Evidence map›Paper›PMID 25025009›Full record

ReviewBlood research2014

Hypercoagulable states: an algorithmic approach to laboratory testing and update on monitoring of direct oral anticoagulants.

Megan O Nakashima, Heesun J Rogers

Open access · hybridAbstract readReview
In one paragraph

Review in Blood research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed, 1 pooled it
2.6field-weighted citation impact, top 9% 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

44 citing papers in PubMed, 1 synthesis or guideline pooled it, 101 citations in OpenAlex.

  1. Pediatric APS: State of the Art.Current rheumatology reports · 2020
    Pooled it
  2. Trial
  3. Article
  4. Persistent hypercoagulability and acute limb ischemia post COVID-19.Journal of vascular surgery cases and innovative techniques · 2025
    Article
  5. Review
  6. Article
  7. Article
  8. Review
  9. Article
  10. Thromboembolism in Children: Unveiling Risk-Factors.Indian journal of pediatrics · 2024
    Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
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  19. 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

2 authors at 1 institution in 1 country.

Megan O NakashimaDepartment of Laboratory Medicine, Cleveland Clinic, Cleveland, OH, United States.
Heesun J RogersDepartment of Laboratory Medicine, Cleveland Clinic, Cleveland, OH, United States.
Cleveland Clinic · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hypercoagulability can result from a variety of inherited and, more commonly, acquired conditions. Testing for the underlying cause of thrombosis in a patient is complicated both by the number and variety of clinical conditions that can cause hypercoagulability as well as the many potential assay interferences. Using an algorithmic approach to hypercoagulability testing provides the ability to tailor assay selection to the clinical scenario. It also reduces the number of unnecessary tests performed, saving cost and time, and preventing potential false results. New oral anticoagulants are powerful tools for managing hypercoagulable patients; however, their use introduces new challenges in terms of test interpretation and therapeutic monitoring. The coagulation laboratory plays an essential role in testing for and treating hypercoagulable states. The input of laboratory professionals is necessary to guide appropriate testing and synthesize interpretation of results.

Indexed as

Algorithmic approachAntiphospholipid syndromeDirect oral anticoagulantHypercoagulabilityVenous thromboembolism

Identifiers

PMID25025009
PMCPMC4090343
OpenAlexW2102537270

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.