Evidence map›Paper›PMID 33560947›Full record

ArticleClinical practice and cases in emergency medicine2021

Where There's Smoke, There's Fire: A Case Report of Turbulent Blood Flow in Lower Extremity Point-of-care Ultrasound in COVID-19.

Mathew Nelson, Dorothy Shi, Miles Gordon, Yash Chavda, Christina Grimaldi, Tanya Bajaj

Abstract read
In one paragraph

Article in Clinical practice and cases in emergency medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Article
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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

6 authors.

Mathew NelsonNorth Shore University Hospital, Department of Emergency Medicine, Manhasset, New York.
Dorothy ShiNorth Shore University Hospital, Department of Emergency Medicine, Manhasset, New York.
Miles GordonNorth Shore University Hospital, Department of Emergency Medicine, Manhasset, New York.
Yash ChavdaNorth Shore University Hospital, Department of Emergency Medicine, Manhasset, New York.
Christina GrimaldiNorth Shore University Hospital, Department of Emergency Medicine, Manhasset, New York.
Tanya BajajNorth Shore University Hospital, Department of Emergency Medicine, Manhasset, New York.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionCoronavirus disease 2019 (COVID-19) may predispose patients to increased risk of venous thromboembolism (VTE) due to various pathophysiological mechanisms, including but not limited to endothelial injury, inflammation, cytokine-mediated microvascular damage, and reactive thrombocytosis. A high risk of vessel thrombosis correlates with disease severity, making early identification and treatment of prime consideration.Although identification of a deep venous thrombosis (DVT) or pulmonary embolism warrants immediate treatment with anticoagulation, trying to predict which COVID-19 patients may be at increased risk for developing these pathologies is challenging. CASE REPORTS: We present two cases of patients with COVID-19 who had ultrasonographic findings of turbulent blood flow within the deep venous system, without clear evidence of acute proximal DVT, who were subsequently found to have significant VTE.

conclusionPoint-of-care lower extremity ultrasound has become one of the core applications used by emergency physicians. Typically we perform compression ultrasound for DVT evaluation. This novel finding of turbulent blood flow, or "smoke," within the deep venous system, may serve as a marker of increased risk of clot development and could be an indication to consider early anticoagulation.

Identifiers

PMID33560947
PMCPMC7872592

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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.