Background: Coronavirus disease 2019 (COVID-19) pandemic has drastically affected global health. Despite several studies, there is yet a dearth of data regarding the mechanisms of cardiac injury, clinical presentation, risk factors, and treatment of COVID-19-associated cardiovascular disease. This systematic review and meta-analysis is aimed at defining the clinical, electrocardiographic, and pathologic spectrum of cardiovascular disease (CVD), frequency of elevated cardiac and inflammatory biomarkers, and their frequency and relationship with severity of the disease and mortality in COVID-19 patients and to develop a triage risk stratification tool (TRST) that can serve as a guide for the timely recognition of the high-risk patients and mechanism-targeted therapy. We conducted an online search in databases of PubMed and Embase to identify relevant studies. Data selection was in concordance with PRISMA guidelines. Results were presented as pooled frequencies, odds ratio, standardized mean difference (SMD), and forest and funnel plots. Results: We gathered a total of 54 studies and included 35 of them in our meta-analysis. Acute cardiac injury occurred in more than 25% of cases, mortality was 20 times higher, and admission to intensive care unit increased by 13.5 times. Hypertension was the most common pre-existing comorbidity with a frequency of 29.2%, followed by diabetes mellitus (13.5%). The deceased group of patients had higher cardiac and inflammatory biomarkers, with statistically significant SMD, compared with survivors. Pediatric patients were predominantly mildly affected. However, less frequently, the presentation was very similar to Kawasaki disease or Kawasaki shock syndrome. This latter presentation hass been called as multisystem inflammatory syndrome in children (MIS-C). Conclusions: There is a wide spectrum of cardiac involvement in COVID-19 patients, and hence a Triage Risk Stratification Tool can serve as a guide for the timely recognition of the high-risk patients and mechanism-targeted therapy.

The cornerstone of this classification is elliptical LV geometry. Large-type IIc LVO have dismal prognosis, if left untreated. LVO type I and small LVO type IIa have the best prognosis.

Background In Iran, admission to medical school is based solely on the results of the highly competitive, nationwide Konkoor examination. This paper examines the predictive validity of Konkoor scores, alone and in combination with high school grade point averages (hsGPAs), for the academic performance of public medical school students in Iran. Methods This study followed the cohort of 2003 matriculants at public medical schools in Iran from entrance through internship. The predictor variables were Konkoor total and subsection scores and hsGPAs. The outcome variables were (1) Comprehensive Basic Sciences Exam (CBSE) scores; (2) Comprehensive Pre-Internship Exam (CPIE) scores; and (3) medical school grade point averages (msGPAs) for the courses taken before internship. Pearson correlation and regression analyses were used to assess the relationships between the selection criteria and academic performance. Results There were 2126 matriculants (1374 women and 752 men) in 2003. Among the outcome variables, the CBSE had the strongest association with the Konkoor total score ( r = 0.473), followed by msGPA ( r = 0.339) and the CPIE ( r = 0.326). While adding hsGPAs to the Konkoor total score almost doubled the power to predict msGPAs ( R 2 = 0.225), it did not have a substantial effect on CBSE or CPIE prediction. Conclusions The Konkoor alone, and even in combination with hsGPA, is a relatively poor predictor of medical students’ academic performance, and its predictive validity declines over the academic years of medical school. Care should be taken to develop comprehensive admissions criteria, covering both cognitive and non-cognitive factors, to identify the best applicants to become "good doctors" in the future. The findings of this study can be helpful for policy makers in the medical education field.