ABSTRACT
Background & Objective: COVID-19 is a serious disease with different symptoms and risk factors infecting and killing many people around the world. This study was performed to investigate the demographic and clinical characteristics of COVID-19 suspects referred to the hospitals and coronavirus treatment centers of Shahroud, Iran. Materials & Methods: Upon the outbreak of the COVID-19 epidemic in Shahroud, Shahroud University of Medical Sciences launched a project to systematically record the demographic, clinical, and medical data of all suspects referred to the Corona Center. In this study, the data of 3945 suspected people collected during 5 months were analyzed. The RT-PCR test was used as the criterion for diagnosing the disease. Results: Among 3945 suspected cases, 24.4% had positive RT-PCR test. The mean age of confirmed cases was 52.16 years. Dry cough and fever in addition to anorexia were reported as the most common symptoms. The results of logistic regression analysis showed that people over 60 years with heart disease reduce the risk, while people over 60 years, diabetics, and obese people increase the risk of infection. Conclusion: These results necessitate further lines of research into different symptoms and risk factors to help identify COVID-19 cases earlier and start faster treatment. © 2022, Zanjan University of Medical Sciences and Health Services. All rights reserved.
ABSTRACT
OBJECTIVES: To gather, synthesize, and meta-analyze data regarding the risk factors associated with a severe course of COVID-19 among patients with multiple sclerosis (pwMS). METHODS: MEDLINE, Embase, Scopus, and WoS were searched in May 2021. Briefly, the eligibility criteria included: 1) studies assessing COVID-19 severity among adult pwMS; 2) definitive diagnoses or high clinical suspicion of COVID-19; 3) a categorization of COVID-19 severity into at least two categories; 4) quantitative effect size and precision measurements; and 5) English language; and 6) clear effect size/precision measures. internal validity of studies was assessed using the NIH Quality Assessment Tools. A list of possible risk factors was created based on the search results and was later used in extraction, synthesis, and meta-analysis of the data. RESULTS: Thirteen studies were included in the syntheses. Outcome measures were either extracted from the papers, obtained from the primary researchers or calculated manually. The meta-analyses showed a significantly (P<0.05) increased odds of a severe COVID-19 in pwMS with all of the assessed risk factors, except smoking and most DMTs. CONCLUSION: This study facilitates evidence-based risk/benefit assessments in practice. Older men with progressive MS on anti-CD20 therapies are more at risk of an unfortunate COVID-19 outcome.
Subject(s)
COVID-19 , Multiple Sclerosis , Adult , Aged , Humans , Male , Multiple Sclerosis/complications , Multiple Sclerosis/diagnosis , Multiple Sclerosis/epidemiology , Risk Factors , SARS-CoV-2ABSTRACT
Context: Using smart mobile devices, called mobile health (mHealth), facilitates providing health services, speeds up the process, and reduces the costs and complications of direct services. Also, mHealth has many capabilities and applications in epidemic and pandemic outbreaks. This study aimed to identify mHealth applications in epidemic/pandemic outbreaks and provide some suggestions for tackling COVID-19. Methods: To find the relevant studies, searches were done in PubMed and Scopus by related keywords during 2014-2020 (March 10). After selecting the studies based on the inclusion and exclusion criteria, data were collected by a data-gathering form. Results: Of the 727 retrieved studies, 17 studies were included. All studies emphasized the positive effect of mHealth for use in epidemic/pandemic outbreaks. The main applications of mHealth for epidemic/pandemic outbreaks included public health aspects, data management, educational programs, diagnosis, and treatment. Conclusions: mHealth is an appropriate method for encountering epidemic/pandemic outbreaks due to its extensive applications. In the pandemic outbreak of COVID-19, mHealth is one of the best choices to use in the patient-physician relationship as televisits, using in fever coach, providing real-time information for healthcare providers, population monitoring, and detecting the disease based on obtained data from different locations.