Evidence map›Paper›PMID 34825259›Full record

ArticleSkeletal radiology2022

Diagnostic performance of conventional magnetic resonance imaging for detection and grading of subscapularis tendon tear according to Yoo and Rhee classification system in patients underwent arthroscopic rotator cuff surgery.

Tae Ran Ahn, Young Cheol Yoon, Jae Chul Yoo, Hyun Su Kim, Ji Hyun Lee

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Article in Skeletal radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.0field-weighted citation impact, top 22% of its field
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 8 citations in OpenAlex.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors at 3 institutions in 1 country.

Tae Ran AhnDepartment of Radiology, Samsung Medical Center, College of Medicine, Sungkyunkwan University, 81 Irwon-Ro Gangnam-gu, Seoul, 06351, Korea.
Young Cheol YoonDepartment of Radiology, Samsung Medical Center, College of Medicine, Sungkyunkwan University, 81 Irwon-Ro Gangnam-gu, Seoul, 06351, Korea. youngcheol.yoon@gmail.com.
Jae Chul YooDepartment of Orthopedic Surgery, Samsung Medical Center, College of Medicine, Sungkyunkwan University, Seoul, Korea.
Hyun Su KimDepartment of Radiology, Samsung Medical Center, College of Medicine, Sungkyunkwan University, 81 Irwon-Ro Gangnam-gu, Seoul, 06351, Korea.
Ji Hyun LeeDepartment of Radiology, Samsung Medical Center, College of Medicine, Sungkyunkwan University, 81 Irwon-Ro Gangnam-gu, Seoul, 06351, Korea.
Sungkyunkwan University · KRGachon University Gil Medical Center · KRSamsung Medical Center · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo assess the diagnostic accuracy of conventional MRI for detecting and grading subscapularis (SSC) tears by applying the Yoo and Rhee classification. MATERIALS AND

methodsA total of 179 patients who underwent MRI followed by arthroscopic rotator cuff surgery were enrolled. Two musculoskeletal radiologists evaluated the SSC using axial, oblique sagittal, and oblique coronal MRI according to the Yoo and Rhee classification. Using arthroscopic findings as the reference standard, the sensitivity, specificity, accuracy, and interobserver agreement of SSC tears were analyzed.

resultsArthroscopy confirmed that the numbers of type I, IIA, IIB, III, IV, and V tears were 35, 70, 35, 9, 9, and 0, respectively. The sensitivity, specificity, and accuracy of readers 1 and 2 for the detection of tears (type IIA or higher) were 85%, 75%, and 82%, and 89%, 70%, and 83%, respectively, while those for the detection of surgical candidates (type IIB or higher) were 77%, 75%, and 75%, and 77%, 83%, and 82%, respectively. The interobserver agreement for detecting SSC tear presence was substantial (κ = 0.70) for reader 1 vs. reader 2, and those for detecting the surgical candidate group was substantial (κ = 0.68) for reader 1 vs. reader 2. The interobserver agreement for grading SSC tears was excellent (κ = 0.86) for reader 1 vs. reader 2.

conclusionConventional MRI showed 82.5% and 78.5% average accuracy in detecting IIA and IIB or higher tears by applying the Yoo and Rhee classification for the diagnosis of SSC tears with an excellent interobserver agreement in tear grading.

Indexed as

Rotator CuffRotator Cuff InjuriesArthroscopyHumansMagnetic Resonance ImagingRetrospective StudiesRuptureSensitivity and SpecificityClassificationRotator cuffSensitivitySpecificity

Identifiers

PMID34825259
OpenAlexW3217779247

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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.