Evidence map›Paper›PMID 39529962›Full record

ArticleBiomedical engineering letters2024

A novel approach to characterize the correction path features for the tibia deformity correction.

Guotong Li, Xiaoqiang Tang, Jianfeng Li, Mingjie Dong

Abstract read
In one paragraph

Article in Biomedical engineering letters, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Guotong LiDepartment of Mechanical Engineering, Tsinghua University, Beijing, 100084 China.ORCID 0000-0001-7274-6520
Xiaoqiang TangDepartment of Mechanical Engineering, Tsinghua University, Beijing, 100084 China.
Jianfeng LiFaculty of Materials and Manufacturing, Beijing University of Technology, Beijing, 100124 China.
Mingjie DongFaculty of Materials and Manufacturing, Beijing University of Technology, Beijing, 100124 China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Preoperative correction path planning is an important preparation for obtaining the desired correction. However, a convenient and effective model has not been proposed to characterize the correction path features, especially how to visualize the growth process of the bone cross-section has not been investigated. In this paper, a new characterization approach of the correction path features and corresponding evaluation indexes are proposed for the tibia deformity correction. We represent the growth process of new bone cross-section by a series of continuous and discrete circles. Based on the definition and assumptions of the bone cross-section, three evaluation indexes are proposed to assist the clinician in critically comparing and analyzing the feasibility of preoperatively correction approaches. A motor-driven parallel external fixator (MD-PEF) is developed to verify the proposed characterization approach. Finally, the features of the generated correction paths are compared and analyzed based on three correction methods. The results show that the proposed method can well present the growth process of bone cross-section and can detect the overlap phenomenon between bone cross-sections. And the approach of joint adjustment for equal bone distraction can generate a smooth correction path, uniform distraction rate and effectively avoid the overlap of bone cross-sections. This study is an important addition to facilitating the development of deformity correction techniques.

Indexed as

Correction pathDeformity correctionExternal fixatorMedical robotPath feature

Identifiers

PMID39529962
PMCPMC11550302

What OpenQuestion holds

Textmetadata
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.