2024 · Orthopaedics & Traumatology: Surgery & Research
양측 TKA 후 보행 속도가 10% 이상 증가하거나 감소할 환자를 수술 전 특성으로 구분할 수 있을까?
평균 보행 속도는 0.87 → 0.94 m/s로 0.07 m/s 증가했습니다(P < 0.001).
연구 구조
- 01대상
단계적 양측 primary TKA를 받은 여성 128명.
- 02방법
단계적 양측 TKA의 후향적 코호트에서 수술 전과 2년의 보행을 비교했습니다. 10% 이상 증가·감소·중간군을 정의하고 보행 속도, 연령, 기계적 축 각도로 분류모형을 구축했습니다.
- 03보고 결과
평균 보행 속도는 0.87 → 0.94 m/s로 0.07 m/s 증가했습니다(P < 0.001).
논문의 대상·방법·결과를 구분한 설명용 모식도입니다. 원문 figure가 아닙니다.
초록 해설
대상과 방법
주요 결과
진료·수술에서 읽을 지점
해석의 제한
짧게 정리하면
이 연구가 확인한 것은 무엇인가요?
평균 보행 속도는 0.87 → 0.94 m/s로 0.07 m/s 증가했습니다(P < 0.001).
개별 환자의 치료 결정에 바로 적용할 수 있나요?
여성의 단계적 양측 TKA에 국한된 후향적 연구입니다. 초록에는 외부 검증 결과가 없어 다른 성별·일측 TKA에서의 성능을 확인할 수 없습니다.
Keywords · 주제어
- Gait analysis
- Gait speed
- Total knee arthroplasty
- Arthroplasty, Replacement, Knee
- Machine Learning
- Walking Speed
- Retrospective Studies
- Recovery of Function
Abstract · 원문 초록
Do Weon Lee, Hyuk-Soo Han, Myung Chul Lee, Du Hyun Ro. Prediction of postoperative gait speed change after bilateral primary total knee arthroplasty in female patients using a machine learning algorithm. Orthopaedics & traumatology, surgery & research : OTSR. 2024;110(7):103842. doi:10.1016/j.otsr.2024.103842.
BACKGROUND
An important aim of total knee arthroplasty is to achieve functional recovery, which includes post-operative increase in walking speed. Therefore, predicting whether a patient will walk faster or slower after surgery is important in TKA, which has not been studied in previous literatures. Who walks faster and who walks slower after TKA? Can we predict these kinds of patients before surgery?
HYPOTHESIS
Whether or not a patient walk faster after total knee arthroplasty can be predicted with preoperative characteristics.
PATIENTS AND METHODS
In this retrospective cohort study, 128 female patients who underwent staged bilateral total knee arthroplasty were analyzed with gait analysis preoperatively and at postoperative two years. These patients were divided into three different groups according to the percentage of gait speed change after total knee arthroplasty: 1) V(+), more than 10% gait speed increase; 2) V(-), more than 10% gait speed decrease; and 3) V(0), those in-between. Gait parameters, mechanical axis angles, WOMAC pain score and Knee Society scores of the two groups (V(+) and V(-)) were compared. Furthermore, a classification model predicting whether a patient walks faster after total knee arthroplasty was designed using a machine learning algorithm.
RESULTS
After total knee arthroplasty, average gait speed increased by 0.07m/s from 0.87m/s to 0.94m/s (p<0.001) and gait speed increased in 43.8% of the patients (n=56). However, gait speed decreased in a significant number of patients (n=17, 13.3%). When V(+) and V(-) groups were compared, gait speed, cadence, sagittal/coronal knee range of motion, and Knee Society Function score were lower in the V(+) group before surgery, but became higher after surgery. Gait speed change could be predicted using three variables (preoperative gait speed, age, and the magnitude of mechanical axis angle). The area under the receiver operating characteristic curve of the machine learning model was 0.86.
DISCUSSION
After total knee arthroplasty, gait speed was maintained or increased in most patients. However, gait speed decreased in a significant number of patients. The machine learning classification model showed a good predictive performance, which could aid in the decision-making and the timing of total knee arthroplasty.
LEVEL OF EVIDENCE
III; retrospective cohort study.
원래 논문
Prediction of postoperative gait speed change after bilateral primary total knee arthroplasty in female patients using a machine learning algorithm
Do Weon Lee, Hyuk-Soo Han, Myung Chul Lee, Du Hyun Ro
Orthopaedics & Traumatology: Surgery & Research · 2024