Background and Aims: Sexually transmitted infections (STIs) are one of the major health concerns globally. Generally, prisoners are at higher risks for STIs due to risk factors including; drug-use, high-risk sexual behaviors, densely populated prisons, and poor living conditions. Therefore, we aimed to conduct a systematic review to evaluate the existing data on STI prevalence, and its associated risk factors among prisoners.Methods: We conducted a systematic search of the literature using the keywords in Scopus, PubMed, Web of Science, and Google Scholar online databases. We selected all the relevant original studies in English through title/abstract and full-text screening process.Results: Based on the inclusion and exclusion criteria, we selected and reviewed 32 studies out of 96 identified papers. The most important STI-associated risk factors among prisoners were drug use, low educational levels, and unsafe sex. The prevalence of STIs was heterogenous in selected studies and was reported as follows; Human Immunodeficiency Virus (HIV) (0%−14.5%), hepatitis B viruses (HBV) (0.04%−27.23%), hepatitis C viruses (HCV) (0.17%−49.7%), Syphilis (0.2%−22.1%), Chlamydia Trachomatis (CT) (1.02%−6.7%), Gonorrhea (0.6%−7.8%), and herpes simplex virus-2 (HSV-2) 22.4%. Conclusion:This systematic review indicates that the prevalence of STIs (HIV, HBV, HCV, Syphilis, Chlamydia Trachomatis, Gonorrhea, and HSV-2) among prisoners appears to be higher than the general population, with drug abuse, low educational levels, and unsafe sex as major risk factors.
Understanding the spreading routes of SARS-CoV-2 is crucial for patient management and defining biosafety strategies for public and health care workers. In the current study, the virus shedding in upper respiratory as well as blood, stool, and urine specimens of infected patients was examined using reverse transcription real-time PCR assay (RT-qPCR).
Introduction: Despite the improvement in COVID-19 therapeutic management the mortality of mechanically ventilated COVID-19 patients remains high. In this study, we determined risk factors of mortality in these cases. Methods: This retrospective study examined clinical and paraclinical data of COVID-19 patients mechanically ventilated at the time of hospitalization to ICU admission until death or discharge from hospital between April and September in 2021 in three COVID-19 referral hospitals. Results: One hundred twenty-five patients (60% male, mean age 62 ± 15.18, range 17 to 97 years old) were recruited to this study. 51(40%) survived and 74 (60%) didn’t survive. At the time of hospital admission, the vital signs were not significantly different between the survivors and non-survivors groups, also diarrhea was not reported in non-survivors, but reported in 9.5% of survivors (P = 0.02). The mean age of 74 non-survivors was higher than 51 survivors (65.1 ± 14.17 vs 56.9 ± 15.41, P = 0.003). The intubation time since the patients were admitted to hospitals was not significantly different between the two groups (3.38 ± 2.88 days vs 4.16 ± 3.42 days, P = 0.34). The mean LDH and D-dimer at the time of ICU admission were significantly higher in the non-survivors group (863 ± 449 vs 613 ± 326, P = 0.01; 4081 ± 3342 vs 542 ± 634, P = 0.009; respectively). However, the mean CRP was not significantly different between the two groups (76 ± 66.4, 54 ± 84.3; P = 0.1). Mean APACHE-II score was higher in the non-survivors than the survivors (15 vs 13; P = 0.01). Use of remdesivir, interfrone beta-1a, and low dose corticosteroids were significantly higher in the survivors group (P = 0.009, P = 0.001, P = 0.000). Conclusion: Success of weaning and hospital discharge among mechanically ventilated COVID-19 patients are probably higher in younger patients with lower D-dimmer and LDH levels that received low dose corticosteroids during treatment.
Introduction: The accurate number of COVID-19 cases is essential knowledge to control an epidemic. Currently, one of the most important obstacles in estimating the exact number of COVID-19 patients is the absence of typical clinical symptoms in a large number of people, called asymptomatic infections. In this systematic review, we included and evaluated the studies mainly focusing on the prediction of undetected COVID-19 incidence and mortality rates as well as the reproduction numbers, utilizing various mathematical models. Methods: This systematic review aims to investigate the estimating methods of undetected infections in the COVID-19 outbreak. Databases of PubMed, Web of Science, Scopus, Cochrane, and Embase, were searched for a combination of keywords. Applying the inclusion/ exclusion criteria, all retrieved English literature by April 7, 2022, were reviewed for data extraction through a two-step screening process; first, titles/ abstracts, and then full-text. This study is consistent with the PRISMA checklist. Results: In this study, 61 documents were retrieved using a systematic search strategy. After an initial review of retrieved articles, 6 articles were excluded and the remaining 55 articles met the inclusion criteria and were included in the final review. Most of the studies used mathematical models to estimate the number of underreported asymptomatic infected cases, assessing incidence and prevalence rates more precisely. The spread of COVID-19 has been investigated using various mathematical models. The output statistics were compared with official statistics obtained from different countries. Although the number of reported patients was lower than the estimated numbers, it appeared that the mathematical calculations could be a useful measure to predict pandemics and proper planning. Conclusion: In conclusion, our study demonstrates the effectiveness of mathematical models in unraveling the true burden of the COVID-19 pandemic in terms of more precise, and accurate infection and mortality rates, and reproduction numbers, thus, statistical mathematical modeling could be an effective tool for measuring the detrimental global burden of pandemic infections. Additionally, they could be a really useful method for future pandemics and would assist the healthcare and public health systems with more accurate and valid information.
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.
hi@scite.ai
334 Leonard St
Brooklyn, NY 11211
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.