Background: Studies have suggested that there is increased risk of thromboembolism (TE) associated with coronavirus disease 2019 (COVID-19). However, overall arterial and venous TE rates of COVID-19 and effect of TE on COVID-19 mortality is unknown. Methods: We did a systematic review and meta-analysis of studies evaluating TE in COVID-19. We searched PubMed, Cochrane, and Embase for studies published up to June 12, 2020. Random effects models were used to produce summary TE rates and odds ratios (OR) of mortality in COVID-19 patients with TE compared to those without TE. Heterogeneity was quantified with I 2. Findings: Of 425 studies identified, 42 studies enrolling 8271 patients were included in the meta-analysis. Overall venous TE rate was 21% (95% CI:17À26%): ICU, 31% (95% CI: 23À39%). Overall deep vein thrombosis rate was 20% (95% CI: 13À28%): ICU, 28% (95% CI: 16À41%); postmortem, 35% (95% CI:15À57%). Overall pulmonary embolism rate was 13% (95% CI: 11À16%): ICU, 19% (95% CI:14À25%); postmortem, 22% (95% CI:16À28%). Overall arterial TE rate was 2% (95% CI: 1À4%): ICU, 5% (95%CI: 3À7%). Pooled mortality rate among patients with TE was 23% (95%CI:14À32%) and 13% (95% CI:6À22%) among patients without TE. The pooled odds of mortality were 74% higher among patients who developed TE compared to those who did not (OR, 1.74; 95%CI, 1.01À2.98; P = 0.04). Interpretation: TE rates of COVID-19 are high and associated with higher risk of death. Robust evidence from ongoing clinical trials is needed to determine the impact of thromboprophylaxis on TE and mortality risk of COVID-19. Funding: None.
We used existing data sources to describe the relationship between the amount of time physicians spend logged in to the EHR—both during daytime hours as well after clinic hours—and performance on a validated patient satisfaction survey. Our null hypothesis is that there is no relationship between increased time logged in to the EHR and patient satisfaction.
Accessing and integrating human genomic data with phenotypes is important for biomedical research. Making genomic data accessible for research purposes, however, must be handled carefully to avoid leakage of sensitive individual information to unauthorized parties and improper use of data. In this article, we focus on data sharing within the scope of data accessibility for research. Current common practices to gain biomedical data access are strictly rule based, without a clear and quantitative measurement of the risk of privacy breaches. In addition, several types of studies require privacy-preserving linkage of genotype and phenotype information across different locations (e.g., genotypes stored in a sequencing facility and phenotypes stored in an electronic health record) to accelerate discoveries. The computer science community has developed a spectrum of techniques for data privacy and confidentiality protection, many of which have yet to be tested on real-world problems. In this article, we discuss clinical, technical, and ethical aspects of genome data privacy and confidentiality in the United States, as well as potential solutions for privacy-preserving genotype–phenotype linkage in biomedical research.
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