Evidence map›Paper›PMID 34887400›Full record

ArticleNature communications2021

Massive image-based single-cell profiling reveals high levels of circulating platelet aggregates in patients with COVID-19.

Masako Nishikawa, Hiroshi Kanno, Yuqi Zhou, Ting-Hui Xiao, Takuma Suzuki, Yuma Ibayashi, Jeffrey Harmon, Shigekazu Takizawa, Kotaro Hiramatsu, Nao Nitta and 14 more

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed
4.1field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

38 citing papers in PubMed, 79 citations in OpenAlex.

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  9. Quantifying Nuclear Structures of Digital Pathology Images Across Cancers Using Transport-Based Morphometry.Cytometry. Part A : the journal of the International Society for Analytical Cytology · 2025
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  11. Observational Analyses of Ex Vivo Native American Platelet Responses.International journal of molecular sciences · 2024
    Observational
  12. Article
  13. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

24 authors at 6 institutions in 3 countries.

Masako Nishikawa *Department of Clinical Laboratory Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, 113-0033, Japan.
Hiroshi Kanno *Department of Chemistry, The University of Tokyo, Tokyo, 113-0033, Japan.ORCID http://orcid.org/0000-0003-3340-9462
Yuqi Zhou *Department of Chemistry, The University of Tokyo, Tokyo, 113-0033, Japan.
Ting-Hui XiaoDepartment of Chemistry, The University of Tokyo, Tokyo, 113-0033, Japan. xiaoth@chem.s.u-tokyo.ac.jp.ORCID http://orcid.org/0000-0002-7339-152X
Takuma SuzukiDepartment of Computational Biology and Medical Sciences, The University of Tokyo, Chiba, 277-8562, Japan.
Yuma IbayashiDepartment of Chemistry, The University of Tokyo, Tokyo, 113-0033, Japan.
Jeffrey HarmonDepartment of Chemistry, The University of Tokyo, Tokyo, 113-0033, Japan.
Shigekazu TakizawaDepartment of Chemistry, The University of Tokyo, Tokyo, 113-0033, Japan.
Kotaro HiramatsuDepartment of Chemistry, The University of Tokyo, Tokyo, 113-0033, Japan.ORCID http://orcid.org/0000-0003-0767-019X
Nao NittaCYBO, Inc, Tokyo, 135-0064, Japan.ORCID http://orcid.org/0000-0002-9093-9016
Risako KameyamaDepartment of Chemistry, The University of Tokyo, Tokyo, 113-0033, Japan.
Walker PetersonDepartment of Chemistry, The University of Tokyo, Tokyo, 113-0033, Japan.
Jun TakiguchiDepartment of Clinical Laboratory Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, 113-0033, Japan.
Mohammad Shifat-E-RabbiDepartment of Biomedical Engineering, University of Virginia, Virginia, 22908, USA.
Yan ZhuangDepartment of Electrical and Computer Engineering, University of Virginia, Virginia, 22908, USA.
Xuwang YinDepartment of Electrical and Computer Engineering, University of Virginia, Virginia, 22908, USA.
Abu Hasnat Mohammad RubaiyatDepartment of Electrical and Computer Engineering, University of Virginia, Virginia, 22908, USA.
Yunjie DengDepartment of Chemistry, The University of Tokyo, Tokyo, 113-0033, Japan.
Hongqian ZhangDepartment of Chemistry, The University of Tokyo, Tokyo, 113-0033, Japan.
Shigeki MiyataResearch and Development Department, Central Blood Institute, Japanese Red Cross Society, Tokyo, 135-8521, Japan.
Gustavo K RohdeDepartment of Biomedical Engineering, University of Virginia, Virginia, 22908, USA.
Wataru IwasakiDepartment of Computational Biology and Medical Sciences, The University of Tokyo, Chiba, 277-8562, Japan.ORCID http://orcid.org/0000-0002-9169-9245
Yutaka YatomiDepartment of Clinical Laboratory Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, 113-0033, Japan. yatoyuta-tky@umin.ac.jp.ORCID http://orcid.org/0000-0003-1719-4297
Keisuke GodaDepartment of Chemistry, The University of Tokyo, Tokyo, 113-0033, Japan. goda@chem.s.u-tokyo.ac.jp.ORCID http://orcid.org/0000-0001-6302-6038
The University of Tokyo · JPUniversity of Virginia · USCYBO (Japan) · JPJapanese Red Cross Society, Japan · JPTokyo University of Information Sciences · JPTokyo University of Science · JP

Funding

Transport transforms for biomedical data modeling, estimation, and classificationR01GM130825 · NIGMS · UNIVERSITY OF VIRGINIA · PI Gustavo Kunde Rohde · 2019 to 2026
$2.8M
NIGMS NIH HHS R01 GM130825
6 · The paper itself

Abstract

A characteristic clinical feature of COVID-19 is the frequent incidence of microvascular thrombosis. In fact, COVID-19 autopsy reports have shown widespread thrombotic microangiopathy characterized by extensive diffuse microthrombi within peripheral capillaries and arterioles in lungs, hearts, and other organs, resulting in multiorgan failure. However, the underlying process of COVID-19-associated microvascular thrombosis remains elusive due to the lack of tools to statistically examine platelet aggregation (i.e., the initiation of microthrombus formation) in detail. Here we report the landscape of circulating platelet aggregates in COVID-19 obtained by massive single-cell image-based profiling and temporal monitoring of the blood of COVID-19 patients (n = 110). Surprisingly, our analysis of the big image data shows the anomalous presence of excessive platelet aggregates in nearly 90% of all COVID-19 patients. Furthermore, results indicate strong links between the concentration of platelet aggregates and the severity, mortality, respiratory condition, and vascular endothelial dysfunction level of COVID-19 patients.

Indexed as

Platelet AggregationSingle-Cell AnalysisCOVID-19FemaleHumansMaleMicroscopySex FactorsThrombosis

Identifiers

PMID34887400
PMCPMC8660840
OpenAlexW4200427314

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.