Your browser doesn't support javascript.
loading
Influencing factors on the quality of recovery after total knee arthroplasty: development of a predictive model.
Shan, Sen; Shi, Qingpeng; Zhang, Hengyuan.
Afiliación
  • Shan S; The Second School of Clinical Medicine, Binzhou Medical University, Yantai, Shandong, China.
  • Shi Q; Department of Bone and Joint Surgery, Yantai Affiliated Hospital of Binzhou Medical University, Yantai, Shandong, China.
  • Zhang H; The Second School of Clinical Medicine, Binzhou Medical University, Yantai, Shandong, China.
Front Med (Lausanne) ; 11: 1427768, 2024.
Article en En | MEDLINE | ID: mdl-39267965
ABSTRACT

Introduction:

Total Knee Arthroplasty (TKA) is a widely performed procedure that significantly benefits patients with severe knee degeneration. However, the recovery outcomes post-surgery can vary significantly among patients. Identifying the factors influencing these outcomes is crucial for improving patient care and satisfaction.

Methods:

In this retrospective study, we analyzed 362 TKA cases performed between January 1, 2018, and July 1, 2022. Multivariate logistic regression was employed to identify key predictors of recovery within the first year after surgery.

Results:

The analysis revealed that Body Mass Index (BMI), age-adjusted Charlson Comorbidity Index (aCCI), sleep quality, Bone Mineral Density (BMD), and analgesic efficacy were significant predictors of poor recovery (p < 0.05). These predictors were used to develop a clinical prediction model, which demonstrated strong predictive ability with an Area Under the Receiver Operating Characteristic (AUC) curve of 0.802. The model was internally validated.

Discussion:

The findings suggest that personalized postoperative care and tailored rehabilitation programs based on these predictors could enhance recovery outcomes and increase patient satisfaction following TKA.
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Front Med (Lausanne) Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Front Med (Lausanne) Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza