ABSTRACT
Objective Surgery simulators have gained popularity in medical education during recent decades especially following COVID-19 pandemics. This study was designed to find the most effective and applicable model for development of total knee arthroplasty surgery simulator.Method The protocol of this study is evaluated and confirmed by Tehran university of Medical Sciences research committee (No: 52841-101-1-1400) in March 2021. This is a qualitative study using focus group discussion (FGD) for data gathering. Three FGDs were performed through online platform. Eligible five orthopedics residents, four fellowship trainees, and seven university professors from 3 different university hospitals were interviewed.Results The main domains of discussion were the necessity of a TKA simulator, virtual vs. physical model, bone and soft tissue characteristics, and the feedback system. 12% of participants (2 senior residents) said a virtual model has more advantages than a physical one while the other two thought physical model is more applicable. 12% of them (One senior resident and a fellowship trainee) suggested a mixed model would be more useful. The essential parts of the TKA simulator were mainly addressed by fellowship trainees focusing on presence of foot, ankle and hip in the model and inclusion of vital soft tissue elements and ligaments and tendons (especially collateral ligaments). Gap balancing was noticed as a crucial part by 40% of participants (senior residents and fellowships). To improve the simulator, participants suggested that it should have a modular design with sensors to alarm any damage to vital elements and feedbacks given during the procedures.Conclusion Through this study, the participants highlighted the most important parts of hard and soft tissues in the model, as well as the fundamental points in designing the TKA simulator.
Subject(s)
COVID-19ABSTRACT
Introduction: Clinical depression and the subsequent low immunity is a comorbidity that can act as a risk factor for severity of COVID-19 cases. Antidepressants such as SSRI and SNRI are associated with immune-modulatory effects, which dismiss inflammatory response and reduce lung tissue damage. The current systematic review and meta-analysis aims to evaluate the effect of antidepressant drugs on prognosis and severity of COVID-19 in hospitalized patients. Methods: A systematic search was carried out in PubMed/Medline, EMBASE, and Scopus up to January 16, 2022. The following keywords were used: "COVID-19", "SARS-CoV-2", "2019-nCoV", "SSRI", "SNRI", "TCA", "MAOI", and "Antidepressant". The pooled risk ratio (RR) with 95% CI was assessed using a fixed or random-effect model. We considered P < 0.05 as statistically significant for publication bias. Data were analyzed by Comprehensive Meta-Analysis software, Version 2.0 (Biostat, Englewood, NJ). Results: Twelve studies were included in our systematic review. Three of them were experimental with 1751, and nine of them were observational with 290,950 participants. Seven out of twelve articles revealed the effect of antidepressants on reducing severity of COVID-19. SSRI medications, including Fluvoxamine, Escitalopram, Fluoxetine, and Paroxetine and also among the SNRI drugs Venlafaxine are also reasonably associated with reduced risk of intubation or death. There were four studies showing no significant effect and one study showing the negative effect of antidepressants on prognosis of covid-19. The meta-analysis on clinical trials showed that fluvoxamine could significantly decrease the severity outcomes of COVID-19 (RR: 0.745; 95% CI: 0.580-0.956) Conclusions: Most of the evidence supports that the use of antidepressant medications, mainly Fluvoxamine may decrease the severity and improve the outcome in hospitalizes patients with sars-cov-2. Some studies showed contradictory findings regarding the effects of antidepressants on severity of COVID-19. Further experimental studies should be conducted to clarify the effects of antidepressants on severity of COVID-19.