Evidence map›Paper›PMID 23372761›Full record

ArticlePloS one2013

From principle to practice: bridging the gap in patient profiling.

Jonathan H Foley, Thomas Orfeo, Anetta Undas, Kelley C McLean, Ira M Bernstein, Georges-Etienne Rivard, Kenneth G Mann, Stephen J Everse, Kathleen E Brummel-Ziedins

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.6field-weighted citation impact, top 17% 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

5 citing papers in PubMed, 11 citations in OpenAlex.

  1. Synthetic data in medicine: Legal and ethical considerations for patient profiling.Computational and structural biotechnology journal · 2025
    Article
  2. Article
  3. Article
  4. Global assays of hemostasis.Current opinion in hematology · 2014
    Review
  5. Modeling thrombin generation: plasma composition based approach.Journal of thrombosis and thrombolysis · 2014
    Review
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

9 authors at 3 institutions in 3 countries.

Jonathan H FoleyDepartment of Biochemistry, University of Vermont, Burlington, Vermont, United States of America.
Thomas Orfeo
Anetta Undas
Kelley C McLean
Ira M Bernstein
Georges-Etienne Rivard
Kenneth G Mann
Stephen J Everse
Kathleen E Brummel-Ziedins
University of Vermont · USCentre Hospitalier Universitaire Sainte-Justine · CAJagiellonian University · PL

Funding

VENOUS THROMBOEMBOLISM: GENES, RISK, MANAGEMENTP01HL046703 · NHLBI · UNIVERSITY OF VERMONT &ST AGRIC COLLEGE · PI BRUMMEL-ZIEDINS, KATHLEEN E · 1991 to 2011
$19.8M
Prepregnancy Phenotype &Predisposition to Pre-eclampsiaR01HL071944 · NHLBI · UNIVERSITY OF VERMONT &ST AGRIC COLLEGE · PI BERNSTEIN, IRA MARK · 2004 to 2014
$3.0M
NHLBI NIH HHS HL 71944NHLBI NIH HHS P01 HL046703NHLBI NIH HHS R01 HL071944PHS HHS HL46703-PROJECT 5
6 · The paper itself

Abstract

The standard clinical coagulation assays, activated partial thromboplastin time (aPTT) and prothrombin time (PT) cannot predict thrombotic or bleeding risk. Since thrombin generation is central to haemorrhage control and when unregulated, is the likely cause of thrombosis, thrombin generation assays (TGA) have gained acceptance as "global assays" of haemostasis. These assays generate an enormous amount of data including four key thrombin parameters (lag time, maximum rate, peak and total thrombin) that may change to varying degrees over time in longitudinal studies. Currently, each thrombin parameter is averaged and presented individually in a table, bar graph or box plot; no method exists to visualize comprehensive thrombin generation data over time. To address this need, we have created a method that visualizes all four thrombin parameters simultaneously and can be animated to evaluate how thrombin generation changes over time. This method uses all thrombin parameters to intrinsically rank individuals based on their haemostatic status. The thrombin generation parameters can be derived empirically using TGA or simulated using computational models (CM). To establish the utility and diverse applicability of our method we demonstrate how warfarin therapy (CM), factor VIII prophylaxis for haemophilia A (CM), and pregnancy (TGA) affects thrombin generation over time. The method is especially suited to evaluate an individual's thrombotic and bleeding risk during "normal" processes (e.g pregnancy or aging) or during therapeutic challenges to the haemostatic system. Ultimately, our method is designed to visualize individualized patient profiles which are becoming evermore important as personalized medicine strategies become routine clinical practice.

Indexed as

Blood CoagulationModels, BiologicalAdolescentAdultAgedAnticoagulantsAtrial FibrillationComputer SimulationFactor VIIIFemaleHemophilia AHumansKineticsMaleMiddle AgedPregnancyAnticoagulantsFactor VIIIProtein CThrombinWarfarin

Identifiers

PMID23372761
PMCPMC3556038
OpenAlexW2037870947

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.