Evidence map›Paper›PMID 34699989›Full record

ArticleJournal of shoulder and elbow surgery2022

The role of familial predisposition in imaging-confirmed atraumatic rotator cuff tears.

Amanda J Ly, Yashas C Reddy, Nitin B Jain, Lichen Du, Folefac Atem, Michael Khazzam

Open access · greenAbstract read
In one paragraph

Article in Journal of shoulder and elbow surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
0.6field-weighted citation impact, top 30% 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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.

  1. Associations ofAging · 2024
    Pooled it
  2. Rotator cuff disease, repair and augmentation.Bulletin of the Hospital for Joint Disease (2013) · 2026
    Review
  3. Article
  4. Article
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 at 4 institutions in 1 country.

Amanda J LyDepartment of Physical Medicine and Rehabilitation, University of Texas Southwestern, Dallas, TX, USA.
Yashas C ReddyDepartment of Physical Medicine and Rehabilitation, University of Texas Southwestern, Dallas, TX, USA; Sidney Kimmel Medical College at Thomas Jefferson University, Philadelphia, PA, USA.
Nitin B JainDepartments of Physical Medicine and Rehabilitation, Orthopaedics, and Population & Data Sciences, University of Texas Southwestern, Dallas, TX, USA.
Lichen DuDepartment of Biostatistics & Data Science, University of Texas Health Science Center, Houston, TX, USA.
Folefac AtemDepartment of Biostatistics & Data Science, University of Texas Health Science Center, Houston, TX, USA.
Michael KhazzamDepartment of Orthopedic Surgery, Shoulder Service, University of Texas Southwestern, Dallas, TX, USA. Electronic address: michael.khazzam@utsouthwestern.edu.
The University of Texas Health Science Center at Houston · USThe University of Texas Southwestern Medical Center · USSouthwestern Medical Center · USThomas Jefferson University · US

Funding

The Genetic Epidemiology of Rotator Cuff Tears: the cuffGEN Study - SupplementR01AR074989 · NIAMS · UT SOUTHWESTERN MEDICAL CENTER · PI JAIN, NITIN B · 2020 to 2025
$3.6M
NIAMS NIH HHS R01 AR074989
6 · The paper itself

Abstract

backgroundThe etiology of atraumatic rotator cuff tears is not completely understood. Limited data suggest the role of genetic and familial predisposition in the etiology of rotator cuff tears. The purpose of this study was to assess whether there is an increased likelihood of rotator cuff tears in family members of patients with rotator cuff tears vs. those without tears. This would provide evidence for whether there is an association between familial predisposition and rotator cuff tearing.

methodsPatients presenting to a shoulder clinic were recruited in this study. They provided information on personal medical history, shoulder symptoms, and family history of rotator cuff tears. The diagnosis of rotator cuff tears was based on imaging (magnetic resonance imaging or computed tomography arthrogram) confirmation of a structural defect in the rotator cuff. The association between family history of rotator cuff problems and the likelihood of an imaging-confirmed rotator cuff tear diagnosis was evaluated using multivariate logistic regression, adjusting for age, sex, race/ethnicity, cigarette smoking, hypertension, diabetes, and depression.

resultsIn our cohort of 2335 patients, 52.6% (n = 1229) of patients had a rotator cuff tear. Among patients with tears, 17.9% (n = 220) of patients reported a family history of rotator cuff issues vs. 11.1% (n = 123) in patients without tears. A family history of rotator cuff problems was significantly associated with the diagnosis of an imaging-confirmed rotator cuff tear (odds ratio [OR] 2.24, 95% confidence interval [CI] 1.71, 2.95). Other confounding variables such as increasing age (OR 1.06, 95% CI 1.05, 1.07) and Hispanic race/ethnicity as compared to non-Hispanic white race/ethnicity (OR 1.48, 95% CI 1.07, 2.05) were significantly associated with rotator cuff tears. Sex, smoking, hypertension, diabetes, and depression were not significantly associated with rotator cuff tearing.

conclusionOur study shows that individuals with rotator cuff tears were more than 2 times as likely to have a family member with a tear as compared to patients without tears. Increasing age and patients who identified as being of Hispanic ancestry were also significantly associated with higher odds of rotator cuff tears.

Indexed as

Rotator Cuff InjuriesArthrographyHumansMagnetic Resonance ImagingRotator CuffShoulderShoulder PainatraumaticFamilial predispositiongeneticrotator cuff tearshoulder pain

Identifiers

PMID34699989
PMCPMC9128138
OpenAlexW3208627786

What OpenQuestion holds

Textmetadata
LicenceTDM
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.