2024 · Orthopaedics & Traumatology: Surgery & Research
術前の特徴から、両側TKA後に歩行速度が10%以上増加または減少する患者を区別できるか？
平均歩行速度は0.87から0.94 m/sへ0.07 m/s増加しました（P < 0.001）。
研究構造
- 01対象
128人の女性が段階ごとに初心TKAを受けた.
- 02方法
段階的両側TKAの後ろ向きコホートで術前と2年の歩行を比較しました。10%以上の増加・減少・中間群を定義し、歩行速度・年齢・機械的軸角で分類モデルを構築しました。
- 03報告された結果
平均歩行速度は0.87から0.94 m/sへ0.07 m/s増加しました（P < 0.001）。
研究対象・方法・結果を分けて示した説明用の模式図です。論文の原図ではありません。
抄録の解説
対象と方法
主な結果
手術に関する読書のポイント
解釈の限界
簡単に説明しましょう
この研究で何が確認されましたか?
平均歩行速度は0.87から0.94 m/sへ0.07 m/s増加しました（P < 0.001）。
治療決定に直接適用できるか?
女性の段階的両側TKAに限定した後ろ向き研究です。抄録には外部検証の結果がなく、他の性別や片側TKAでの性能は確認できません。
Keywords・キーワード
- Gait analysis
- Gait speed
- Total knee arthroplasty
- Arthroplasty, Replacement, Knee
- Machine Learning
- Walking Speed
- Retrospective Studies
- Recovery of Function
Abstract・原文の抄録
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.
オリジナル紙だ
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