Evidence map›Paper›PMID 35090739›Full record

ArticleSurgery2022

Rotational thromboelastometry in patients with acute respiratory distress syndrome owing to coronavirus disease 2019: Is there a viscoelastic fingerprint and a role for predicting thrombosis?

Ljiljana V Vasovic, James Littlejohn, Dalia Alqunaibit, Alicia Dillard, Yuqing Qiu, Sophie Rand, Matthew Bronstein, Cameron J Gibson, Anton G Kelly, Christina Lee and 8 more

Open access · bronzeAbstract read
In one paragraph

Article in Surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 39% 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

1 citing paper in PubMed, 6 citations in OpenAlex.

  1. Article
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

18 authors at 1 institution in 1 country.

Ljiljana V VasovicDepartment of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY.
James LittlejohnDepartment of Anesthesiology, Weill Cornell Medicine, New York, NY. Electronic address: jel9088@med.cornell.edu.
Dalia AlqunaibitDepartment of Surgery, Weill Cornell Medicine New York, NY.
Alicia DillardDepartment of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY.
Yuqing QiuDepartment of Population Health Sciences, Weill Cornell Medicine, New York, NY.
Sophie RandDepartment of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY.
Matthew BronsteinDepartment of Surgery, Weill Cornell Medicine New York, NY.
Cameron J GibsonDepartment of Surgery, Weill Cornell Medicine New York, NY.
Anton G KellyDepartment of Surgery, Weill Cornell Medicine New York, NY.
Christina LeeDepartment of Surgery, Weill Cornell Medicine New York, NY.
Jennifer A MinnemanDepartment of Surgery, Weill Cornell Medicine New York, NY.
Mayur NarayanDepartment of Surgery, Weill Cornell Medicine New York, NY.
Jian ShouDepartment of Surgery, Weill Cornell Medicine New York, NY.
Kira E SmithDepartment of Surgery, Weill Cornell Medicine New York, NY.
Cassandra V VillegasDepartment of Surgery, Weill Cornell Medicine New York, NY.
Robert J WinchellDepartment of Surgery, Weill Cornell Medicine New York, NY.
Melissa M CushingDepartment of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY.
Philip S BarieDepartment of Surgery, Weill Cornell Medicine New York, NY; Department of Medicine, Weill Cornell Medicine, New York, NY.
Cornell University · US

Funding

Clinical and Translational Science CenterUL1TR000457 · NCATS · WEILL MEDICAL COLL OF CORNELL UNIV · PI IMPERATO-MCGINLEY, JULIANNE L · 2012 to 2016
$46.0M
NCATS NIH HHS UL1 TR000457
6 · The paper itself

Abstract

objectivesWe evaluated rotational thromboelastometry tracings in 44 critically ill coronavirus disease 2019 patients, to determine whether there is a viscoelastic fingerprint and to test the hypothesis that the diagnosis and prediction of venous thromboembolism would be enhanced by the addition of rotational thromboelastometry testing.

resultsRotational thromboelastometry values reflected an increase in clot strength for the EXTEM, INTEM, and FIBTEM assays beyond the reference range. No hyperfibrinolysis was noted. Fibrinolysis shutdown was present but did not correlate with thrombosis; 32% (14/44) of patients experienced a thrombotic episode. For every 1 mm increase of FIBTEM maximum clot formation, the odds of developing thrombosis increased 20% (95% confidence interval, 0-40%, P = .043), whereas for every 1,000 ng/mL increase in D-dimer, the odds of thrombosis increased by 70% (95% confidence interval, 20%-150%, P = .004), after adjustment for age and sex (AUC 0.96, 95% confidence interval, 0.90-1.00). There was a slight but significant improvement in model performance after adding FIBTEM maximum clot formation and EXTEM clot formation time to D-dimer in a multivariable model (P = .04).

conclusionsD-dimer concentrations were more predictive of thrombosis in our patient population than any other parameter. Rotational thromboelastometry confirmed the hypercoagulable state of coronavirus disease 2019 intensive care unit patients. FIBTEM maximum clot formation and EXTEM clot formation time increased the predictability for thrombosis compared with only using D-dimer. Rotational thromboelastometry analysis is most useful in augmenting the information provided by the D-dimer concentration for venous thromboembolism risk assessment when the D-dimer concentration is between 1,625 and 6,900 ng/dL, but the enhancement is modest. Fibrinolysis shutdown did not correlate with thrombosis.

Indexed as

COVID-19Respiratory Distress SyndromeThrombophiliaThrombosisHumansThrombelastography

Identifiers

PMID35090739
PMCPMC8426191
OpenAlexW3199786728

What OpenQuestion holds

Textmetadata
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.