Evidence map›Paper›PMID 38927117›Full record

ReviewBiomolecules2024

Advances in Platelet-Dysfunction Diagnostic Technologies.

Inkwon Yoon, Jong Hyeok Han, Hee-Jae Jeon

Abstract readReview
In one paragraph

Review in Biomolecules, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Trial
  2. Review
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Innovative Diagnostic Solutions in Hemostasis.Diagnostics (Basel, Switzerland) · 2024
    Review
  13. Review
  14. 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

3 authors.

Inkwon YoonDepartment of Smart Health Science and Technology, Kangwon National University, Chuncheon 24341, Republic of Korea.
Jong Hyeok HanDepartment of Smart Health Science and Technology, Kangwon National University, Chuncheon 24341, Republic of Korea.
Hee-Jae JeonDepartment of Smart Health Science and Technology, Kangwon National University, Chuncheon 24341, Republic of Korea.

Funding

Korea and Regional Innovation Strategy (RIS) 2022RIS-005the IITP and funded by the Ministry of Science and ICT (MSIT) IITP-2023-RS-2023-00260267the National Research Foundation of Korea (NRF) grant RS-2023-00213379
6 · The paper itself

Abstract

The crucial role of platelets in hemostasis and their broad implications under various physiological conditions underscore the importance of accurate platelet-function testing. Platelets are key to clotting blood and healing wounds. Therefore, accurate diagnosis and management of platelet disorders are vital for patient care. This review outlines the significant advancements in platelet-function testing technologies, focusing on their working principles and the shift from traditional diagnostic methods to more innovative approaches. These improvements have deepened our understanding of platelet-related disorders and ushered in personalized treatment options. Despite challenges such as interpretation of complex data and the costs of new technologies, the potential for artificial-intelligence integration and the creation of wearable monitoring devices offers exciting future possibilities. This review underscores how these technological advances have enhanced the landscape of precision medicine and provided better diagnostic and treatment options for platelet-function disorders.

Indexed as

Blood Platelet DisordersBlood PlateletsPlatelet Function TestsHemostasisHumansPrecision Medicineclottinghemostasisplatelet aggregationplatelet function testpoint-of-care testing

Identifiers

PMID38927117
PMCPMC11201885

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.