Chayanin Angthong, MD, PhD Foot & Ankle Surgery Department of Orthopaedics, Faculty of Medicine Thammasat University, Pathum Thani, Thailand

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The relationships between patient-reported outcome, quality of life, and gait characteristics using a wearable foot inertial-sensor assessment in patients with foot and ankle conditions Chayanin Angthong, MD, PhD Foot & Ankle Surgery Department of Orthopaedics, Faculty of Medicine Thammasat University, Pathum Thani, Thailand

CONFLICT TO DISCLOSE The relationships between patient-reported outcome, quality of life, and gait characteristics using a wearable foot inertialsensor assessment in patients with foot and ankle conditions Chayanin Angthong, M.D., Ph.D. I have potential conflicts out of this presentation due to: financial supports to attend the meetings from Device Innovation Company (Thailand), Phoenix Company (Thailand), and Smith & Nephew Company.

PURPOSE The purpose of this study was to report the relationships between validated patient-reported outcome, health-related quality of life, and gait characteristics using a wearable foot inertial-sensor assessment in patients with footankle conditions. The inter-metrics correlations were analyzed to determine the relationships between each spatiotemporal or gait parameter.

METHODS (1) Fifty-three patients with foot-ankle conditions (38 female/15 male, the mean age was 51.9 (± 13.7) years (range: 21 75 years) were collected for this study. Clinical assessments, including evaluations with validated patient-reported outcomes using the visual analogue scale foot and ankle (VAS-FA) score, and health-related quality of life using the validated Short Form-36 (SF-36), were performed and recorded in each patient.

METHODS (2) Gait characteristics assessment were performed in all patients using a Foot Pod (Garmin Ltd.) wearable device with Micro-electro-mechanical systems (MEMS) inertial-sensor technology during patients' walking-trial for a distance of 10-meter at their selfselected speeds. Pearson s correlation coefficient r and Analysis-of-variance (ANOVA) tests were mainly used to analyze the data.

DEMOGRAPHIC DATA

PATIENTS SCORES AND GAIT PARAMETERS

VAS-FA SCORES VS GAIT PARAMETERS No significant correlation between VAS- FA scores and gait parameters was shown by Pearson s correlation analysis.

SF-36 SCORES VS GAIT PARAMETERS Negative correlation between physical component summary (PCS) and maximal cadence only showed a significant value at Pearson s correlation coefficient (r) = 0.308, P = 0.025. In addition, the correlation between VAS-FA and SF-36 scores was high, as Pearson s correlation coefficient r = 0.858, P < 0.001.

RESULTS: INTER-METRICS CORRELATIONS Positive correlations (r) were found between mean walking speed and mean cadence (r = 0.776, P < 0.001) and between maximal walking speed and mean step length (r = 0.498, P < 0.001). Negative correlations (r) were found between mean cadence and mean step length (r = 0.491, P < 0.001) and between maximal cadence and mean step length (r = 0.355, P = 0.009).

DISCUSSION & CONCLUSION walking speed = step length cadence Regarding relationships among several spatiotemporal parameters and patient-reported outcome measures, cadence is the only parameter that was significantly negatively related with PCS in health-related quality of life. Regarding Tudor-Locke C and Rowe DA, Cadence also significantly positively correlated with walking intensity; patients with increased cadence need more energy during walking. Based on inter-metrics relationships, increased cadence might be used to maintain walking speed as a compensatory mechanism in patients with foot-ankle conditions.

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