Background: Passive smartphone-based apps are becoming more common for measuring patient progress after total hip arthroplasty (THA). Optimum activity levels during early THA recovery have not been well documented.
Objectives: Correlations between step-count and patient reported outcome measures (PROMs) during early recovery were explored. This study also investigated how demographics impact step-count during early post-operative recovery.
Methods: Smartphone captured step-count data from 666 THA patients was retrospectively reviewed. Mean age was 64 ± 11 years. 55% were female. Mean BMI was 29 ± 8kg/m2. Mean daily step-count was calculated for each patient over four time-windows: 60 days prior to surgery (preop), 42-49 days postop (6 weeks), 91-98 days postop (3 months), and 183-197 days postop (6 months). Spearman correlation coefficients and linear regression were used to assess the association between PROMs (HOOS-12, HOOS-Jr, and UCLA) were performed. Patients were separated into three step-count levels: low (< 2500 steps/day), medium (2500-5500 steps/day), and high (> 5500 steps/day). Age > 65 years, BMI > 35 kg/m2, and sex were used for demographic comparisons. Post hoc analyses were performed using Welch's unequal variances t-tests, or Wilcoxon rank-sum tests, both with Bonferroni corrections, where appropriate when comparing between groups. Chi-squared analyses were also used when comparing categorical variables.
Results: UCLA correlated with step-count at all time-windows (p< 0.001). HOOS12-Function correlated with step-count preoperatively, at 6 weeks, and at 3 months (p< 0.001). High step-count individuals had improved UCLA scores compared to low step-count individuals preoperatively (Δ1.5, p< 0.001), at 6 weeks (Δ0.9, p< 0.001), at 3 months (Δ1.4, p< 0.001), and at 6 months (Δ1.4, p< 0.001). High step-count individuals had improved HOOS12-Function scores compared to low step-count individuals preoperatively (Δ9.6, p< 0.001), at 6 weeks (Δ5.3, p< 0.001), and at 3 months (Δ6.1, p< 0.001). Males had greater step-count at all time points (p< 0.001). Younger patients and low BMI patients had greater step-count across all time points (p< 0.001).
Conclusion: High step-count improved PROMs scores compared to low step-count. Early post-operative step-count was significantly impacted by age, sex, and BMI. Generic recovery profiles may not be appropriate across diverse populations.
Keywords: PROMs; Total hip arthroplasty; remote patient monitoring; smartphone; step-count.