Evidence map›Paper›PMID 35142105›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2022

Laser Direct-Write Sensors on Carbon-Fiber-Reinforced Poly-Ether-Ether-Ketone for Smart Orthopedic Implants.

Xingjian Hu, Jincai Huang, Yanzhuo Wei, Haiyan Zhao, Shize Lin, Chuxiong Hu, Ze Wang, Zhe Zhao, Xining Zang

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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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

9 authors.

Xingjian HuDepartment of Mechanical Engineering, Tsinghua University, Beijing, 100084, China.ORCID 0000-0002-6079-4872
Jincai HuangDepartment of Mechanical Engineering, Tsinghua University, Beijing, 100084, China.
Yanzhuo WeiDepartment of Mechanical Engineering, Tsinghua University, Beijing, 100084, China.
Haiyan ZhaoDepartment of Mechanical Engineering, Tsinghua University, Beijing, 100084, China.
Shize LinDepartment of Mechanical Engineering, Tsinghua University, Beijing, 100084, China.
Chuxiong HuDepartment of Mechanical Engineering, Tsinghua University, Beijing, 100084, China.
Ze WangDepartment of Mechanical Engineering, Tsinghua University, Beijing, 100084, China.
Zhe ZhaoOrthopedics Department, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, 100084, China.
Xining ZangDepartment of Mechanical Engineering, Tsinghua University, Beijing, 100084, China.ORCID 0000-0001-6930-8060

Funding

Beijing Municipal Natural Science Foundation M22011National Natural Science Foundation of China 52105459Tongji UniversityTsinghua University Initiative Scientific Research Program
6 · The paper itself

Abstract

Mechanically close-to-bone carbon-fiber-reinforced poly-ether-ether-ketone (CFR-PEEK)-based orthopedic implants are rising to compete with metal implants, due to their X-ray transparency, superior biocompatibility, and body-environment stability. While real-time strain assessment of implants is crucial for the postsurgery study of fracture union and failure of prostheses, integrating precise and durable sensors on orthopedic implants remains a great challenge. Herein, a laser direct-write technique is presented to pattern conductive features (minimum sheet resistance <1.7 Ω sq

Indexed as

EtherKetonesBenzophenonesCarbonCarbon FiberLasersPolyethylene GlycolsPolymersProstheses and ImplantsBenzophenonesCarbonCarbon FiberEtherKetonesPolyethylene GlycolsPolymersCFR-PEEKfracture healing assessmentlaser annealingorthopedic implantsstrain sensors

Identifiers

PMID35142105
PMCPMC9009116

What OpenQuestion holds

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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.