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Prothrombotic autoantibodies in serum from patients hospitalized with COVID-19

Overview of attention for article published in Science Translational Medicine, November 2020
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#29 of 4,370)
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Mentioned by

news
44 news outlets
blogs
6 blogs
twitter
964 tweeters
facebook
4 Facebook pages
reddit
5 Redditors
video
1 video uploader

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
5 Mendeley
Title
Prothrombotic autoantibodies in serum from patients hospitalized with COVID-19
Published in
Science Translational Medicine, November 2020
DOI 10.1126/scitranslmed.abd3876
Pubmed ID
Authors

Yu Zuo, Shanea K. Estes, Ramadan A. Ali, Alex A. Gandhi, Srilakshmi Yalavarthi, Hui Shi, Gautam Sule, Kelsey Gockman, Jacqueline A. Madison, Melanie Zuo, Vinita Yadav, Jintao Wang, Wrenn Woodard, Sean P. Lezak, Njira L. Lugogo, Stephanie A. Smith, James H. Morrissey, Yogendra Kanthi, Jason S. Knight

Abstract

Patients with COVID-19 are at high risk for thrombotic arterial and venous occlusions. Lung histopathology often reveals fibrin-based occlusions in the small blood vessels of patients who succumb to the disease. Antiphospholipid syndrome is an acquired and potentially life-threatening thrombophilia in which patients develop pathogenic autoantibodies targeting phospholipids and phospholipid-binding proteins (aPL antibodies). Case series have recently detected aPL antibodies in patients with COVID-19. Here, we measured eight types of aPL antibodies in serum samples from 172 patients hospitalized with COVID-19. These aPL antibodies included anticardiolipin IgG, IgM and IgA; anti-β2 glycoprotein I IgG, IgM, and IgA; and anti-phosphatidylserine/ prothrombin (aPS/PT) IgG and IgM. We detected aPS/PT IgG in 24% of serum samples, anticardiolipin IgM in 23% of samples, and aPS/PT IgM in 18% of samples. Antiphospholipid autoantibodies were present in 52% of serum samples using the manufacturer's threshold and in 30% using a more stringent cutoff (≥40 ELISA-specific units). Higher titers of aPL antibodies were associated with neutrophil hyperactivity including the release of neutrophil extracellular traps (NETs), higher platelet counts, more severe respiratory disease, and lower clinical estimated glomerular filtration rate. Similar to IgG from patients with antiphospholipid syndrome, IgG fractions isolated from COVID-19 patients promoted NET release from neutrophils isolated from healthy individuals. Furthermore, injection of IgG purified from COVID-19 patient serum into mice accelerated venous thrombosis in two mouse models. These findings suggest that half of patients hospitalized with COVID-19 become at least transiently positive for aPL antibodies and that these autoantibodies are potentially pathogenic.

Twitter Demographics

The data shown below were collected from the profiles of 964 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 2 40%
Professor 1 20%
Researcher 1 20%
Student > Ph. D. Student 1 20%
Readers by discipline Count As %
Unspecified 3 60%
Biochemistry, Genetics and Molecular Biology 1 20%
Immunology and Microbiology 1 20%

Attention Score in Context

This research output has an Altmetric Attention Score of 1009. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 December 2020.
All research outputs
#6,864
of 16,342,103 outputs
Outputs from Science Translational Medicine
#29
of 4,370 outputs
Outputs of similar age
#514
of 328,709 outputs
Outputs of similar age from Science Translational Medicine
#2
of 103 outputs
Altmetric has tracked 16,342,103 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,370 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 66.7. This one has done particularly well, scoring higher than 99% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 328,709 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 103 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 98% of its contemporaries.