Comparison of High-Flow Nasal Canula and Non-Invasive Mechanical Ventilation in Treating COVID-19 Patients

Objectives: The World Health Organization has declared COVID-19 a global pandemic in March 2020. Multiple COVID-19 waves are putting tremendous stress on healthcare systems. Evidence showed that high-flow nasal canula (HFNC) reduced the need for mechanical ventilation and shortened the time to clinical recovery among patients with severe COVID-19. This study aimed to assess the effect of using HFNC compared to non-invasive mechanical ventilation (NIV), on adult patients with COVID-19. Method(s): This retrospective study included patients hospitalized due to COVID-19 between October 2020 to December 2021 with appropriate ICD-10 diagnosis recorded in a commercially available, all-payer administrative database across 300+ hospitals. The identified patients were divided in two cohorts, one being the patients treated with HFNC as the first line respiratory support and another with NIV. Outcomes included all-cause mortality rate and length of stay. Multivariable analyses were performed to adjust for baseline characteristics. Result(s): Out of 16,534 eligible patients, 4,334 patients received HFNC as the first line respiratory support, whereas 12,200 received NIV. The all-cause mortality rate was 20.24% and 37.14% in the HFNC and NIV group, respectively. After adjusting for baseline characteristics, the all-cause mortality rate in the HFNC group was lower compared to NIV (odds ratio [OR], 0.51;95% confidence interval [CI], 0.47-0.55;p<0.001). The total length of stay was around 15 days for all patients. No different was observed between groups ( mean difference 0.3 days;95% CI, -0.27 - 0.92 days;p>0.05). Conclusion(s): Patients treated with HFNC showed lower mortality rates compared to NIV for hospitalized COVID-19 patients. However, further studies are still needed to better elucidate the clinical and economic benefit of HFNC in COVID-19 patients.Copyright © 2023

Network evolution underneath the volatility spillover in traditional and clean energy markets

When facing volatility spillovers in energy markets, all players require risk mitigation strategies to insulate themselves from the same. To prevent energy markets from being strongly crashed by volatility spillovers, which even trigger financial crises, in this paper, we use network analysis as an aid to identify spillovers among the main nine energy markets. Specifically, we first measure the volatility spillovers among the main energy markets through a BEKK model. Based on this, influential markets are identified by using network analysis. The coal, wind and water energy markets should be paid close attention as they occupy vital roles in the volatility spillover network. Even though clean energy markets contribute more in terms of market stability, traditional energy markets are still important to ensure energy supply when experiencing extreme crashes caused by COVID-19. In this paper, we make the contributions to analysing volatility spillovers in multiple energy markets and identifying crucial energy markets in volatility spillover networks, then provide more market information that helps the government and policymakers effectively manage systemic risks caused by volatility spillovers. The effective risk management of crucial energy markets enhances economic recovery and stability, especially in the post-COVID-19 era.

[Epidemiological characteristics of imported COVID-19 cases in Tianjin].

Objective: To understand the epidemiological characteristics of imported COVID-19 cases in Tianjin, and provide references for risk assessment and control of imported COVID-19 cases. Methods: The information of imported COVID-19 cases were obtained from National Notifiable Disease Report System of China CDC. The data of imported COVID-19 cases reported from Tianjin airport and epidemiological surveys by CDCs at all levels from March 15, 2020 to August 31, 2021 were collected and analyzed by using software Excel 2010, SPSS 25.0 and R. Results: From March 15, 2020 to August 31, 2021, a total of 606 imported cases of COVID-19 were reported in Tianjin, in which 552 cases were finally included in the analysis. The male to female ratio of the cases was 1.8∶1, the age of the cases ranged from 3 to 77 years, and the cases were mainly reported in age group 20-39 years (59.8%). The areas where the imported case sojourned within 14 days included Europe (242 cases, 43.8%), Africa (139 cases, 25.2%), Americas (85 cases, 15.4%) and Asia (86 cases, 15.6%). The proportion of confirmed cases in autumn and winter was relatively high. During the study period, the proportion of infected persons found in custom entry quarantine decreased, and the proportion of persons with personal health declaration and under medical isolation observation increased. The interval between entry and diagnosis of infected persons tended to increase. Conclusion: The proportion of imported COVID-19 cases detected on the first day of entry at Tianjin airport decreased, and the interval to detect the infected persons trended to increase, to which close attention must be paid.

Improving in-hospital stroke service utilization (MISSION) to shorten thrombolytic door-to-needle time in acute ischemic stroke patients: A cluster randomized controlled trial

Background and Aims: Rapid intravenous thrombolysis (IVT) for acute ischemic stroke (AIS) is crucial for improving outcomes. However, randomized trials to reduce in-hospital delay are clearly limited in China. We aimed to evaluate the effect of a multi-component intervention on thrombolytic door-to needle time (DNT) of AIS patients via video teleconference based on the Behavior Change Wheel method. Methods: This trial randomly allocated 22 hospitals equally to PEITEM (Persuasion Environment reconstruction Incentivisation Training Education Modeling) intervention or routine care plus stroke registry and subsequently enrolled 1634 AIS patients who receiving IVT within 4.5 hours upon stroke onset from participant hospitals. The PEITEM group received a one-year PEITEM intervention based on the behavioral theory monthly via video teleconference. Results: A total of 1, 634 patients from the 22 hospitals were enrolled. The proportion of DNT ≤ 60 minutes was 82.0% in the PEITEM group and 73.7% in the control group (adjusted odds ratio, 1.85;95% confidence interval [CI], 1.42 to 2.42, P<0.001). The average DNT was 43 minutes in the PEITEM group and 50 minutes in the control group (β: -9.00;95% CI, -11.37 to ≤6.63, P<0.001). Favorable neurological outcomes were achieved in 55.6% patients in the PEITEM group and 50.4% patients in the control group (adjusted odds ratio, 1.34;95% CI, 1.02 to 1.75;P=0.04). Conclusions: The teleconference-delivered PEITEM intervention resulted in a moderately but clinically relevant shorter DNT and better neurological outcomes in the AIS treated with the IVT. Video teleconference may be more appropriate and easier for quality improvement in the current global COVID-19 public health crisis disrupting healthcare services.

A pre-registered short-term forecasting study of COVID-19 in Germany and Poland during the second wave.

Disease modelling has had considerable policy impact during the ongoing COVID-19 pandemic, and it is increasingly acknowledged that combining multiple models can improve the reliability of outputs. Here we report insights from ten weeks of collaborative short-term forecasting of COVID-19 in Germany and Poland (12 October-19 December 2020). The study period covers the onset of the second wave in both countries, with tightening non-pharmaceutical interventions (NPIs) and subsequently a decay (Poland) or plateau and renewed increase (Germany) in reported cases. Thirteen independent teams provided probabilistic real-time forecasts of COVID-19 cases and deaths. These were reported for lead times of one to four weeks, with evaluation focused on one- and two-week horizons, which are less affected by changing NPIs. Heterogeneity between forecasts was considerable both in terms of point predictions and forecast spread. Ensemble forecasts showed good relative performance, in particular in terms of coverage, but did not clearly dominate single-model predictions. The study was preregistered and will be followed up in future phases of the pandemic.

National health and nutrition examination survey 2017–march 2020 prepandemic data files-development of files and prevalence estimates for selected health outcomes

Background and objectives-In March 2020, the coronavirus disease 2019 (COVID-19) pandemic halted National Health and Nutrition Examination Survey (NHANES) field operations. As data collected in the partial 2019–2020 cycle (herein referred to as 2019–March 2020) are not nationally representative, they were combined with previously released 2017–2018 data to produce nationally representative estimates. This report explains the creation of the 2017–March 2020 prepandemic data files, provides recommendations for and limitations of the files’ use, and presents prevalence estimates for selected health outcomes based on the files. Methods-The 2019–2020 primary sampling units (PSUs) were reassigned to the 2015–2018 sample design strata and combined with the 2017–2018 data to create a data set that could be used to calculate nationally representative estimates. A PSUlevel adjustment factor was created to equalize the contribution of each stratum to the total survey sample and applied to participant base weights. Interview and examination weights were calculated from the adjusted base weights. The performance of final interview weights was assessed by comparing the demographic characteristics of the weighted NHANES 2017–March 2020 prepandemic sample with nationally representative estimates from the 2018 5-year American Community Survey. Prevalence estimates and 95% confidence intervals were calculated for selected health outcomes. Results-Among children and adolescents aged 2–19 years, the prevalence of obesity was 19.7% and the prevalence of untreated or restored dental caries in one or more primary or permanent teeth was 46.0%. Among adults aged 20 and over, the age-adjusted prevalence of obesity was 41.9%, severe obesity was 9.2%, and diabetes was 14.8%. Among adults aged 18 and over, the age-adjusted prevalence of hypertension was 45.1%. Among adults aged 65 and over, the age-adjusted prevalence of complete tooth loss was 13.8%. Conclusion-A PSU-level adjustment factor and additional weighting adjustments made nationally representative estimates from the 2017–March 2020 prepandemic data files possible;this was the last NHANES data collected before widespread transmission of COVID-19. © 2021, National Center for Health Statistics. All rights reserved.