This study aimed to determine which state, On or Off, during the 10MWT more accurately predicts fall risk in patients with PD.
The study included 48 patients (30 females) with PD who were admitted to our hospital and were able to walk independently without physical assistance. The mean age was 66.3 ± 8.0 years, with 11 participants in Hoehn and Yahr stage II, 28 in stage III, and 9 in stage IV. Walking speed was calculated from the time taken to walk the middle 10 m of a 14 m walkway at 10 MWT. Measurements were taken in both the On state (when anti-PD medication was effective) and the Off state (after the medication had been discontinued from the previous night). Participants were classified based on their fall history over the previous three months. A 2 × 2 contingency table was created using a predictive cutoff for falls at 1.1 m/sec, with speeds 1.1 m/sec classified as Positive and speeds ≥1.1 m/sec as Negative. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy were calculated for both the On and Off states.
Thirty participants (62.5%) had a history of falls. In the On state, 24 participants (50%) had a walking speed 1.1 m/sec (Positive), while 24 (50%) had a speed ≥1.1 m/sec (Negative). In the Off state, 39 participants (81.3%) were classified as Positive, and 9 (18.8%) as Negative. The accuracy of identifying fall risk in the On state was 60% sensitivity, 66.7% specificity, 75% PPV, 50% NPV, and 62.5% diagnostic accuracy. In the Off state, sensitivity was 86.7%, specificity 27.8%, PPV 66.7%, NPV 55.6%, and diagnostic accuracy 64.6%.
The 10MWT was more sensitive for detecting fall risk in the Off state, when motor symptoms were more pronounced. However, sensitivity and specificity in both states were lower than previously reported, potentially due to differences in disease severity among participants.
These findings suggest that neither the On nor Off state alone provides a definitive assessment of fall risk in patients with PD using the 10MWT. A combined approach—evaluating gait in both states or incorporating additional assessments—may improve the accuracy of fall risk predictions.
10-Meter Walk Test
fall risk
