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To examine the association between red/processed meat consumption and glycaemic conditions (i.e., prediabetes [preDM] and DM) among middle-aged residents in rural Khánh Hòa, Vietnam.
In this cross-sectional study, a multinomial regression model was used to examine the association between daily consumption of red/processed meat (0-99 g, 100-199 g, or ≥ 200 g) and preDM/DM with adjustments for sociodemographic, lifestyle-related, and health-related variables.
Khánh Hòa Province, Vietnam
The study used data collected through a baseline survey conducted during a prospective cohort study on cardiovascular diseases among 3000 residents, aged 40-60 years, living in rural communes in Khánh Hòa Province.
The multinomial regression model revealed that the prevalence ratios (PRs) for DM were 1.00 (reference), 1.11 (95% confidence interval [CI] = 0.75-1.62), and 1.80 (95% CI = 1.40-2.32) from the lowest to the highest red/processed meat consumption categories (p trend = 0.006). The corresponding values for preDM were 1.00 (reference), 1.25 (95% CI = 1.01-1.54), and 1.67 (95% CI = 1.20-2.33) (p trend = 0.004). We did not find any evidence of statistical significance in relation to poultry consumption.
Increased red/processed meat consumption, but not poultry consumption, was positively associated with the prevalence of preDM/DM in rural communes in Khánh Hòa Province, Vietnam. Dietary recommendations involving a reduction in red/processed meat consumption should be considered in LMICs.
Let M be a closed n-dimensional smooth Riemannian manifold, and let X be a $C^1$-vector field of $M.$ Let $\gamma $ be a hyperbolic closed orbit of $X.$ In this paper, we show that X has the $C^1$-stably shadowing property on the chain component $C_X(\gamma )$ if and only if $C_X(\gamma )$ is the hyperbolic homoclinic class.
More than 80% of coronavirus disease 2019 (COVID-19) cases are mild or moderate. In this study, a risk model was developed for predicting rehabilitation duration (the time from hospital admission to discharge) of the mild-moderate COVID-19 cases and was used to conduct refined risk management for different risk populations.
A total of 90 consecutive patients with mild-moderate COVID-19 were enrolled. Large-scale datasets were extracted from clinical practices. Through the multivariable linear regression analysis, the model was based on significant risk factors and was developed for predicting the rehabilitation duration of mild-moderate cases of COVID-19. To assess the local epidemic situation, risk management was conducted by weighing the risk of populations at different risk.
Ten risk factors from 44 high-dimensional clinical datasets were significantly correlated to rehabilitation duration (P < 0.05). Among these factors, 5 risk predictors were incorporated into a risk model. Individual rehabilitation durations were effectively calculated. Weighing the local epidemic situation, threshold probability was classified for low risk, intermediate risk, and high risk. Using this classification, risk management was based on a treatment flowchart tailored for clinical decision-making.
The proposed novel model is a useful tool for individualized risk management of mild-moderate COVID-19 cases, and it may readily facilitate dynamic clinical decision-making for different risk populations.
The median duration of hospital stays due to COVID-19 has been reported in several studies on China as 10−13 days. Global studies have indicated that the length of hospitalisation depends on different factors, such as the time elapsed from exposure to symptom onset, and from symptom onset to hospital admission, as well as specificities of the country under study. The goal of this paper is to identify factors associated with the median duration of hospital stays of COVID-19 patients during the second COVID-19 wave that hit Vietnam from 5 March to 8 April 2020.
We used retrospective data on 133 hospitalised patients with COVID-19 recorded over at least two weeks during the study period. The Cox proportional-hazards regression model was applied to determine the potential risk factors associated with length of hospital stay.
There were 65 (48.9%) females, 98 (73.7%) patients 48 years old or younger, 15 (11.3%) persons with comorbidities, 21 (16.0%) severely ill patients and 5 (3.8%) individuals with life-threatening conditions. Eighty-two (61.7%) patients were discharged after testing negative for the SARS-CoV-2 virus, 51 were still in the hospital at the end of the study period and none died. The median duration of stay in a hospital was 21 (IQR: 16–34) days. The multivariable Cox regression model showed that age, residence and sources of contamination were significantly associated with longer duration of hospitalisation.
A close look at how long COVID-19 patients stayed in the hospital could provide an overview of their treatment process in Vietnam, and support the country's National Steering Committee on COVID-19 Prevention and Control in the efficient allocation of resources over the next stages of the COVID-19 prevention period.
Probing and controlling electrons and nuclei in matter at the attosecond timescale became possible with the generation of attosecond pulses by few-cycle intense lasers, and has revolutionized our understanding of atomic structure and molecular processes. This book provides an intuitive approach to this emerging field, utilizing simplified models to develop a clear understanding of how matter interacts with attosecond pulses of light. An introductory chapter outlines the structure of atoms and molecules and the properties of a focused laser beam. Detailed discussion of the fundamental theory of attosecond and strong-field physics follows, including the molecular tunnelling ionization model (MO-ADK theory), the quantitative rescattering (QRS) model, and the laser induced electronic diffraction (LIED) theory for probing the change of atomic configurations in a molecule. Highlighting the cutting-edge developments in attosecond and strong field physics, and identifying future opportunities and challenges, this self-contained text is invaluable for students and researchers in the field.