Evidence map›Paper›PMID 35887573›Full record

ArticleJournal of personalized medicine2022

Risk Factors Associated with Cartilage Defects after Anterior Cruciate Ligament Rupture in Military Draftees.

Ting-Yi Sun, Chun-Liang Hsu, Wei-Cheng Tseng, Tsu-Te Yeh, Guo-Shu Huang, Pei-Hung Shen

Abstract read
In one paragraph

Article in Journal of personalized medicine, 2022. 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. Review
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

6 authors.

Ting-Yi SunDepartment of Orthopedic Surgery, Tri-Service General Hospital, National Defense Medical Center, Taipei 114, Taiwan.ORCID 0000-0001-5151-9214
Chun-Liang HsuDepartment of Orthopedic Surgery, Tri-Service General Hospital, National Defense Medical Center, Taipei 114, Taiwan.
Wei-Cheng TsengDepartment of Anesthesiology, Tri-Service General Hospital, National Defense Medical Center, Taipei 114, Taiwan.ORCID 0000-0003-3528-8633
Tsu-Te YehDepartment of Orthopedic Surgery, Tri-Service General Hospital, National Defense Medical Center, Taipei 114, Taiwan.ORCID 0000-0002-9766-9290
Guo-Shu HuangDepartment of Radiology, Tri-Service General Hospital, National Defense Medical Center, Taipei 114, Taiwan.
Pei-Hung ShenDepartment of Orthopedic Surgery, Tri-Service General Hospital, National Defense Medical Center, Taipei 114, Taiwan.

Funding

Tri-Service General Hospital TSGH-C106-077
6 · The paper itself

Abstract

This study aimed to evaluate the different clinical results and factors associated with cartilage defects in military draftees who underwent different treatments after anterior cruciate ligament (ACL) rupture. Overall, 105 patients who had sustained ACL rupture were military draftees who underwent a conscription examination for physical status assessment from January 2012 to December 2020. Patients were divided into three groups: conservative treatment after ACL rupture, status post-anterior cruciate ligament reconstruction (ACLR), but graft rupture, and status post-ACLR with graft intact. Inter-group comparisons and statistical analyses were performed for age, body mass index (BMI), thigh circumference difference, side-to-side difference in anterior knee translation by KT-2000, meniscus tear, and cartilage defect. Multivariate logistic regression analysis was used to determine the factors associated with cartilage defects. The multivariable regression model showed that BMI (odds ratio OR: 1.303; 95% CI: 1.016-1.672;

Indexed as

ACLRanterior cruciate ligament ruptureconservative treatmentgraft rupturemilitaryosteoarthritisrisk factors

Identifiers

PMID35887573
PMCPMC9317476

What OpenQuestion holds

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Registered trials

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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.