Department of Neurosurgery, Stanford University Hospital and Clinics, Stanford, CA, USA.
Department of Neurosurgery, Stanford University, 213 Quarry Road, 4th Fl MC 5958, Palo Alto, CA, 94304, USA.
Sci Rep. 2024 Aug 28;14(1):19988. doi: 10.1038/s41598-024-70912-7.
Longitudinal physical activity monitoring is a novel and promising objective outcome measure for patients with degenerative spine disorder (DSD) that currently lacks established standards for data collection and interpretation. Here, we monitored 100 patients with DSD with the Apple Watch to establish the optimal duration and pattern of step count monitoring needed to estimate their weekly physical activity before their elective surgery. Participants were predominantly female (65.3%), had an average age of 61.5 years, and showed consistent step counts between preoperative days, as well as across weekends and weekdays. Intraclass correlations (ICC) analysis showed that a step count average over 2 days achieved an ICC of 0.92 when compared to a 7-day average before surgery, while 4 days were required for a similar agreement of 0.93 with a 14-day average. Sequential linear regression demonstrated that incorporating additional preoperative days improved the model's ability to predict 7- and 14-days step count averages. We conclude that, while daily preoperative step counts remain relatively stable, longer activity monitoring is necessary to account for the variance in step count over an increasing time frame, and the full extent of data fluctuation may only become apparent with long-term trend analysis.
纵向体力活动监测是一种新颖且有前途的退行性脊柱疾病（DSD）患者客观结局测量方法，但目前缺乏用于数据收集和解释的既定标准。在这里，我们使用 Apple Watch 监测了 100 名 DSD 患者，以确定在选择性手术前估计其每周体力活动所需的最佳步数监测持续时间和模式。参与者主要为女性（65.3%），平均年龄为 61.5 岁，术前天数、周末和工作日的步数一致。组内相关系数（ICC）分析表明，与术前 7 天的平均步数相比，2 天的平均步数的 ICC 为 0.92，而 4 天的 ICC 为 0.93，与 14 天的平均步数相似。序贯线性回归表明，纳入更多术前天数可以提高模型预测 7 天和 14 天平均步数的能力。我们得出结论，虽然术前每天的步数相对稳定，但需要更长时间的活动监测来解释在不断增加的时间框架内步数的变化，并且只有通过长期趋势分析，数据波动的全部程度才可能变得明显。
