Evidence map›Paper›PMID 37744247›Full record

ReviewFrontiers in bioengineering and biotechnology2023

Biomaterials-based additive manufacturing for customized bioengineering in management of otolaryngology: a comprehensive review.

Jigar Vyas, Isha Shah, Sudarshan Singh, Bhupendra G Prajapati

Abstract readReview
In one paragraph

Review in Frontiers in bioengineering and biotechnology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. 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

4 authors.

Jigar VyasSigma Institute of Pharmacy, Vadodara, Gujarat, India.
Isha ShahSigma Institute of Pharmacy, Vadodara, Gujarat, India.
Sudarshan SinghDepartment of Pharmaceutical Sciences, Faculty of Pharmacy, Chiang Mai University, Chiang Mai, Thailand.
Bhupendra G PrajapatiShree S. K. Patel College of Pharmaceutical Education and Research, Ganpat University, Kherva, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Three-dimensional (3D)/four-dimensional (4D) printing, also known as additive manufacturing or fast prototyping, is a manufacturing technique that uses a digital model to generate a 3D/4D solid product. The usage of biomaterials with 3D/4D printers in the pharma and healthcare industries is gaining significant popularity. 3D printing has mostly been employed in the domain of otolaryngology to build portable anatomical models, personalized patient-centric implants, biologic tissue scaffolds, surgical planning in individuals with challenging conditions, and surgical training. Although identical to 3D printing technology in this application, 4D printing technology comprises a fourth dimension of time. With the use of 4D printing, a printed structure may alter over time under various stimuli. Smart polymeric materials are also generally denoted as bioinks are frequently employed in tissue engineering applications of 3D/4D printing. In general, 4D printing could significantly improve the safety and efficacy of otolaryngology therapies. The use of bioprinting in otolaryngology has an opportunity to transform the treatment of diseases influencing the ear, nose, and throat as well as the field of tissue regeneration. The present review briefs on polymeric material including biomaterials and cells used in the manufacturing of patient centric 3D/4D bio-printed products utilized in management of otolaryngology.

Indexed as

additive manufacturingbiomaterialsbioprintingfour-dimensional printingotolaryngologythree dimensional printing

Identifiers

PMID37744247
PMCPMC10515088

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.