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1.
Pathophysiology ; 31(2): 269-287, 2024 May 27.
Artigo em Inglês | MEDLINE | ID: mdl-38921725

RESUMO

Bronchial asthma (BA) continues to be a difficult disease to diagnose. Various factors have been described in the development of BA, but to date, there is no clear evidence for the etiology of this chronic disease. The emergence of COVID-19 has contributed to the pandemic course of asthma and immunologic features. However, there are no unambiguous data on asthma on the background and after COVID-19. There is correlation between various trigger factors that provoke the development of bronchial asthma. It is now obvious that the SARS-CoV-2 virus is one of the provoking factors. COVID-19 has affected the course of asthma. Currently, there is no clear understanding of whether asthma progresses during or after COVID-19 infection. According to the results of some studies, a significant difference was identified between the development of asthma in people after COVID-19. Mild asthma and moderate asthma do not increase the severity of COVID-19 infection. Nevertheless, oral steroid treatment and hospitalization for severe BA were associated with higher COVID-19 severity. The influence of SARS-CoV-2 infection is one of the protective factors. It causes the development of severe bronchial asthma. The accumulated experience with omalizumab in patients with severe asthma during COVID-19, who received omalizumab during the pandemic, has strongly suggested that continued treatment with omalizumab is safe and may help prevent the severe course of COVID-19. Targeted therapy for asthma with the use of omalizumab may also help to reduce severe asthma associated with COVID-19. However, further studies are needed to prove the effect of omalizumab. Data analysis should persist, based on the results of the course of asthma after COVID-19 with varying degrees of severity.

2.
Diagnostics (Basel) ; 14(7)2024 Mar 26.
Artigo em Inglês | MEDLINE | ID: mdl-38611611

RESUMO

The COVID-19 pandemic resulted in the cessation of many tuberculosis (TB) support programs and reduced screening coverage for TB worldwide. We propose a model that demonstrates, among other things, how undetected cases of TB affect the number of future M. tuberculosis (M. tb) infections. The analysis of official statistics on the incidence of TB, preventive examination coverage of the population, and the number of patients with bacterial excretion of M. tb in the Russian Federation from 2008 to 2021 is carried out. The desired model can be obtained due to the fluctuation of these indicators in 2020, when the COVID-19 pandemic caused a dramatic reduction in TB interventions. Statistical analysis is carried out using R v.4.2.1. The resulting model describes the dependence of the detected incidence and prevalence of TB with bacterial excretion in the current year on the prevalence of TB with bacterial excretion in the previous year and on the coverage of preventive examinations in the current and previous years. The adjusted coefficient of model determination (adjusted R-squared) is 0.9969, indicating that the model contains almost no random component. It clearly shows that TB cases missed due to low screening coverage and left uncontrolled will lead to a significant increase in the number of new infections in the future. We may conclude that the obtained results clearly demonstrate the need for mass screening of the population in the context of the spread of TB infection, which makes it possible to timely identify patients with TB with bacterial excretion.

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