Evidence map›Paper›PMID 40008032›Full record

ArticleFrontiers in bioengineering and biotechnology2025

The effects of different carbon-fiber plate shapes in shoes on lower limb biomechanics following running-induced fatigue.

Yufan Xu, Chengyuan Zhu, Yufei Fang, Zhenghui Lu, Yang Song, Chen Hu, Dong Sun, Yaodong Gu

Abstract read
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Article in Frontiers in bioengineering and biotechnology, 2025. 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

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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

8 authors.

Yufan XuFaculty of Sports Science, Ningbo University, Ningbo, China.
Chengyuan ZhuFaculty of Sports Science, Ningbo University, Ningbo, China.
Yufei FangDepartment of Radiology, Ningbo No. 2 Hospital, Ningbo, China.
Zhenghui LuFaculty of Sports Science, Ningbo University, Ningbo, China.
Yang SongDepartment of Biomedical Engineering, Faculty of Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China.
Chen HuFaculty of Sports Science, Ningbo University, Ningbo, China.
Dong SunFaculty of Sports Science, Ningbo University, Ningbo, China.
Yaodong GuFaculty of Sports Science, Ningbo University, Ningbo, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Different shapes of carbon-fiber plates (CFPs) are likely to affect lower limb biomechanics, particularly under conditions of running-induced fatigue, and potentially impact runners' performance and risk of injury. However, no studies have yet elucidated the precise effects of CFP shapes on the lower limb biomechanical characteristics subsequent to running-induced fatigue. The purpose of this study was to investigate the effects of different CFP shapes in running shoes on the lower limb biomechanics of runners following running-induced fatigue. 12 male runners (aged 21.8 ± 1.3 years, mass 59.1 ± 4.1 kg, height 168.9 ± 2.2 cm, weekly running distance 68.8 ± 5.5 km/week) were recruited for this study. Two-way repeated measures ANOVA was used to compare kinematic and kinetic data, while SPM (Statistical Parametric Mapping) was used to assess the activation levels of lower limb muscles. Compared to wearing flat CFP shoes ("Flat"), wearing curved CFP shoes ("Curve") resulted in a significant reduction in the hip (p = 0.034) and knee contact angle (p < 0.000), as well as a significant decrease in the hip flexion moment (p = 0.008). The activation level of the tibialis anterior (TA) was significantly higher when wearing "Curve" in pre-fatigue compared to "Flat", whereas the opposite was observed post-fatigue. The curved CFP altered the bending angle of the forefoot, thereby significantly reducing the joint angles and joint moments of the hip and knee.

Indexed as

carbon-fiber plate (CFP)injurylower limb biomechanicsrunning-induced fatiguerunning performance

Identifiers

PMID40008032
PMCPMC11850346

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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.