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Zhang J, Zhao Q, Liu S, Yuan N, Hu Z. Clinical predictive value of the CRP-albumin-lymphocyte index for prognosis of critically ill patients with sepsis in intensive care unit: a retrospective single-center observational study. Front Public Health 2024; 12:1395134. [PMID: 38841671 PMCID: PMC11150768 DOI: 10.3389/fpubh.2024.1395134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2024] [Accepted: 05/06/2024] [Indexed: 06/07/2024] Open
Abstract
Background Sepsis is a complex syndrome characterized by physiological, pathological, and biochemical abnormalities caused by infection. Its development is influenced by factors such as inflammation, nutrition, and immune status. Therefore, we combined C-reactive protein (CRP), albumin, and lymphocyte, which could reflect above status, to be the CRP-albumin-lymphocyte (CALLY) index, and investigated its association with clinical prognosis of critically ill patients with sepsis. Methods This retrospective observational study enrolled critically ill patients with sepsis who had an initial CRP, albumin, and lymphocyte data on the first day of ICU admission. All data were obtained from the Affiliated Hospital of Jiangsu University. The patients were divided into quartiles (Q1-Q4) based on their CALLY index. The outcomes included 30-/60-day mortality and acute kidney injury (AKI) occurrence. The association between the CALLY index and these clinical outcomes in critically ill patients with sepsis was evaluated using Cox proportional hazards and logistic regression analysis. Results A total of 1,123 patients (63.0% male) were included in the study. The 30-day and 60-day mortality rates were found to be 28.1 and 33.4%, respectively, while the incidence of AKI was 45.6%. Kaplan-Meier analysis revealed a significant association between higher CALLY index and lower risk of 30-day and 60-day mortality (log-rank p < 0.001). Multivariate Cox proportional hazards analysis indicated that the CALLY index was independently associated with 30-day mortality [HR (95%CI): 0.965 (0.935-0.997); p = 0.030] and 60-day mortality [HR (95%CI): 0.969 (0.941-0.997); p = 0.032]. Additionally, the multivariate logistic regression model showed that the CALLY index served as an independent risk predictor for AKI occurrence [OR (95%CI): 0.982 (0.962-0.998); p = 0.033]. Conclusion The findings of this study indicated a significant association between the CALLY index and both 30-day and 60-day mortality, as well as the occurrence of AKI, in critically ill patients with sepsis. These findings suggested that the CALLY index may be a valuable tool in identifying sepsis patients who were at high risk for unfavorable outcomes.
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Affiliation(s)
- Jinhui Zhang
- Department of Critical Care Medicine, The Affiliated Hospital, Jiangsu University, Zhenjiang, Jiangsu, China
| | | | | | | | - Zhenkui Hu
- Department of Critical Care Medicine, The Affiliated Hospital, Jiangsu University, Zhenjiang, Jiangsu, China
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Chen Y, Gel YR, Marathe MV, Poor HV. A simplicial epidemic model for COVID-19 spread analysis. Proc Natl Acad Sci U S A 2024; 121:e2313171120. [PMID: 38147553 PMCID: PMC10769830 DOI: 10.1073/pnas.2313171120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Accepted: 11/11/2023] [Indexed: 12/28/2023] Open
Abstract
Networks allow us to describe a wide range of interaction phenomena that occur in complex systems arising in such diverse fields of knowledge as neuroscience, engineering, ecology, finance, and social sciences. Until very recently, the primary focus of network models and tools has been on describing the pairwise relationships between system entities. However, increasingly more studies indicate that polyadic or higher-order group relationships among multiple network entities may be the key toward better understanding of the intrinsic mechanisms behind the functionality of complex systems. Such group interactions can be, in turn, described in a holistic manner by simplicial complexes of graphs. Inspired by these recently emerging results on the utility of the simplicial geometry of complex networks for contagion propagation and armed with a large-scale synthetic social contact network (also known as a digital twin) of the population in the U.S. state of Virginia, in this paper, we aim to glean insights into the role of higher-order social interactions and the associated varying social group determinants on COVID-19 propagation and mitigation measures.
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Affiliation(s)
- Yuzhou Chen
- Department of Computer and Information Sciences, Temple University, Philadelphia, PA19122
| | - Yulia R. Gel
- Department of Mathematical Sciences, University of Texas at Dallas, Richardson, TX75080
- Division of Mathematical Sciences, NSF, Alexandria, VA22314
| | - Madhav V. Marathe
- Department of Computer Science, University of Virginia
- Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA22904
| | - H. Vincent Poor
- Department of Electrical and Computer Engineering, Princeton University, Princeton, NJ08544
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Jaros P, Ghosh S, Dudkowski D, Dana SK, Kapitaniak T. Higher-order interactions in Kuramoto oscillators with inertia. Phys Rev E 2023; 108:024215. [PMID: 37723775 DOI: 10.1103/physreve.108.024215] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 08/01/2023] [Indexed: 09/20/2023]
Abstract
How do higher-order interactions influence the dynamical landscape of a network of the second-order phase oscillators? We address this question using three coupled Kuramoto phase oscillators with inertia under pairwise and higher-order interactions, in search of various collective states, and new states, if any, that show marginal presence or absence under pairwise interactions. We explore this small network for varying phase lag in the coupling and over a range of negative to positive coupling strength of pairwise as well as higher-order or group interactions. In the extended coupling parameter plane of the network we record several well-known states such as synchronization, frequency chimera states, and rotating waves that appear with distinct boundaries. In the parameter space, we also find states generated by the influence of higher-order interactions: The 2+1 antipodal point and the 2+1 phase-locked states. Our results demonstrate the importantance of the choices of the phase lag and the sign of the higher-order coupling strength for the emergent dynamics of the network. We provide analytical support to our numerical results.
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Affiliation(s)
- Patrycja Jaros
- Division of Dynamics, Lodz University of Technology, Stefanowskiego 1/15, 90-924 Lodz, Poland
| | - Subrata Ghosh
- Division of Dynamics, Lodz University of Technology, Stefanowskiego 1/15, 90-924 Lodz, Poland
- Center for Computational Natural Sciences and Bioinformatics, International Institute of Information Technology, Gachibowli, Hyderabad 500032, India
| | - Dawid Dudkowski
- Division of Dynamics, Lodz University of Technology, Stefanowskiego 1/15, 90-924 Lodz, Poland
| | - Syamal K Dana
- Division of Dynamics, Lodz University of Technology, Stefanowskiego 1/15, 90-924 Lodz, Poland
- Department of Mathematics, National Institute of Technology, Durgapur 713209, India
| | - Tomasz Kapitaniak
- Division of Dynamics, Lodz University of Technology, Stefanowskiego 1/15, 90-924 Lodz, Poland
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Ghosh S, Khanra P, Kundu P, Ji P, Ghosh D, Hens C. Dimension reduction in higher-order contagious phenomena. CHAOS (WOODBURY, N.Y.) 2023; 33:2893033. [PMID: 37229635 DOI: 10.1063/5.0152959] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 05/01/2023] [Indexed: 05/27/2023]
Abstract
We investigate epidemic spreading in a deterministic susceptible-infected-susceptible model on uncorrelated heterogeneous networks with higher-order interactions. We provide a recipe for the construction of one-dimensional reduced model (resilience function) of the N-dimensional susceptible-infected-susceptible dynamics in the presence of higher-order interactions. Utilizing this reduction process, we are able to capture the microscopic and macroscopic behavior of infectious networks. We find that the microscopic state of nodes (fraction of stable healthy individual of each node) inversely scales with their degree, and it becomes diminished due to the presence of higher-order interactions. In this case, we analytically obtain that the macroscopic state of the system (fraction of infectious or healthy population) undergoes abrupt transition. Additionally, we quantify the network's resilience, i.e., how the topological changes affect the stable infected population. Finally, we provide an alternative framework of dimension reduction based on the spectral analysis of the network, which can identify the critical onset of the disease in the presence or absence of higher-order interactions. Both reduction methods can be extended for a large class of dynamical models.
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Affiliation(s)
- Subrata Ghosh
- Physics and Applied Mathematics Unit, Indian Statistical Institute, Kolkata 700108, India
| | - Pitambar Khanra
- Department of Mathematics, State University of New York at Buffalo, Buffalo, New York 14260, USA
| | - Prosenjit Kundu
- Dhirubhai Ambani Institute of Information and Communication Technology, Gandhinagar, Gujarat 382007, India
| | - Peng Ji
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai 200433, China
| | - Dibakar Ghosh
- Physics and Applied Mathematics Unit, Indian Statistical Institute, Kolkata 700108, India
| | - Chittaranjan Hens
- Physics and Applied Mathematics Unit, Indian Statistical Institute, Kolkata 700108, India
- International Institute of Information Technology, Hyderabad 500 032, India
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5
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Fan J, Zhao D, Xia C, Tanimoto J. Coupled spreading between information and epidemics on multiplex networks with simplicial complexes. CHAOS (WOODBURY, N.Y.) 2022; 32:113115. [PMID: 36456318 DOI: 10.1063/5.0125873] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Accepted: 10/10/2022] [Indexed: 06/17/2023]
Abstract
The way of information diffusion among individuals can be quite complicated, and it is not only limited to one type of communication, but also impacted by multiple channels. Meanwhile, it is easier for an agent to accept an idea once the proportion of their friends who take it goes beyond a specific threshold. Furthermore, in social networks, some higher-order structures, such as simplicial complexes and hypergraph, can describe more abundant and realistic phenomena. Therefore, based on the classical multiplex network model coupling the infectious disease with its relevant information, we propose a novel epidemic model, in which the lower layer represents the physical contact network depicting the epidemic dissemination, while the upper layer stands for the online social network picturing the diffusion of information. In particular, the upper layer is generated by random simplicial complexes, among which the herd-like threshold model is adopted to characterize the information diffusion, and the unaware-aware-unaware model is also considered simultaneously. Using the microscopic Markov chain approach, we analyze the epidemic threshold of the proposed epidemic model and further check the results with numerous Monte Carlo simulations. It is discovered that the threshold model based on the random simplicial complexes network may still cause abrupt transitions on the epidemic threshold. It is also found that simplicial complexes may greatly influence the epidemic size at a steady state.
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Affiliation(s)
- Junfeng Fan
- Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology, Tianjin University of Technology, Tianjin 300384, China
| | - Dawei Zhao
- Shandong Provincial Key Laboratory of Computer Networks, Shandong Computer Science Center (National Supercomputer Center in Jinan), Qilu University of Technology (Shandong Academy of Sciences), Jinan 250014, China
| | - Chengyi Xia
- School of Control Science and Engineering, Tiangong University, Tianjin 300387, China
| | - Jun Tanimoto
- Interdisciplinary Graduate School of Engineering Sciences, Kyushu University, Kasuga-koen, Kasuga-shi, Fukuoka 816-8580, Japan
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Li W, Nie Y, Li W, Chen X, Su S, Wang W. Two competing simplicial irreversible epidemics on simplicial complex. CHAOS (WOODBURY, N.Y.) 2022; 32:093135. [PMID: 36182379 DOI: 10.1063/5.0100315] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Accepted: 08/26/2022] [Indexed: 06/16/2023]
Abstract
Higher-order interactions have significant implications for the dynamics of competing epidemic spreads. In this paper, a competing spread model for two simplicial irreversible epidemics (i.e., susceptible-infected-removed epidemics) on higher-order networks is proposed. The simplicial complexes are based on synthetic (including homogeneous and heterogeneous) and real-world networks. The spread process of two epidemics is theoretically analyzed by extending the microscopic Markov chain approach. When the two epidemics have the same 2-simplex infection rate and the 1-simplex infection rate of epidemic A ( λ) is fixed at zero, an increase in the 1-simplex infection rate of epidemic B ( λ) causes a transition from continuous growth to sharp growth in the spread of epidemic B with λ. When λ > 0, the growth of epidemic B is always continuous. With the increase of λ, the outbreak threshold of epidemic B is delayed. When the difference in 1-simplex infection rates between the two epidemics reaches approximately three times, the stronger side obviously dominates. Otherwise, the coexistence of the two epidemics is always observed. When the 1-simplex infection rates are symmetrical, the increase in competition will accelerate the spread process and expand the spread area of both epidemics; when the 1-simplex infection rates are asymmetrical, the spread area of one epidemic increases with an increase in the 1-simplex infection rate from this epidemic while the other decreases. Finally, the influence of 2-simplex infection rates on the competing spread is discussed. An increase in 2-simplex infection rates leads to sharp growth in one of the epidemics.
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Affiliation(s)
- Wenjie Li
- School of Public Health and Management, Chongqing Medical University, Chongqing 400016, China
| | - Yanyi Nie
- School of Public Health and Management, Chongqing Medical University, Chongqing 400016, China
| | - Wenyao Li
- College of Computer Science, Sichuan University, Chengdu 610065, China
| | - Xiaolong Chen
- School of Computing and Artificial Intelligence, Southwestern University of Finance and Economics, Chengdu 611130, China
| | - Sheng Su
- School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu 611713, China
| | - Wei Wang
- School of Public Health and Management, Chongqing Medical University, Chongqing 400016, China
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7
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Leng H, Zhao Y, Luo J, Ye Y. Simplicial epidemic model with birth and death. CHAOS (WOODBURY, N.Y.) 2022; 32:093144. [PMID: 36182376 DOI: 10.1063/5.0092489] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Accepted: 08/29/2022] [Indexed: 06/16/2023]
Abstract
In this paper, we propose a simplicial susceptible-infected-susceptible (SIS) epidemic model with birth and death to describe epidemic spreading based on group interactions, accompanying with birth and death. The site-based evolutions are formulated by the quenched mean-field probability equations for each site, which is a high-dimensional differential system. To facilitate a theoretical analysis of the influence of system parameters on dynamics, we adopt the mean-field method for our model to reduce the dimension. As a consequence, it suggests that birth and death rates influence the existence and stability of equilibria, as well as the appearance of a bistable state (the coexistence of the stable disease-free and endemic states), which is then confirmed by extensive simulations on empirical and synthetic networks. Furthermore, we find that another type of the bistable state in which a stable periodic outbreak state coexists with a steady disease-free state also emerges when birth and death rates and other parameters satisfy the certain conditions. Finally, we illustrate how the birth and death rates shift the density of infected nodes in the stationary state and the outbreak threshold, which is also verified by sensitivity analysis for the proposed model.
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Affiliation(s)
- Hui Leng
- School of Science, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China
| | - Yi Zhao
- School of Science, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China
| | - Jianfeng Luo
- School of Science, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China
| | - Yong Ye
- School of Science, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China
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8
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Zheng Q, Shen J, Zhou L, Guan L. Turing pattern induced by the directed ER network and delay. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2022; 19:11854-11867. [PMID: 36653978 DOI: 10.3934/mbe.2022553] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Infectious diseases generally spread along with the asymmetry of social network propagation because the asymmetry of urban development and the prevention strategies often affect the direction of the movement. But the spreading mechanism of the epidemic remains to explore in the directed network. In this paper, the main effect of the directed network and delay on the dynamic behaviors of the epidemic is investigated. The algebraic expressions of Turing instability are given to show the role of the directed network in the spread of the epidemic, which overcomes the drawback that undirected networks cannot lead to the outbreaks of infectious diseases. Then, Hopf bifurcation is analyzed to illustrate the dynamic mechanism of the periodic outbreak, which is consistent with the transmission of COVID-19. Also, the discrepancy ratio between the imported and the exported is proposed to explain the importance of quarantine policies and the spread mechanism. Finally, the theoretical results are verified by numerical simulation.
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Affiliation(s)
- Qianqian Zheng
- School of Science, Xuchang University; Henan Joint International Research Laboratory of High Performance Computation for Complex Systems, Xuchang 461000, China
| | - Jianwei Shen
- School of Mathematics and Statistics, North China University of Water Resources and Electric Power, Zhengzhou 450046, China
| | - Lingli Zhou
- School of Mathematical Sciences, Soochow University, Suzhou 215006, China
| | - Linan Guan
- School of Mathematics and Statistics, North China University of Water Resources and Electric Power, Zhengzhou 450046, China
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9
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Wang H, Zhang HF, Zhu PC, Ma C. Interplay of simplicial awareness contagion and epidemic spreading on time-varying multiplex networks. CHAOS (WOODBURY, N.Y.) 2022; 32:083110. [PMID: 36049933 DOI: 10.1063/5.0099183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/15/2022] [Accepted: 07/14/2022] [Indexed: 06/15/2023]
Abstract
There has been growing interest in exploring the dynamical interplay of epidemic spreading and awareness diffusion within the multiplex network framework. Recent studies have demonstrated that pairwise interactions are not enough to characterize social contagion processes, but the complex mechanisms of influence and reinforcement should be considered. Meanwhile, the physical social interaction of individuals is not static but time-varying. Therefore, we propose a novel sUAU-tSIS model to characterize the interplay of simplicial awareness contagion and epidemic spreading on time-varying multiplex networks, in which one layer with 2-simplicial complexes is considered the virtual information layer to address the complex contagion mechanisms in awareness diffusion and the other layer with time-varying and memory effects is treated as the physical contact layer to mimic the temporal interaction pattern among population. The microscopic Markov chain approach based theoretical analysis is developed, and the epidemic threshold is also derived. The experimental results show that our theoretical method is in good agreement with the Monte Carlo simulations. Specifically, we find that the synergistic reinforcement mechanism coming from the group interactions promotes the diffusion of awareness, leading to the suppression of the spreading of epidemics. Furthermore, our results illustrate that the contact capacity of individuals, activity heterogeneity, and memory strength also play important roles in the two dynamics; interestingly, a crossover phenomenon can be observed when investigating the effects of activity heterogeneity and memory strength.
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Affiliation(s)
- Huan Wang
- The Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, School of Mathematical Science, Anhui University, Hefei 230601, China
| | - Hai-Feng Zhang
- The Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, School of Mathematical Science, Anhui University, Hefei 230601, China
| | - Pei-Can Zhu
- School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University (NWPU), Xi'an 710072, Shaanxi, China
| | - Chuang Ma
- School of Internet, Anhui University, Hefei 230601, China
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Maletić S, Andjelković M, Rajković M. Potential grouping of nodes induced by higher-order structures in complex networks. CHAOS (WOODBURY, N.Y.) 2021; 31:123115. [PMID: 34972312 DOI: 10.1063/5.0069444] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 11/18/2021] [Indexed: 06/14/2023]
Abstract
Complex networks display an organization of elements into nontrivial structures at versatile inherent scales, imposing challenges on a more complete understanding of their behavior. The interest of the research presented here is in the characterization of potential mesoscale structures as building blocks of generalized communities in complex networks, with an integrated property that goes beyond the pairwise collections of nodes. For this purpose, a simplicial complex is obtained from a mathematical graph, and indirectly from time series, producing the so-called clique complex from the complex network. As the higher-order organizational structures are naturally embedded in the hierarchical strata of a simplicial complex, the relationships between aggregation of nodes are stored in the higher-order combinatorial Laplacian. Based on the postulate that aggregation of nodes represents integrated configuration of information, the observability parameter is defined for the characterization of potential configurations, computed from the entries of the combinatorial Laplacian matrix. The framework introduced here is used to characterize nontrivial inherent organizational patterns embedded in two real-world complex networks and three complex networks obtained from heart rate time series recordings of three different subject's meditative states.
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Affiliation(s)
- Slobodan Maletić
- "VINČA" Institute of Nuclear Sciences, National Institute of the Republic of Serbia, University of Belgrade, Mike Alasa 12-14, 11351 Vinča, Belgrade, Serbia
| | - Miroslav Andjelković
- "VINČA" Institute of Nuclear Sciences, National Institute of the Republic of Serbia, University of Belgrade, Mike Alasa 12-14, 11351 Vinča, Belgrade, Serbia
| | - Milan Rajković
- "VINČA" Institute of Nuclear Sciences, National Institute of the Republic of Serbia, University of Belgrade, Mike Alasa 12-14, 11351 Vinča, Belgrade, Serbia
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