Evidence map›Paper›PMID 33948306›Full record

ReviewBio-design and manufacturing2021

Three-dimensional printing for heart diseases: clinical application review.

Yanyan Ma, Peng Ding, Lanlan Li, Yang Liu, Ping Jin, Jiayou Tang, Jian Yang

Abstract readReview
In one paragraph

Review in Bio-design and manufacturing, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Polysaccharide-based biomaterials in a journey from 3D to 4D printing.Bioengineering & translational medicine · 2023
    Review
  11. Review
  12. Article
  13. Review
  14. Review
  15. 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

7 authors.

Yanyan MaDepartment of Cardiovascular Surgery, Xijing Hospital, Airforce Medical University, Xi'an, 710032 China.
Peng DingDepartment of Cardiovascular Surgery, Xijing Hospital, Airforce Medical University, Xi'an, 710032 China.
Lanlan LiDepartment of Cardiovascular Surgery, Xijing Hospital, Airforce Medical University, Xi'an, 710032 China.
Yang LiuDepartment of Cardiovascular Surgery, Xijing Hospital, Airforce Medical University, Xi'an, 710032 China.
Ping JinDepartment of Cardiovascular Surgery, Xijing Hospital, Airforce Medical University, Xi'an, 710032 China.
Jiayou TangDepartment of Cardiovascular Surgery, Xijing Hospital, Airforce Medical University, Xi'an, 710032 China.
Jian YangDepartment of Cardiovascular Surgery, Xijing Hospital, Airforce Medical University, Xi'an, 710032 China.ORCID 0000-0003-2059-1912

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Heart diseases remain the top threat to human health, and the treatment of heart diseases changes with each passing day. Convincing evidence shows that three-dimensional (3D) printing allows for a more precise understanding of the complex anatomy associated with various heart diseases. In addition, 3D-printed models of cardiac diseases may serve as effective educational tools and for hands-on simulation of surgical interventions. We introduce examples of the clinical applications of different types of 3D printing based on specific cases and clinical application scenarios of 3D printing in treating heart diseases. We also discuss the limitations and clinically unmet needs of 3D printing in this context.

Indexed as

Cardiac imaging techniquesCongenital heart diseaseHeart diseasesThree-dimensional printingTranscatheter aortic valve replacement

Identifiers

PMID33948306
PMCPMC8085656

What OpenQuestion holds

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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.