Evidence map›Paper›PMID 39435304›Full record

ReviewOrthopedic research and reviews2024

3D Printing for Personalized Solutions in Cervical Spondylosis.

Li-Na Wu, Zhi-Feng Zhang, Ru-Jun Li, Da-Qi Xin, Jun-Feng Wang

Abstract readReview
In one paragraph

Review in Orthopedic research and reviews, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Li-Na WuOrthopaedic Clinical Research Center, The Second Affiliated Hospital of Inner Mongolia Medical University, Hohhot, Inner Mongolia Autonomous Region, People's Republic of China.
Zhi-Feng ZhangOrthopaedic Clinical Research Center, The Second Affiliated Hospital of Inner Mongolia Medical University, Hohhot, Inner Mongolia Autonomous Region, People's Republic of China.
Ru-Jun LiOrthopaedic Clinical Research Center, The Second Affiliated Hospital of Inner Mongolia Medical University, Hohhot, Inner Mongolia Autonomous Region, People's Republic of China.
Da-Qi XinOrthopaedic Clinical Research Center, The Second Affiliated Hospital of Inner Mongolia Medical University, Hohhot, Inner Mongolia Autonomous Region, People's Republic of China.
Jun-Feng WangOrthopaedic Clinical Research Center, The Second Affiliated Hospital of Inner Mongolia Medical University, Hohhot, Inner Mongolia Autonomous Region, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the context of the digital revolution, 3D printing technology brings innovation to the personalized treatment of cervical spondylosis, a clinically common degenerative disease that severely impacts the quality of life and increases the economic burden of patients. Although traditional surgeries, medications, and physical therapies are somewhat effective, they often fail` to meet individual needs, thus affecting treatment adherence and outcomes. 3D printing, with its customizability, precision, material diversity, and short production cycles, shows tremendous potential in the treatment of cervical spondylosis. This review discusses the multiple applications of 3D printing in the treatment of cervical spondylosis, including the design, manufacture, and advantages of 3D-printed cervical collars, the role of 3D models in clinical teaching and surgical simulation, and the application of 3D-printed scaffolds and implants in cervical surgery. It also discusses the current challenges and future directions.

Indexed as

3D printingbiomaterialscervical collarcervical spondylosisorthopedic implants

Identifiers

PMID39435304
PMCPMC11492914

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.