University of Utah Department of Biomedical Engineering, 36 S Wasatch Dr, Salt Lake City, UT 84112, United States.
Medtronic, 710 Medtronic Parkway, Minneapolis, MN 55432-5604 USA.
Injury. 2023 Jul;54(7):110756. doi: 10.1016/j.injury.2023.04.043. Epub 2023 Apr 27.
Weight-bearing protocols for rehabilitation of lower extremity fractures are the gold standard despite not being data-driven. Additionally, current protocols are focused on the amount of weight placed on the limb, negating other patient rehabilitation behaviors that may contribute to outcomes. Wearable sensors can provide insight into multiple aspects of patient behavior through longitudinal monitoring. This study aimed to understand the relationship between patient behavior and rehabilitation outcomes using wearable sensors to identify the metrics of patient rehabilitation behavior that have a positive effect on 1-year rehabilitation outcomes.
Prospective observational study on 42 closed ankle and tibial fracture patients. Rehabilitation behavior was monitored continuously between 2 and 6 weeks post-operative using a gait monitoring insole. Metrics describing patient rehabilitation behavior, including step count, walking time, cadence, and body weight per step, were compared between patient groups of excellent and average rehabilitation outcomes, as defined by the 1-year Patient Reported Outcome Measure Physical Function t-score (PROMIS PF). A Fuzzy Inference System (FIS) was used to rank metrics based on their impact on patient outcomes. Additionally, correlation coefficients were calculated between patient characteristics and principal components of the behavior metrics.
Twenty-two patients had complete insole data sets, and 17 of which had 1-year PROMIS PF scores (33.7 ± 14.5 years of age, 13 female, 9 in Excellent group, 8 in Average group). Step count had the highest impact ranking (0.817), while body weight per step had a low impact ranking (0.309). No significant correlation coefficients were found between patient or injury characteristics and behavior principal components. General patient rehabilitation behavior was described through cadence (mean of 71.0 steps/min) and step count (logarithmic distribution with only ten days exceeding 5,000 steps/day).
Step count and walking time had a greater impact on 1-year outcomes than body weight per step or cadence. The results suggest that increased activity may improve 1-year outcomes for patients with lower extremity fractures. The use of more accessible devices, such as smart watches with step counters combined with patient reported outcome measures may provide more valuable insights into patient rehabilitation behaviors and their effect on rehabilitation outcomes.
尽管缺乏数据支持,但承重方案仍是下肢骨折康复的金标准。此外,目前的方案侧重于放置在肢体上的重量,而忽略了可能对结果产生影响的其他患者康复行为。可穿戴传感器可通过纵向监测深入了解患者行为的多个方面。本研究旨在通过可穿戴传感器了解患者行为与康复结果之间的关系,确定对 1 年康复结果有积极影响的患者康复行为指标。
对 42 例闭合性踝关节和胫骨骨折患者进行前瞻性观察研究。术后 2 至 6 周,使用步态监测鞋垫连续监测康复行为。比较了优秀和一般康复结果患者组之间的患者康复行为指标,包括步数、行走时间、步频和每步体重,定义为 1 年患者报告结局测量物理功能 t 评分(PROMIS PF)。使用模糊推理系统(FIS)根据对患者结局的影响程度对指标进行排名。此外,还计算了患者特征与行为指标主成分之间的相关系数。
22 例患者有完整的鞋垫数据集,其中 17 例有 1 年 PROMIS PF 评分(33.7±14.5 岁,女性 13 例,优秀组 9 例,一般组 8 例)。步数的影响排名最高(0.817),而每步体重的影响排名最低(0.309)。患者或损伤特征与行为主成分之间未发现显著相关系数。通过步频(平均 71.0 步/分钟)和步数(对数分布,仅有 10 天超过 5,000 步/天)描述了一般患者康复行为。
与每步体重或步频相比,步数和行走时间对 1 年结局的影响更大。结果表明,增加活动量可能会改善下肢骨折患者的 1 年结局。使用更易获得的设备,如带有计步器的智能手表与患者报告结局测量相结合,可能会更深入地了解患者康复行为及其对康复结果的影响。