Validity and reliability of the Unified Classification System applied to periprosthetic femur fractures: a comparison with the Vancouver system

01 Pubblicazione su rivista
De Meo Daniele, Zucchi Benedetta, Castagna Valerio, Pieracci Edoardo M, Mangone Massimiliano, Calistri Alessandro, Persiani Pietro, Villani Ciro
ISSN: 0300-7995

Objective:
The Unified Classification System (UCS) presents itself as an evolution of the Vancouver Classification (VCS) for the evaluation of periprosthetic fractures of the proximal femur (PPF). The aim of our study was to evaluate the interobserver and intraobserver reliability, with the purpose of highlighting any loss of reproducibility or validity of the new classification system, compared to the previous one, when applied to the proximal femur.
Material and Methods:
We tested the interobserver and intraobserver agreement using 40 PPF clinical cases. Each classifying subtype of the UCS and VCS was present in at least two cases. Six experienced hip surgeons (Senior Surgeon, SS) and 5 surgeons in training (Junior Surgeon, JS) classified the clinical cases, twice using the VCS and twice with the UCS. The validity of both classifications was then tested with intraoperative surveys.
Results:
The mean κ value for interobserver agreement for the VCS in the JS group was 0.65 (CI 95% = 0.57-0.70) and 0.81 for the SS group (0.74-0.88). The mean κ value for interobserver agreement for the UCS in the JS group was 0.63 (0.57-0.67) and 0.65 for the SS group (0.59-0.73). The mean κ value for intraobserver agreement for the VCS in the JS group was 0.71 (0.66-0.75) and 0.73 for the SS group (0.65-0.80). The mean κ value for intraobserver agreement for the UCS in the JS group was 0.72 (0.67-0.76) and 0.7 for the SS group (0.65-0.75). The validity analysis showed a κ value of 0.56 (0.52-0.61) for the VCS (moderate agreement) and a κ value of 0.64 (0.58-0.7) for the UCS (good agreement).
Conclusion:
The UCS completes the Vancouver classification, expanding it. It is reliable, despite the increase in classification categories and number of parameters to evaluate, with a slightly higher validity.

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