Evidence map›Paper›PMID 36407161›Full record

ArticleCureus2022

Treatment With EkoSonic™ Endovascular System (EKOS®) of Massive Pulmonary Thrombosis Following Recovery From COVID-19 Infection.

Ugur Cetingok, Cayan Akkoyun, Zulkuf Isik, Orhan Gungor

Open access · diamondAbstract readCase Reports
In one paragraph

Article in Cureus, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 73% 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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

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

4 authors at 3 institutions in 1 country.

Ugur CetingokDepartment of Cardiovascular Surgery, Alanya Anadolu Hospital, Antalya, TUR.
Cayan AkkoyunDepartment of Cardiology, Uzmanlar Hospital, Yalova, TUR.
Zulkuf IsikDepartment of Pulmonology, Atakent Hospital, Yalova, TUR.
Orhan GungorDepartment of Cardiovascular Surgery, Cesme Public Hospital, Izmir, TUR.
Yalova University · TRAcıbadem University Atakent Hospital · TRAlanya Hamdullah Emin Pasa University · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

COVID-19 infection caused by the new coronavirus called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an infection with symptoms and results ranging from mild flu-like symptoms to severe respiratory failure leading to death. The risk of thrombosis increases due to hypercoagulation in COVID-19 infection. All causes (endothelial injury, stasis, and hypercoagulopathy) known as Virchow's triad contribute to thrombosis in COVID-19 infection. However, the pathogenesis of hypercoagulability in COVID-19 is still unknown. In this article, we discuss the unique multiple thrombosis events following recovery from COVID-19 infection and our treatment strategy for pulmonary thrombosis. The patient had symptoms of dry cough, fever, and myalgia two months ago. His polymerase chain reaction (PCR) test for COVID-19 was positive, but there was no need for hospitalization. His symptoms resolved within seven days. But, thrombosis of the superior mesenteric artery (SMA) occurred one month after the COVID-19 infection, and bowel resection was performed. He was admitted to our hospital with dyspnea, chest pain, palpitations, and hoarseness. Further evaluation showed tachycardia, hypotension, tachypnea, and anxiety. Peripheral oxygen saturation (SpO

Indexed as

accelerated thrombolysiscovid-19 infectionekos catheterpulmonary artery thrombosispulmonary embolism (pe)systemic thrombolysis

Identifiers

PMID36407161
PMCPMC9673463
OpenAlexW4306789981

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.