2 = 72%） and long-term （HR = 0.64, 95% CI： 0.57-0.72; P 〈 0.001; I2 = 55%）. Conclusions Telemonitoring and hemodynamic monitoring reduce hospitalization in both short- and long-term in heart failure patients展开更多
A long-term common belief in complex networks is that,the most connected nodes are the most efficient spreaders.However,recent investigations on real-world complex networks show that the most influential spreaders are...A long-term common belief in complex networks is that,the most connected nodes are the most efficient spreaders.However,recent investigations on real-world complex networks show that the most influential spreaders are those with the highest fc-shell values.It is well-known that,many real-world complex networks have scale free(SF),small world(SW) properties,therefore,identification of influential spreaders in general artificial SF,SW as well as random networks will be more appealing.This research finds that,for artificial ER and SW networks,degree is more reliable than fc-shell in predicting the outcome of spreading.However,for artificial SF networks,fc-shell is remarkably reliable than degree and betweeness,which indicate that the four recently investigated real-world networks[Kitsak M,Gallos L K,Havlin S,Liljeros F,Muchnik L,Stanley H E,Makse H A,Identification of influential spreaders in complex networks,Nat.Phys.,2010,6:888-893.]are more similar to scale free ones.Moreover,the investigations also indicate us an optimal dissemination strategy in networks with scale free property.That is,starting from moderate-degree-nodes will be ok and even more economical,since one can derive roughly similar outcome with starting from hubs.展开更多
There are a lot of continuous evolving networks in real world, such as Internet, WWW network, etc. The evolving operation of these networks are not an equating interval of time by chance. In this paper, the author pro...There are a lot of continuous evolving networks in real world, such as Internet, WWW network, etc. The evolving operation of these networks are not an equating interval of time by chance. In this paper, the author proposes a new mathematical model for the mechanism of continuous single preferential attachment on the scale free networks, and counts the distribution of degree using stochastic analysis. Namely, the author has established the random continuous model of the network evolution of which counting process determines the operating number, and has proved that this system self-organizes into scale-free structures with scaling exponent γ=3＋a/m.展开更多
Information sharing is a critical task for group-living animals. The pattern of sharing can be modeled as a network whose structure can affect the decision-making performance of individual members as well as that of t...Information sharing is a critical task for group-living animals. The pattern of sharing can be modeled as a network whose structure can affect the decision-making performance of individual members as well as that of the group as a whole. A fully connected network, in which each member can directly transfer information to all other members, ensures rapid sharing of important information, such as a promising foraging location. However, it can also impose costs by amplifying the spread of inaccur- ate information （if, for example the foraging location is actually not profitable）. Thus, an optimal net- work structure should balance effective sharing of current knowledge with opportunities to discover new information. We used a computer simulation to measure how well groups characterized by dif- ferent network structures （fully connected, small world, lattice, and random） find and exploit resource peaks in a variable environment. We found that a fully connected network outperformed other struc- tures when resource quality was predictable. When resource quality showed random variation, however, the small world network was better than the fully connected one at avoiding extremely poor outcomes. These results suggest that animal groups may benefit by adjusting their informa- tion-sharing network structures depending on the noisiness of their environment.展开更多
文摘Background Heart failure is a significant problem leading to repeated hospitalizations. Telemonitoring and hemodynamic monitoring have demonstrated success in reducing hospitalization rates, but not all studies reported significant effects. The aim of this systematic review and meta-analysis is to examine the effectiveness of telemonitoring and wireless hemodynamic monitoring devices in reducing hospitalizations in heart failure. Methods ＆ Results PubMed and Cochrane Library were searched up to 1st May 2017 for articles that investigated the effects of telemonitoring or hemodynamic monitoring on hospitalization rates in heart failure. In 31,501 patients （mean age： 68 ± 12 years; 61% male; follow-up 11 ± 8 months）, telemonitoring reduced hospitalization rates with a HR of 0.73 （95% CI： 0.65-0.83; P 〈 0.0001） with significant heterogeneity （I2 = 94%）. These effects were observed in the short-term （≤ 6 months： HR = 0.77, 95% CI： 0.65-0.89; P 〈 0.01） and long-term （≥ 12 months： HR = 0.73, 95% CI： 0.62-0.87; P 〈 0.0001）. In 4831 patients （mean age 66 ± 18 years; 66% male; follow-up 13 ± 4 months）, wireless hemodynamic monitoring also reduced hospitalization rates with a HR of 0.60 （95% CI： 0.53-0.69; P 〈 0.001） with significant heterogeneity （I2 = 64%）.This reduction was observed both in the short-term （HR = 0.55, 95% CI： 0.45-0.68; P 〈 0.001; I2 = 72%） and long-term （HR = 0.64, 95% CI： 0.57-0.72; P 〈 0.001; I2 = 55%）. Conclusions Telemonitoring and hemodynamic monitoring reduce hospitalization in both short- and long-term in heart failure patients
基金supported by the National Natural Science Foundation of China under Grant Nos.11172215,61304151,61174028China-Australia Health and HIV/AIDS Facility(FA36 EID101)the Science Foundation of Henan University under Grant No.2012YBZR007
文摘A long-term common belief in complex networks is that,the most connected nodes are the most efficient spreaders.However,recent investigations on real-world complex networks show that the most influential spreaders are those with the highest fc-shell values.It is well-known that,many real-world complex networks have scale free(SF),small world(SW) properties,therefore,identification of influential spreaders in general artificial SF,SW as well as random networks will be more appealing.This research finds that,for artificial ER and SW networks,degree is more reliable than fc-shell in predicting the outcome of spreading.However,for artificial SF networks,fc-shell is remarkably reliable than degree and betweeness,which indicate that the four recently investigated real-world networks[Kitsak M,Gallos L K,Havlin S,Liljeros F,Muchnik L,Stanley H E,Makse H A,Identification of influential spreaders in complex networks,Nat.Phys.,2010,6:888-893.]are more similar to scale free ones.Moreover,the investigations also indicate us an optimal dissemination strategy in networks with scale free property.That is,starting from moderate-degree-nodes will be ok and even more economical,since one can derive roughly similar outcome with starting from hubs.
基金This research is supported by the National Natural Science Foundation of China under Grant No. 10671197.
文摘There are a lot of continuous evolving networks in real world, such as Internet, WWW network, etc. The evolving operation of these networks are not an equating interval of time by chance. In this paper, the author proposes a new mathematical model for the mechanism of continuous single preferential attachment on the scale free networks, and counts the distribution of degree using stochastic analysis. Namely, the author has established the random continuous model of the network evolution of which counting process determines the operating number, and has proved that this system self-organizes into scale-free structures with scaling exponent γ=3＋a/m.
文摘Information sharing is a critical task for group-living animals. The pattern of sharing can be modeled as a network whose structure can affect the decision-making performance of individual members as well as that of the group as a whole. A fully connected network, in which each member can directly transfer information to all other members, ensures rapid sharing of important information, such as a promising foraging location. However, it can also impose costs by amplifying the spread of inaccur- ate information （if, for example the foraging location is actually not profitable）. Thus, an optimal net- work structure should balance effective sharing of current knowledge with opportunities to discover new information. We used a computer simulation to measure how well groups characterized by dif- ferent network structures （fully connected, small world, lattice, and random） find and exploit resource peaks in a variable environment. We found that a fully connected network outperformed other struc- tures when resource quality was predictable. When resource quality showed random variation, however, the small world network was better than the fully connected one at avoiding extremely poor outcomes. These results suggest that animal groups may benefit by adjusting their informa- tion-sharing network structures depending on the noisiness of their environment.
