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1.
Resources Policy ; 77:102766, 2022.
Article in English | ScienceDirect | ID: covidwho-1867720

ABSTRACT

The current study investigates volatility in natural resources commodity prices by estimating volatility in oil rents, natural gas rents, and total natural resources rents. This study utilized data for two developed economies, namely: Japan and the United Kingdom (UK), covering the period from 1990 to 2020. In order to analyze volatility, we utilized autoregressive conditional heteroscedasticity (ARCH), threshold generalized autoregressive conditional heteroscedasticity [TGARCH(1, 1)], and exponential generalized autoregressive conditional heteroscedasticity [EGARCH(1, 1)] specifications. The empirical findings reveal that only natural gas is volatile in Japan. Also, natural gas showed asymmetry, where negative shock severely affects natural gas volatility. In the case of the UK, all the three rents are found volatile. However, oil rents and total natural resources rents are symmetric throughout the period. While natural gas rents are asymmetric, the negative shock highly influences volatility during the study period. Besides, there is a negative association of current variance with the past variances of natural gas rents. Based on the empirical findings, this study suggests the stabilization of the financial system, recovery from the Covid-19 pandemic crisis, adoption of price ceiling policies, and regulation of natural resources prices.

2.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-313435

ABSTRACT

Background: The coronavirus disease 2019 (COVID-19) has caused global pandemic, resulting in considerable mortality. The risk factors, clinical treatments and especially comprehensive risk models for COVID-19 death are urgently warranted. Methods In this retrospective study, 281 non-survivors and 712 survivors with propensity score matching by age, sex and comorbidities were enrolled from January 13, 2020 to March 31, 2020. Results Higher SOFA, qSOFA, APACHE II and SIRS scores, hypoxia, elevated inflammatory cytokines, multi-organ dysfunction, decreased immune cells subsets and complications were significantly associated with the higher COVID-19 death risk. In addition to traditional predictors for death risk, including APACHE II (AUC = 0.83), SIRS (AUC = 0.75), SOFA (AUC = 0.70) and qSOFA scores (AUC = 0.61), another four prediction models that included immune cells subsets (AUC = 0.90), multiple organ damage biomarkers (AUC = 0.89), complications (AUC = 0.88) and inflammatory-related indexes (AUC = 0.75) were established. Additionally, the predictive accuracy of combining these risk factors (AUC = 0.950) was also significantly higher than that of each risk group alone, outperforming previous risk models, which was significant for early clinical management for COVID-19. Conclusions The potential risk factors could help to predict the clinical prognosis of COVID-19 patients at an early stage. The combined model might be more suitable for the death risk evaluation of COVID-19.

3.
BMC Infect Dis ; 21(1): 951, 2021 Sep 14.
Article in English | MEDLINE | ID: covidwho-1412707

ABSTRACT

BACKGROUND: The coronavirus disease 2019 (COVID-19) has caused a global pandemic, resulting in considerable mortality. The risk factors, clinical treatments, especially comprehensive risk models for COVID-19 death are urgently warranted. METHODS: In this retrospective study, 281 non-survivors and 712 survivors with propensity score matching by age, sex, and comorbidities were enrolled from January 13, 2020 to March 31, 2020. RESULTS: Higher SOFA, qSOFA, APACHE II and SIRS scores, hypoxia, elevated inflammatory cytokines, multi-organ dysfunction, decreased immune cell subsets, and complications were significantly associated with the higher COVID-19 death risk. In addition to traditional predictors for death risk, including APACHE II (AUC = 0.83), SIRS (AUC = 0.75), SOFA (AUC = 0.70) and qSOFA scores (AUC = 0.61), another four prediction models that included immune cells subsets (AUC = 0.90), multiple organ damage biomarkers (AUC = 0.89), complications (AUC = 0.88) and inflammatory-related indexes (AUC = 0.75) were established. Additionally, the predictive accuracy of combining these risk factors (AUC = 0.950) was also significantly higher than that of each risk group alone, which was significant for early clinical management for COVID-19. CONCLUSIONS: The potential risk factors could help to predict the clinical prognosis of COVID-19 patients at an early stage. The combined model might be more suitable for the death risk evaluation of COVID-19.


Subject(s)
COVID-19 , Sepsis , Humans , Intensive Care Units , Organ Dysfunction Scores , Prognosis , ROC Curve , Retrospective Studies , Risk Factors , SARS-CoV-2
4.
BMC Infect Dis ; 21(1): 951, 2021 Sep 14.
Article in English | MEDLINE | ID: covidwho-1406708

ABSTRACT

BACKGROUND: The coronavirus disease 2019 (COVID-19) has caused a global pandemic, resulting in considerable mortality. The risk factors, clinical treatments, especially comprehensive risk models for COVID-19 death are urgently warranted. METHODS: In this retrospective study, 281 non-survivors and 712 survivors with propensity score matching by age, sex, and comorbidities were enrolled from January 13, 2020 to March 31, 2020. RESULTS: Higher SOFA, qSOFA, APACHE II and SIRS scores, hypoxia, elevated inflammatory cytokines, multi-organ dysfunction, decreased immune cell subsets, and complications were significantly associated with the higher COVID-19 death risk. In addition to traditional predictors for death risk, including APACHE II (AUC = 0.83), SIRS (AUC = 0.75), SOFA (AUC = 0.70) and qSOFA scores (AUC = 0.61), another four prediction models that included immune cells subsets (AUC = 0.90), multiple organ damage biomarkers (AUC = 0.89), complications (AUC = 0.88) and inflammatory-related indexes (AUC = 0.75) were established. Additionally, the predictive accuracy of combining these risk factors (AUC = 0.950) was also significantly higher than that of each risk group alone, which was significant for early clinical management for COVID-19. CONCLUSIONS: The potential risk factors could help to predict the clinical prognosis of COVID-19 patients at an early stage. The combined model might be more suitable for the death risk evaluation of COVID-19.


Subject(s)
COVID-19 , Sepsis , Humans , Intensive Care Units , Organ Dysfunction Scores , Prognosis , ROC Curve , Retrospective Studies , Risk Factors , SARS-CoV-2
5.
Zhonghua Wei Zhong Bing Ji Jiu Yi Xue ; 32(6): 646-651, 2020 Jun.
Article in Chinese | MEDLINE | ID: covidwho-659777

ABSTRACT

The high incidence of coronavirus disease 2019 (COVID-19) and high mortality of critical patients have posed a great challenge to global public health resources. Currently there are no specific antiviral drugs and vaccines available for COVID-19, which has drawn the attention to the usefulness of convalescent plasma (CP) again, so the application of CP in the adult patients with COVID-19 is reviewed. The main contents include the possible mechanism of CP, the evidence of CP in the treatment of COVID-19 patients, the safety of clinical application of CP and the main factors affecting the clinical effect of CP, which may provide some basis for clinicians to choose CP for the treatment of adult patients with COVID-19.


Subject(s)
Betacoronavirus , Coronavirus Infections , Pandemics , Pneumonia, Viral , Adult , COVID-19 , Coronavirus Infections/therapy , Humans , Immunization, Passive , Pneumonia, Viral/therapy , SARS-CoV-2
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