Knowledge of Medical Imaging Professionals on Healthcare-Associated Infections: A Systematic Review and Meta-Analysis.

Healthcare-associated infections (HCAIs) are a significant concern for both healthcare professionals and patients. With recent advances in imaging modalities, there is an increase in patients visiting the radiology department for diagnosis and therapeutic examination. The equipment used for the investigator is contaminated, which may result in HCAIs to the patients and healthcare professionals. Medical imaging professionals (MIPs) should have adequate knowledge to overcome the spread of infection in the radiology department. This systematic review aimed to examine the literature on the knowledge and precaution standard of MIPs on HCIAs. This study was performed with a relative keyword using PRISMA guidelines. The articles were retrieved from 2000 to 2022 using Scopus, PubMed, and ProQuest databases. The NICE public health guidance manual was used to assess the quality of the full-length article. The search yielded 262 articles, of which Scopus published 13 articles, PubMed published 179 articles, and ProQuest published 55 articles. In the present review, out of 262 articles, only 5 fulfilled the criteria that reported MIPs' knowledge of Jordan, Egypt, Sri Lanka, France, and Malawi populations. The present review reported that MIPs have moderate knowledge and precautionary standards regarding HCIAs in the radiology department. However, due to the limited studies published in the literature, the current review limits the application of the outcome in the vast MIPs population. This review recommended further studies to be conducted among the MIPs worldwide to know the actual knowledge and precaution standards regarding HCIAs.

Quality of life of people after COVID-19 recovery.

FAKE NEWS PREDICTION ON COVID DATASET USING MACHINE LEARNING

Fake news is false information, nowadays these are big challenges in all types of media, especially social media. In this covid-19 pandemic situation, people are facing more problems and struggling every day. One among those problems, is fake news or false information about covid. To tackle this, we have made an attempt and created a dataset with 4200 records from social media. We analyze the outbreak of covid information and visualize them using charts and graphs and predict the fake news using three classifier machine learning models. They are passive aggressive classifiers, Naïve Bayes classifiers and Support Vector Machines. © 2021 IEEE.

Prevalence of Anxiety Disorders among Antenatal Women in a Rural Area Adjacent to Chennai

Aim: Antenatal anxiety and depression are major health problems all over the world. Research conducted during pandemics found that pregnant women are more vulnerable psychologically. The aim of the study is to estimate the prevalence of anxiety level during the COVID-19 pandemic among pregnant women Study Design: A Cross sectional study design Place and Duration of Study: was done on pregnant women attending the antenatal clinic at the rural area adjacent to Chennai, India between april 2021 to October 2021. Methadology: This study was conducted among 74 pregnant women coming for antenatal checkups in the Rural area adjacent to Chennai. Hamilton - Anxiety Scale (HAM-A) was applied after initial psychiatry work up to all women who were selected for the interview. The statistically significant P value was < 0.05. Results: The sociodemographic variables have been found as significant contributors in explaining the variability of the prevalence rates of antenatal depression. According to the findings, less than 1/3rd of pregnant women experience depression as a result of life circumstances such as economic crises in order to support their families. These were identified as significant risk variables (P>0.05). And also, this study identified those who receiving insufficient socioeconomic assistance were more likely to experience multiple psychological discomfort [atleast 1] than women who got appropriate economic support. (r = -0.112, P < 0.001) Conclusion: COVID-19 infection during pregnancy was associated with increased levels of generalized anxiety scores. Patient-tailored psychological support should be a mainstay of comprehensive antenatal medical care in order to avoid anxiety- related complications.

Quality of life and mental health of people who have recovered after COVID 19 infection: A survey

Coping strategies for obese individuals with obstructive sleep apnea during COVID-19 pandemic: A narrative review.

BACKGROUND: Patients infected with SARS-CoV-2- having pre-existing non-communicable diseases (NCDs)- are at a higher risk of complications. Obesity is one of the proven risk factors causing NCDs and can influence outcomes of COVID-19 patients. It is closely related to obstructive sleep apnea (OSA). The increased risk of COVID-19 and reduced access to treatment of non-COVID conditions during the pandemic may increase the stress in obese patients with OSA. This situation makes it necessary for them to cope with their condition by themselves. This review aimed at the effect of this pandemic on these patients and coping strategies for them. METHODS: Databases like PubMed and Scopus were searched using a combination of key words. Full-text articles meeting the inclusion criteria were selected. RESULTS: The search yielded eight studies, discussing about the potential interactions between the COVID-19, obesity and OSA, the impact of COVID-19 on them, and management of these patients. CONCLUSIONS: Increased prevalence of COVID-19 was found among obese patients with OSA. The fear of COVID-19 and shift of health care workers to manage COVID-19 patients has affected their regular visits to the hospital. However, there is lack of coping strategies for them, which should soon be established for these patients.