Pericardial fat and cardiovascular diseases: A systematic review and meta-analysis.

OBJECTIVE: Previous studies investigated the effect of pericardial fat on cardiovascular diseases. However, until now there was no systematic review and meta-analysis investigated this association, thus we conducted this article to assess the relationship between pericardial fat and cardiovascular diseases. METHODS: We searched PubMed, The Cochrane Library, Scopus, Google Scholar and Clinicaltrials.gov to select observational studies reported the relationship between pericardial fat and cardiovascular diseases including coronary artery disease (CAD), ventricular dysfunction, heart failure (HF), atrial fibrillation (AF), major adverse cardiac events (MACE), coronary artery calcifications (CAC), arrhythmias other than atrial fibrillation, and cardiovascular events prediction scores. Meta XL 5.3 was used for data analysis. RESULTS: A total of 83 articles that included 73,934 patients were included in our analysis. The results showed that pericardial fat was significantly associated with CAD (OR = 1.38; 95% CI: 1.28-1.50), ventricular dysfunction (OR = 1.53 per 1 mm3 ; 95% CI: 1.17-2.01), HF (OR = 1.32 per 1 mm3 ; 95% CI: 1.23-1.41), AF (OR = 1.16 per 1 mm3 ; 95% CI: 1.09-1.24), MACE (OR = 1.39 per 1 mm3 ; 95% CI: 1.22-1.57), and CAC (OR = 1.15 per 1 mm3 ; 95% CI: 1.05-1.27). On the other hand, there was no enough data about the relationship between pericardial fat with arrhythmias other than atrial fibrillation or cardiovascular risk scores. CONCLUSION: The analysis demonstrated that the relationship between pericardial fat volume and cardiovascular diseases was significant. Since pericardial fat is a good predictor of obesity, it suggests investigating its relationship and adds on effect to previously established risk factor to evaluate the possibility of incorporating it with cardiovascular risk scores.

The delaying of elective surgeries after COVID-19 infection decreases postoperative complications.

BACKGROUND: Huge controversy surrounds delaying elective surgeries after COVID-19 infection. Although two studies evaluated the issue, several gaps still exist. METHODS: A propensity score matched retrospective single center cohort design was used to evaluate the optimum time of delaying elective surgeries after COVID-19 infection and the validity of the current ASA guidelines in this regard. The exposure of interest was a previous COVID-19 infection. The primary composite included the incidence of death, unplanned Intensive Care Unit admission or postoperative mechanical ventilation. The secondary composite included the occurrence of pneumonia, acute respiratory distress, or venous thromboembolic. RESULTS: The total number of patients was 774, half of them had a history of COVID-19 infection. The analysis revealed that delaying surgeries for 4 weeks was associated with significant reduction in primary composite (AOR = 0.02; 95%CI: 0.00-0.33) and the length of hospital stay (B = 3.05; 95%CI: 0.41-5.70). Furthermore, before implementing the ASA guidelines in our hospital, a significant higher risk for the primary composite (AOR = 15.15; 95%CI: 1.84-124.44; P-value = 0.011) was observed compared to after applying it. CONCLUSION: Our study showed that the optimum period of delaying elective surgery after COVID-19 infection is four weeks, with no further benefits from waiting for longer times. This finding provide further support to the current ASA guidelines about delaying elective surgeries. Further large-scale prospective studies are needed to give more evidence-based support to the appropriateness of the 4-week waiting time for elective surgeries after COVID-19 infection and to investigate the effect of type of surgery on the required delay.

Efficacy and safety of COVID-19 vaccines: A network meta-analysis.

OBJECTIVE: Several vaccines showed a good safety profile and significant efficacy against COVID-19. Moreover, in the absence of direct head to head comparison between COVID-19 vaccines, a network meta-analysis that indirectly compares between them is needed. METHODS: Databases PubMed, CENTRAL, medRxiv, and clinicaltrials.gov were searched. Studies were included if they were placebo-controlled clinical trials and reported the safety profile and/or effectiveness of COVID-19 vaccines. The quality of the included studies was assessed using the Revised Cochrane risk-of-bias tool for randomized trials and the Revised Cochrane risk-of-bias tool for nonrandomized trials. RESULTS: Forty-nine clinical trials that included 421,173 participants and assessed 28 vaccines were included in this network meta-analysis. The network meta-analysis showed that Pfizer is the most effective in preventing COVID-19 infection whereas the Sputnik Vaccine was the most effective in preventing severe COVID-19 infection. In terms of the local and systemic side, the Sinopharm and V-01 vaccines were the safest. CONCLUSION: We found that almost all of the vaccines included in this study crossed the threshold of 50% efficacy. However, some of them did not reach the previously mentioned threshold against the B.1.351 variant while the remainder have not yet investigated vaccine efficacy against this variant. Since each vaccine has its own strong and weak points, we strongly advocate continued vaccination efforts in individualized manner that recommend the best vaccine for each group in the community which is abundantly required to save lives and to avert the emergence of future variants.

Quality of Distance Learning After One and a Half Year From Its Integration Due to the COVID-19 Pandemic: A Cross-Sectional Study at the University of Jordan.

Background The coronavirus disease 2019 (COVID-19) pandemic mandated the change from face-to-face learning to distance learning. As a result, the quality of distance learning worldwide is questionable. Objectives and aims The aim of this study is to investigate the quality of distance learning among university students at the University of Jordan, as well as its determinants and obstacles. Methods A questionnaire-based cross-sectional study was conducted among undergraduate students at the University of Jordan from May 29 to July 11, 2021. Using a quantitative approach, students' attitudes toward and perceptions of online and distance education were analyzed. The Distance Education Learning Environments Survey (DELES) tool was used to evaluate the quality of distance learning during COVID-19 pandemic. IBM SPSS Version 25 was used for data analysis. Results The total number of participants was 486, and the mean total DELES score was 61.6 ± 24.6. The lowest mean of DELES score components was for the active learning component (6.9 ± 2.9). Moreover, 65.9% of the students were very dissatisfied or dissatisfied with the quality of distance learning. The quality of distance learning derived by the total DELES score was determined by several general demographics, and students' perceptions and attitudes. Conclusions The present study showed a low quality of distance learning and high levels of dissatisfaction among students at the University of Jordan. Thus, improvement of distance learning quality by filling its infrastructural defects and the implementation of its adjunct tools are required. In addition, we recommend collaboration with regional and international educational institutions to improve the quality of distance learning.