ABSTRACT
Background: Delayed door-to-balloon (DTB) time and deterioration of inhospital mortality during the coronavirus disease 2019 (COVID-19) pandemic have been reported. Little is known about the impact of changes in in-hospital medical management before primary percutaneous coronary intervention (PCI) for COVID-19 such as screening test (antigen or polymerase chain reaction (PCR) tests, chest CT for excluding the pneumoniae) and primary PCI under full personal protective equipment (PPE) on DTB time and in-hospital mortality. Purpose(s): The purpose of this study was to evaluate the impact of inhospital medical management for COVID-19 on DTB time and in-hospital mortality during COVID-19 pandemic period. Method(s): We compared DTB time and in-hospital mortality of 502 STelevation myocardial infarction (STEMI) patients during COVID-19 pandemic (February 2020 and January 2021) with 2035 STEMI patients before pandemic (February 2016 and January 2020) using date from Mie ACS registry, a retrospective and multicenter registry. Result(s): The COVID-19 screening tests before primary PCI and/or primary PCI under full PPE was performed on 173/502 (34.5%) patients (antigen or PCR tests;39 (7.8%), chest CT;156 (31.3%), full PPE;11 (2.2%)). These patients had lower rate of achievement of DTB time <=90 min compared with others (Figure 1A). Moreover, In-hospital management of COVID-19 screening tests and/or primary PCI under full PPE was an independent factor of DTB time>90 min with odds ratio of 1.94 (95% confidential interval: 1.37-2.76, p<0.001). In addition, in-hospital mortality of those patients was higher compared with others (Figure 1B). Conclusion(s): In-hospital medical management for COVID-19 screening tests before primary PCI and/or primary PCI under full PPE was the independent factor of DTB time>90 min. This study reinforces the need to focus efforts on shortening DTB time, while controlling the epidemic of infection.
ABSTRACT
Although the coronavirus disease of 2019 arguably changed citizens' transportation mode choices, how these choices changed and what factors influenced them, especially during the soft intervention period, remains ambiguous. To clarify this phenomenon, this study examined how citizens' socio-demographic and psychological factors contributed to their transportation mode changes (public transportation, active transportation: walking and cycling, and cars) between 2019 and 2020. We employed the extended theory of the norm activation model and the value–attitude–behaviour hierarchy, surveyed 973 citizens in Toyama City, Japan, and applied a confirmatory factor analysis and a multinomial logistic regression model. Regarding psychological characteristics, the findings showed that those with positive attitudes toward public transportation tended to shift to public transportation;those with high personal norms for car use tended to shift to public transportation;those with perceived behavioural control over car use tended not to change to public transportation;and those with positive attitudes toward car use tended not to shift to active transportation. Socio-demographically, respondents who were female, highly educated and/or whose income decreased from the previous year tended to shift to active transportation. Age was not significantly associated with transportation mode changes. No significant variable was found between respondents' shift to cars and socio-demographic and psychological factors. Our study provides implications, suggesting that policymakers focus on adopting measures to retain female or highly educated individuals in the active transportation mode use even beyond the pandemic period, while raising awareness among men, informing them of the health benefits of the active transportation mode and establishing active transportation mode-friendly infrastructure. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
ABSTRACT
Technologies using artificial intelligence (AI) have been implemented as services to solve various social problems. However, the contributions of AI to people's mentality and unknown/ unobserved events have not been extensively discussed. In this study, we focus on people's mental changes caused by the COVID-19 pandemic and discuss the origin of data sources for well-being using marketing research online communities (MROCs) and variable quest (VQ). In the experiment, we selected 15 females aged between 20 and 40 who were interested in exploring how daily life has changed since the emergence of COVID-19 using MROCs. The analysis results by VQ revealed that the variable sets of the events differed with the situations, mental states, and attitudes, while not being featured in any of the MROC topics as keywords. The result suggests that ing the features of unobserved events as variable sets, can help us acquire information potentially contributing to unexplored data discovery for human well-being from texts not containing any information related to the data. © 2022 for this paper by its authors.
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In this paper, we discuss the balance between two measures to contain infectious diseases. One is isolation of infected individuals. The other is mass vaccination. This paper focuses on shared resources in implementing the two measures in a society. To seek an effective strategy to balance the two measures in the COVID-19 situation in Japan, we propose a mathematical model dividing the population into six subpopulations according to infection, symptoms, and quarantine. Using the data of COVID-19 infections in Japan, parameters in the model are estimated. Based on simulations computed with the model and the estimated parameters, this paper proposes a feedback control that achieves a better balance between isolation and vaccination sharing limited resources.
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Study Objective: There have been concerns that some patients with sepsis-life-threatening organ dysfunction caused by a dysregulated host response to infection-may be overlooked with a quick Sequential Organ Failure Assessment (qSOFA)2 in the emergency department (ED). Despite this, little is known about the risk factors associated with sepsis among patients with qSOFA<2 in the ED.
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A system that uses the susceptible-exposed-infectious-removed (SEIR) model and some methods to predict COVID-19 (SARS-Cov-2) trajectory of the pandemic which is currently prevalent. This paper reports on how to estimate the optimal parameters of the SEIR model, which can predict the pandemics of infectious diseases. © 2021 IEEE.
ABSTRACT
Recently Social Networking Service (SNS) is used extensively due to proliferation of the Internet and cheaper, compact, easy to use computing devices. Texting, especially via Twitter, is very popular among people of all ages all over the world, and enormous text data is generated regularly which contains various types of information, rumors, sentimental expressions etc. The variety of topics related to the contents of the social media data are prone to changes with the passing of time and sometimes fade out completely after a certain time. Such time varying topics may include beneficial information that could be used for various decision making by general public as well as governmental organization. Especially for the recent pandemic of COVID-19, extraction and visualization of the changing needs of people might help them making some better countermeasures. In this study, COVID-19 related tweets have been collected and analyzed in units of time (hour, day and month) by means of various clustering models to visualize the dynamic changes of topics with time. It is found that Sentence-Bert is the most effective tool among the techniques used here though it is not yet enough for clear understanding of the topics semantically.
ABSTRACT
Lack of exercise, which increases the risk of many serious physical and mental illness, has been a common health issue in Japan. Recent studies confirm that financial literacy discourages irrational behavior like gambling and smoking. We therefore investigate how financial literacy, as a rational decision-making instrument, relates to peoples’ exercise behavior in Japan. We hypothesize that financial literacy encourages people to exercise regularly. Using Osaka University’s Preference Parameters Study (PPS) for 2010, we categorized respondents into two groups: those who exercise regularly or at least once a week and those who do not. Our probit estimation results show that financial literacy is positively related with exercise behavior, meaning that financially literate people are more likely to exercise regularly. As the COVID-19 health pandemic seems to exacerbate peoples’ physical inactivity, the results of our study show an alternative approach to encourage exercise. We therefore recommend that governments implement a financial literacy improvement policy to alleviate the lack of exercise. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.