Tonnesen Jochumsen (stopcoil0)

Electrocardiographic (ECG) findings in patients admitted with COVID-19 and a decision tree to predict their survival were assessed. 145 consecutive patients with severe COVID-19 infection were selected. Patient demographics, ECG variables, peak troponins, use of standard medications, and clinical outcomes were analyzed using descriptive and inferential statistics, and a predictive model of survival was developed using classification tree analysis. Of the 145 admitted patients, 38 (26%) died. Deceased patients were more likely to have a significantly higher incidence of poor R-Wave progression [6 of 37 (16.2%) Vs. 0 of 104 (0%), p less then 0.001] as well as prolonged QTc values [24 of 37 (64.9%) Vs. 38 of 99 (38.4%), p 0.006]. Significant ST segment depressions were found in 5 of 37 (13.5%) of the deceased category compared to 0% in the non-deceased (p less then 0.01). Right and/or left atrial enlargement was more prevalent in the deceased cohort [7 of 37 (18.9%) Vs. 4 of 104 (3.8%), p = 0.03]. Bundle branch blocks were more prevalent in the deceased group [9 of 35 (25.8%) Vs. 7 of 104 (6.7%), p 0.002]. Peak troponins were significantly higher in the deceased group (1.0 Vs 0.07 ng/ml, p less then 0.001) A prediction tree built utilizing age, PACs, troponins and QTc had an accuracy of 85.5%. 65 of 74 patients (87.8%) were correctly predicted to survive, while 23 of 29 (79.3%) were correctly predicted to become deceased. Among patients hospitalized with Covid-19, the parameters of age, QT interval, troponin and PACs are useful for prognostication and help predict survival with reasonable accuracy. To assess the reporting and methodological quality of COVID-19 systematic reviews, and to analyze trends and gaps in the quality, clinical topics, author countries, and populations of the reviews using an evidence mapping approach. A structured search for systematic reviews concerning COVID-19 was performed using PubMed, Embase, Cochrane Library, Campbell Library, Web of Science, CBM, WanFang Data, CNKI, and CQVIP from inception until June 2020. The quality of each review was assessed using the Assessment of Multiple Systematic Reviews 2 (AMSTAR 2) checklist and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist. In total, 243 systematic reviews met the inclusion criteria, over 50% of which (128, 52.7%) were from 14 developing countries, with China contributing the most reviews (76, 31.3%). In terms of methodological quality of the studies, 30 (12.3%) were of moderate quality, 63 (25.9%) were of low quality, and 150 (61.7%) were of critically low quality. In terms of reporting quality, the median (interquartile range) PRISMA score was 14 (10-18). Regarding the topics of the reviews, 24 (9.9%) focused on the prevalence of COVID-19, 69 (28.4%) focused on the clinical manifestations, 30 (12.3%) focused on etiology, 43 (17.7%) focused on diagnosis, 65 (26.7%) focused on treatment, 104 (42.8%) focused on prognosis, and 25 (10.3%) focused on prevention. These studies mainly focused on general patients with COVID-19 (161, 66.3%), followed by children (22, 9.1%) and pregnant patients (18, 7.4%). This study systematically evaluated the methodological and reporting quality of systematic reviews of COVID-19, summarizing and analyzing trends in their clinical topics, author countries, and study populations. This study systematically evaluated the methodological and reporting quality of systematic reviews of COVID-19, summarizing and analyzing trends in their clinical topics, author countries, and study populations.Bacterial infections and the formation of biofilms on the surface of implantable medical devices are critical issues that cause device failure. Implantable medical devices, such as drug delivery technologies, offer promising benefits for targeted and prolonged drug release, but a number of common disadvantages arise that include inadequate release and