Background Respiratory viral and atypical bacterial infections data in Egyptian patients are sparse. This study describes the clinical features and outcomes of patients with severe acute respiratory infections (SARI) in hospitalized patients in Egypt. Methods SARI surveillance was implemented at Cairo University Hospital (CUH) during the period 2010–2014. All hospitalized patients meeting the WHO case definition for SARI were enrolled. Nasopharyngeal/oropharyngeal (NP/OP) swabs were collected and samples were tested using RT-PCR for influenza A, B, respiratory syncytial virus (RSV), human metapneumovirus (hMPV), parainfluenza virus (PIV 1,2,3,4), adenovirus, bocavirus, coronavirus, enterovirus, rhinovirus, and atypical bacteria. Data were analyzed to calculate positivity rates for viral pathogens and determine which pathogens related to severe outcomes or resulted in death. Results Overall, 1,075/3,207 (33.5%) cases had a viral etiology, with a mean age of 5.74 (±13.87) years. The highest rates were reported for RSV (485 cases, 45.2%), PIV (125, 11.6%), and adenovirus (105, 9.8%). Children had a higher viral rate (981, 91.2%) compared to 94 (8.8%) cases in adults. Patients with identified viruses had significantly lower rates for ICU admission, hospital stay, mechanical ventilation, and overall mortality than those without identified viruses. No infections were independently associated with severe outcomes. Conclusions Viral pathogens were encountered in one-third of hospitalized adult and pediatric Egyptian patients with SARI, while atypical bacteria had a minor role. Highest rates of viral infections were reported for RSV, PIV, and adenovirus. Viral infections had neither negative impacts on clinical features nor outcomes of patients with SARI in our locality.
Approximately one-third of infected pregnant women died from severe acute respiratory syndrome coronavirus (SARS-CoV) and the Middle East respiratory syndrome coronavirus (MERS-CoV) epidemics of the past two decades. It is logical to predict that pregnant women infected with the novel coronavirus (SARS-CoV-2) might be at higher risk for severe illness, morbidity, or mortality compared with non-pregnant women. However, a review of the literature indicates that pregnant women are not more likely to be seriously ill than other healthy non-pregnant women if they develop coronavirus disease (COVID-19). This observation begs the question: "Why does pregnancy not increase the risk for acquiring SARS-CoV-2 infection, nor does it worsen the clinical course of COVID-19 compared with nonpregnant individuals?" Herein, we try to explain our observations when considering whether the immunologic changes of pregnancy and other physiologic adaptations of pregnancy affect the virulence and course of SARS-CoV-2 infection.
926 women attending the Obstetrics and Gynaecology Department of the Faculty of Medicine, Khartoum, were investigated to study the inbreeding effects on reproductive profiles and morbidity of the offspring. 49.5% of the women had married their first cousins and 13.8% had married more distant relatives. Altogether, 4,471 pregnancy outcomes were analysed including abortions, still births, neonatal and childhood deaths, physical deformity, mental retardation and other congenital abnormalities. No significant difference in the reproductive loss or net fertility was observed between the inbred and outbred groups. Only the proportions of childhood deaths were found to be significantly higher in the inbred marriages (p < 0.005). The morbidity was also not affected by the practice of inbreeding.
Background: Pregnant women may be more vulnerable than others to the psychological and social effects of the coronavirus disease 2019 (COVID-19) pandemic. In this study, we try to answer the question -is the modified distress thermometer (m-DT) useful for screening pregnant women with COVID-19 for psychological distress? Methods: We have used the m-DT to screen pregnant women with COVID-19 for psychological distress. A total of 112 pregnant women with COVID-19 were prospectively enrolled. The study participants were asked to rate their distress in the past three days on an 11-point visual analog scale ranging from 0 (no distress) to 10 (extreme distress). They were then asked to fill in the problem list (PL) which accompanied the visual image of the m-DT. To explore the association between these scores and the clinical variables, binary logistic regression tests were carried out.Results: Sixty-eight percent (76/112) of the study subjects experienced significant (m-DT score ≥ 4) COVID-19-related distress. Regression analysis showed that m-DT score of ≥4 had statistically significant associations with gravida status length of quarantine time, the presence of chronic medical or respiratory disease, fears, worry, shortness of breath, and sleep. Multivariable analysis confirmed that the presence of chronic respiratory disease, shortness of breath, and sleep were independent factors associated with significant distress in pregnant women with COVID-19. Conclusion:With the use of m-DT, two-thirds of pregnant women with COVID-19 experienced significant distress. This distress was significantly related to older age, multigravida, exposure to longer quarantine time, presence of underlying medical disorder, and the presence of chronic respiratory disorders. The presence of chronic respiratory disease, shortness of breath, and sleep disturbance were independent factors associated with significant distress in pregnant women with COVID-19.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.