Evidence map›Paper›PMID 36299682›Full record

Trial reportComputational and mathematical methods in medicine2022

Effect of Core Stability Training on Unstable Support Surfaces in Postoperative Rehabilitation of Thoracolumbar Vertebral Compression Fractures in the Elderly.

Yanfei Yin, Shixia Cao, Chenjie Wang, Yanju Liu, Huakai Zhang

RetractedOpen access · hybridAbstract readClinical TrialRetracted Publication
In one paragraph

Trial report in Computational and mathematical methods in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.9field-weighted citation impact, top 27% of its field
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, 6 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Yanfei YinDepartment of Rehabilitation Teaching and Research, Medical College of Zhengzhou University of Industrial Technology, Xinzheng, Henan 451100, China.ORCID https://orcid.org/0000-0001-6904-5117
Shixia CaoDepartment of Rehabilitation Teaching and Research, Medical College of Zhengzhou University of Industrial Technology, Xinzheng, Henan 451100, China.
Chenjie WangDepartment of Rehabilitation Medicine, South Branch of the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450000, China.
Yanju LiuDepartment of Rehabilitation Teaching and Research, Medical College of Zhengzhou University of Industrial Technology, Xinzheng, Henan 451100, China.
Huakai ZhangDepartment of Rehabilitation Teaching and Research, Medical College of Zhengzhou University of Industrial Technology, Xinzheng, Henan 451100, China.
Zhengzhou University of Industrial Technology · CNFirst Affiliated Hospital of Zhengzhou University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Thoracolumbar vertebral compression fractures (TVCF) are caused by anterior flexion or vertical downward violence to the spine (Sezer et al. 2021). This study is aimed at investigating the effect of core stability training (CST) on unstable support surfaces in the postoperative rehabilitation of TVCF in the elderly Conclusion: Unstable support surface CST can effectively improve postoperative vertebral body rehabilitation, balance function, gait, pain conditions, and lumbar spine function in elderly TVCF patients, and enhance their quality of life and rehabilitation satisfaction. This trial is registered with ChiCTR2000014547.

Indexed as

Fractures, CompressionSpinal FracturesAgedCore StabilityFracture Fixation, InternalHumansLumbar VertebraePainQuality of LifeThoracic VertebraeTreatment Outcome

Identifiers

PMID36299682
PMCPMC9592204
OpenAlexW4306641724

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.