ABSTRACT
Children are usually affected by pneumonia, which is a common ailment caused by Pathogenic Streptococcus pneumoniae. This study's objective was to isolate and identify S. pneumoniae, which was recovered from blood samples of suspected paediatric pneumonia patients using conventional techniques, such as antibiotic sensitivity profiles and molecular approaches. In this study, forty (40) samples from three major hospitals in the Dinajpur region of Bangladesh were collected and assessed using various bacteriological, biochemical, antibiotic susceptibility test, and molecular techniques. 37.5% of the 40 samples tested positive for pneumonia, and 15 isolates were discovered. In terms of age, pneumonia was more common in children aged 3-5 years (50%) than in those aged 6 to 8 (33.33%), 9 to 11 (25%) and 12 to 15 (20%). According to the results of the current study, the study area had no statistically significant impact (P > 0.05), while age and socioeconomic status had a significant impact on the prevalence of pneumonia in patients with pneumonia (P 0.05). The age group for which pneumonia was most prevalent (at 50%) was that for children between the ages of 3-5. Poor socioeconomic status was associated with the highest prevalence of pneumonia (54.54%). By sequencing the 16S rRNA gene, S. pneumoniae was identified as S. pneumoniae NBRC102642. In the antibiotic investigation, S. pneumoniae was found to be extremely resistant to ciprofloxacin, amikacin, vancomycin, and cefexime, but responsive to erythromycin and azithromycin, as well as neomycin, kanamycin, streptomycin, and bacitracin. S. pneumoniae causes serious complications in paediatric patients, and this scenario requires prevention through vaccination and the development of new, efficient antibiotic therapies for pneumonia. If specific laboratory features of paediatric patients with pneumonia are understood, sepsis will be easier to detect early, treat, and reduce mortality.
ABSTRACT
Background Several studies are ongoing to obtain more information about post-COVID-19 (corona virus disease-19) pulmonary fibrosis. Old-aged patients are more likely to evolve lung fibrosis in COVID-19. Another risk factor is the degree of disease severity, including comorbidities, such as hypertension, diabetes, as well as lab findings, for example, lymphopenia and leukocytosis. Aims of work To assess the prevalence of post-COVID-19 pulmonary fibrosis and reveal some of its predictors. Results The study included 50 patients in the outpatient clinics of Chest and EL-Helal Hospitals with a mean age of 49.6 +/- 17.7 years. It included 32 (64%) males and 18 (36%) females. Pulmonary fibrosis was detected in 34 (68%) patients. Pulmonary fibrosis was bilateral in 24 patients and unilateral in 10 patients. Leucopenia, elevated serum ferritin, elevated D-dimer, and elevated C-reactive protein (CRP) were associated with pulmonary fibrosis (P value 0.001). Conclusion Pulmonary fibrosis is recognized as a complication between survivors. Immune response due to lung injury by viral infection, and trials to repair are keys to the procedure of fibro genesis. Predictors of lung fibrosis involve increased lab parameters such as serum ferritin, C-reactive protein, and D-dimer. Copyright © 2022 The Egyptian Journal of Chest Diseases and Tuberculosis.
ABSTRACT
The fatal disease of COVID-19 is wrapping up the whole world. Long-term lockdown policy has become the main reason for an increase in the unemployment rate all around the globe which has affected the economy of the developed and third world countries disastrously. This paper is written to suggest a solution for the COVID-19 pandemic. The best counter-strategy would be to clean a region with a preplanned structure of short-term lockdown using the Strategic Algorithm. The area needs to be divided into two equal parts and each part will then be further divided into five subparts. These parts will be cleaned and sanitized simultaneously through the specific set of rules determined by the Strategic Algorithm. Results of the cleaning mechanism are generated using simulation of non-deterministic and deterministic automata for each accepted or cleaned area in the JFLAP tool. The current study provides a short-term lockdown mechanism for cleaning a specific area and taking other strategic steps within the lockdown period to minimize the COVID-19 effects. © 2021 IEEE.