A new and simple method for patellar height measurement: Fibula-condyle-patella angle.


Journal

Joint diseases and related surgery
ISSN: 2687-4792
Titre abrégé: Jt Dis Relat Surg
Pays: Turkey
ID NLM: 101764223

Informations de publication

Date de publication:
13 Feb 2024
Historique:
received: 01 12 2023
accepted: 28 01 2024
medline: 10 5 2024
pubmed: 10 5 2024
entrez: 10 5 2024
Statut: ppublish

Résumé

This study aims to evaluate the inter-observer reliability of fibula-condyle-patella angle measurements and to compare it with other measurement techniques. Between January 01, 2023 and January 31, 2023, a total of 108 patients (20 males, 88 females; mean age: 47.5±12.0 years; range, 18 to 72 years) who underwent X-rays using the fibula-condyle-patella angle, Insall-Salvati, Caton-Deschamps, Blackburne-Pell, and plateau-patella angle (PPA) methods were retrospectively analyzed. Knee lateral radiographs taken in at least 30 degrees of flexion and appropriate rotation were scanned. All measurements were made by two orthopedic surgeons who were blinded to measurement methods. Right knee patellar height measurements were conducted in 56 patients, while left knee patellar heights were assessed in 52 patients. The highest inter-observer concordance was found in the fibula-condyle-patella angle. The second highest concordance was found in the Insall-Salvati. The highest concordance correlation was found with PPA in the measurements of both researchers. The fibula-condyle-patella angle is a reliable technique with a good inter-observer reliability for measuring patellar height. We believe that this study will inspire future research to establish comprehensive reference values for clinical applications.

Identifiants

pubmed: 38727111
doi: 10.52312/jdrs.2024.1553
pii: jdrs.2024.1553
doi:
pii:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

324-329

Auteurs

Mahmud Aydin (M)

Haseki Eğitim ve Araştırma Hastanesi, Ortopedi ve Travmatoloji Kliniği, 34096 Fatih, İstanbul, Türkiye. mahmut_aydn@windowslive.com.

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Classifications MeSH