Introduction. The ability to walk over various surfaces such as cobblestones, slopes or stairs is a very patient centric and clinically meaningful mobility outcome. Current wearable sensors only measure step counts or walking speed regardless of such context relevant for assessing gait function. This study aims to improve deep learning (DL) models to classify surfaces of walking by altering and comparing model features and sensor configurations. Method. Using a public dataset, signals from 6 IMUs (Movella DOT) worn on various body locations (trunk, wrist, right/left thigh, right/left shank) of 30 subjects walking on 9 surfaces were analyzed (flat ground, ramps (up/down), stairs (up/down), cobblestones (irregular), grass (soft), banked (left/right)). Two variations of a CNN Bi-directional LSTM model, with different Batch Normalization layer placement (beginning vs end) as well as data reduction to individual sensors (versus combined) were explored and model performance compared in-between and with previous models using F1 scores. Result. The Bi-LSTM architecture improved performance over previous models, especially for subject-wise data splitting and when combining the 6 sensor locations (e.g. F1=0.94 versus 0.77). Placement of the Batch Normalization layer at the beginning, prior to the convolutional layer, enhanced model understanding of participant gait variations across surfaces. Single sensor performance was best on the right shank (F1=0.88). Conclusion. Walking surface detection using wearable IMUs and DL models shows promise for clinically relevant real-world applications, achieving high F1 levels (>0.9) even for subject-wise data splitting enhancing the model applicability in real-world scenarios. Normalization techniques, such as Batch Normalization, seem crucial for optimizing model performance across diverse participant data. Also single-sensor set-ups can give acceptable performance, in particular for specific surface types of potentially high clinical relevance (e.g. stairs, ramps), offering practical and cost-effective solutions with high usability. Future research will focus on collecting ground-truth labeled data to investigate system performance in real-world settings

Aims

Conventional patient-reported surveys, used for patients undergoing total hip arthroplasty (THA), are limited by subjectivity and recall bias. Objective functional evaluation, such as gait analysis, to delineate a patient’s functional capacity and customize surgical interventions, may address these shortcomings. This systematic review endeavours to investigate the application of objective functional assessments in appraising individuals undergoing THA.

The June 2024 Research Roundup³⁶⁰ looks at: Do the associations of daily steps with mortality and incident cardiovascular disease differ by sedentary time levels?; Large-scale assessment of ChatGPT in benign and malignant bone tumours imaging report diagnosis and its potential for clinical applications; Long-term effects of diffuse idiopathic skeletal hyperostosis on physical function: a longitudinal analysis; Effect of intramuscular fat in the thigh muscles on muscle architecture and physical performance in the middle-aged females with knee osteoarthritis; Preoperative package of care for osteoarthritis an opportunity not to be missed?; Superiority of kinematic alignment over mechanical alignment in total knee arthroplasty during medium- to long-term follow-up: a meta-analysis and trial sequential analysis.

Smartphones are often equipped with inertial sensors capable of measuring individuals' physical activities. Their role in monitoring the patients' physical activities in telemedicine, however, needs to be explored. The main objective of this study was to explore the correlation between a participant's daily step counts and the daily step counts reported by their smartphone. This prospective observational study was conducted on patients undergoing lower limb orthopedic surgery and a group of non-patients. The data collection period was from 2 weeks before until four weeks after the surgery for the patients and two weeks for the non-patients. The participants' daily steps were recorded by physical activity trackers employed 24/7, and an application recorded the number of daily steps registered by the participants' smartphones. We compared the cross-correlation between the daily steps time-series taken from the smartphones and physical activity trackers in different groups of participants. We also employed mixed modeling to estimate the total number of steps. Overall, 1067 days of data were collected from 21 patients (11 females) and 10 non-patients (6 females). The cross-correlation coefficient between the smartphone and physical activity tracker was 0.70 [0.53–0.83]. The correlation in the non-patients was slightly higher than in the patients (0.74 [0.60–0.90] and 0.69 [0.52–0.81], respectively). Considering the ubiquity, convenience, and practicality of smartphones, the high correlation between the smartphones and the total daily step time-series highlights the potential usefulness of smartphones in detecting the change in the step counts in remote monitoring of the patient's physical activity

Aims

The aim of this study was to investigate the association between additional rehabilitation at the weekend, and in-hospital mortality and complications in patients with hip fracture who underwent surgery.

There is controversy regarding the effect of different approaches on recovery after THR. Collecting detailed relevant data with satisfactory compliance is difficult. Our retrospective observational multi-center study aimed to find out if the data collected via a remote coaching app can be used to monitor the speed of recovery after THR using the anterolateral (ALA), posterior (PA) and the direct anterior approach (DAA). 771 patients undergoing THR from 13 centers using the moveUP platform were identified. 239 had ALA, 345 DAA and 42 PA. There was no significant difference between the groups in the sex of patients or in preoperative HOOS Scores. There was however a significantly lower age in the DAA (64,1y) compared to ALA (66,9y), and a significantly lower Oxford Hip Score in the DAA (23,9) compared to PA(27,7). Step count measured by an activity tracker, pain killer and NSAID use was monitored via the app. We recorded when patients started driving following surgery, stopped using crutches, and their HOOS and Oxford hip scores at 6 weeks. Overall compliance with data request was 80%. Patients achieved their preoperative activity level after 25.8, 17,7 and 23.3 days, started driving a car after 33.6, 30.3 and 31.7 days, stopped painkillers after 27.5, 20.2 and 22.5 days, NSAID after 30.3, 25.7, and 24.7 days for ALA, DAA and PA respectively. Painkillers were stopped and preoperative activity levels were achieved significantly earlier favoring DAA over ALA. Similarly, crutches were abandoned significantly earlier (39.9, 29.7 and 24.4 days for ALA, DAA and PA respectively) favoring DAA and PA over ALA. HOOS scores and Oxford Hip scores improved significantly in all 3 groups at 6 weeks, without any statistically significant difference between groups in either Oxford Hip or HOOS subscores. No final conclusion can be drawn as to the superiority of either approach in this study but the remote coaching platform allowed the collection of detailed data which can be used to advise patients individually, manage expectations, improve outcomes and identify areas for further research

Smartphone-based apps that measure step-count and patient reported outcomes (PROMs) are being increasingly used to quantify recovery in total hip arthroplasty (THA). However, optimum patient-specific activity level before and during THA early-recovery is not well characterised. This study investigated 1) correlations between step-count and PROMs and 2) how patient demographics impact step-count preoperatively and during early postoperative recovery. Smartphone step-count and PROM data from 554 THA patients was retrospectively reviewed. Mean age was 64±10yr, BMI was 29±13kg/m2, 56% were female. Mean daily step count was calculated over three time-windows: 60 days prior to surgery (preop), 5–6 weeks postop (6wk), and 11–12 weeks postop (12wk). Linear correlations between step-count and HOOS12 Function and UCLA activity scores were performed. Patients were separated into three step-count levels: low (<2500steps/day), medium (2500-5500steps/day), and high (>5500steps/day). Age >65years, BMI >30, and sex were used for demographic comparisons. Student's t-tests determined significant differences in mean step-counts between demographic groups and in mean PROMs between step-count groups. UCLA correlated with step-count at all time-windows (p<0.01). HOOS12 Function correlated with step-count preoperatively and at 6wk (p<0.01). High vs low step count individuals had improved UCLA scores preoperatively (∆1.8,p<0.001), at 6wk (∆1.1,p<0.05), and 12wk (∆1.6,p<0.01), and improved HOOS12 Function scores preoperatively (∆8.4,p<0.05) and at 6wk (∆8.8,p<0.001). Younger patients had greater step-count preoperatively (4.1±3.0k vs 3.0±2.5k, p<0.01) and at 12wk (5.1±3.3k vs 3.6±2.9k, p<0.01). Males had greater step-count preoperatively (4.1±3.0k vs. 3.0±2.7k, p<0.001), at 6wk (4.5±3.2k vs 2.6±2.5k, p<0.001), and at 12wk (5.2±3.6k vs. 3.4±2.5k, p<0.001). Low BMI patients had greater step-count at 6wk (4.3±3.3k vs. 2.6±2.7k, p<0.01) and 12wk (5.0±3.6k vs. 3.6±2.6k, p<0.05). Daily step-count is significantly impacted by patient demographics and correlates with PROMs, where patients with high step count exhibit improved PROMs. Generic recovery profiles may therefore not be appropriate for benchmarking across diverse populations

Passive smartphone-based apps are becoming more common for measuring patient progress after total knee arthroplasty (TKA). Optimum activity levels during early TKA recovery haven't been well documented. This study investigated correlations between step-count and patient reported outcome measures (PROMs) and how demographics impact step-count preoperatively and during early post-operative recovery. Smartphone capture step-count data from 357 TKA patients was retrospectively reviewed. Mean age was 68±8years. 61% were female. Mean BMI was 31±6kg/m2. Mean daily step count was calculated over three time-windows: 60 days prior to surgery (preop), 5-6 weeks postop (6wk), and 11-12 weeks postop (12wk). Linear correlations between step-count and KOOS12-function and UCLA activity scores were performed. Patients were separated into three step-count levels: low (<1500steps/day), medium (1500-4000steps/day), and high (>4000steps/day). Age >65years, BMI >30kg/m2, and sex were used for demographic comparisons. Student's t-tests determined significant differences in mean step-counts between demographic groups, and in mean PROMs between step-count groups. UCLA correlated with step-count at all time-windows (p<0.01). KOOS12-Function correlated with step-count at 6wk and 12wk (p<0.05). High step-count individuals had improved PROMs compared to low step-count individuals preoperatively (UCLA: ∆1.4 [p<0.001], KOOS12-Function: ∆7.3 [p<0.05]), at 6wk (UCLA: ∆1 [p<0.01], KOOS12-Function: ∆7 [p<0.05]), and at 12wk (UCLA: ∆0.8 [p<0.05], KOOS12-Function: ∆6.5 [p<0.05]). Younger patients had greater step-count preoperatively (3.8±3.0k vs. 2.5±2.3k, p<0.01), at 6wk (3.1±2.9k vs. 2.2±2.3k, p<0.05) and at 12wk (3.9±2.6k vs. 2.8±2.6k, p<0.01). Males had greater step-count preoperatively (3.7±2.6k vs. 2.5±2.6k, p<0.001), at 6wk (3.6±2.6k vs. 1.9±2.4k, p<0.001), and at 12wk (3.9±2.3 vs. 2.8±2.8k, p<0.01). No differences in step-count were observed between low and high BMI patients at any timepoint. High step count led to improved PROMs scores compared to low step-count. Early post-operative step-count was significantly impacted by age and sex. Generic recovery profiles may not be appropriate across a diverse population

Introduction. The purpose of this study was to demonstrate the feasibility of passively collecting objective data from a commercially available smartphone-based care management platform (sbCMP) and robotic assisted total knee arthroplasty (raTKA). Methods. Secondary data analysis was performed using de-identified data from a commercial database that collected metrics from a sbCMP combined with intraoperative data collection from raTKA. Patients were included in this analysis if they underwent unilateral raTKA between July 2020 and February 2021, and were prescribed the sbCMP (n=131). The population consisted of 76 females and 55 males, with a mean age of 64 years (range, 43 – 81). Pre-operative through six-week post-operative data included step counts from the sbCMP, as well as administration of the KOOS JR. Intraoperative data included surgical times, the hip-knee-ankle angle (HKA), and medial and lateral laxity assessments from the robotic assessment. Data are presented using descriptive statistics. Comparisons were performed using a paired samples t-test, or Wilcoxon Signed-rank test, with significance assessed at p<0.05. A minimal detectable change (MDC) in the KOOS JR score was considered ½ standard deviation of the preoperative values. Results. KOOS JR scores improved from a preoperative mean of 51.5 ± 11.5 to a 6-week postoperative mean of 64 ± 10.04 (p<0.001). An MDC of 5.75 units was achieved. Step counts decreased initially and returned to preoperative values by week 6 (Figure 1, p=0.196). When evaluating time requirements from landmarking to completed surgical cuts, the median surgical time was 40.2 minutes (IQR, 29.4 – 52.0). The median absolute deformity for HKA preoperatively was 6.9 degrees (IQR, 4.1 – 10.1) and the final intraoperative median HKA was 0.9 degrees (IQR, 0.1 – 3, p<0.001). There was a difference in medial and lateral joint laxity in flexion and extension at the initial intraoperative evaluation (p<0.01). At the final evaluation there was no difference in medial and lateral joint laxity in extension (p=0.239); however, a slight difference in flexion was noted (p=0.001). Given the median values of 1.2mm (0.8 – 2.4) medially vs. 1.4mm (0.9 – 3) laterally, this difference is not likely clinically relevant. Patients who had <1 mm of medial laxity in flexion had significantly fewer step counts at week 6 post-operatively (p=0.035). There was no difference in KOOS JR scores associated with tightness (p>0.05). Discussion. The use of passively collected objective measures in a commercial database across the episode of care was feasible and demonstrated associations between intraoperative and post-operative metrics. To our knowledge, this is the first integrated data collection and reporting platform to report on these measures in a commercial population. Future research is needed in order to understand the benefit of displaying these metrics, as well as the role of variations in alignment and gap balance on function. Conclusions. Contemporary data platforms may be used to improve the understanding of individual recovery paths through real-time passive data collection throughout the episode of care. For any figures or tables, please contact the authors directly

Introduction. The purpose of this study was to characterize the recovery of physical activity following knee arthroplasty by means of step counts and flight counts (flights of stairs) measured using a smartphone-based care platform. Methods. This is a secondary data analysis on the treatment cohort of a multicenter prospective trial evaluating the use of a smartphone-based care platform for primary total and unicondylar joint arthroplasty. Participants in the treatment arm that underwent primary total or unicondylar knee arthroplasty and had at least 3 months of follow-up were included (n=367). Participants were provided the app with an associated smart watch for measuring several different health measures including daily step and flight counts. These measures were monitored preoperatively, and the following postoperative intervals were selected for review: 2–4 days, 1 month, 1.5 month, 3 months and 6 months. The data are presented as mean, standard deviation, median, and interquartile range (IQR). Signed rank tests were used to assess the difference in average of daily step counts over time. As not all patients reported having multiple stairs at home, a separate analysis was also performed on average flights of stairs (n=214). A sub-study was performed to evaluate patients who returned to preoperative levels at 1.5 months (step count) and 3 months (flight count) using an independent samples T test or Fisher's Exact test was to compare demographics between patients that returned to preoperative levels and those that did not. Results. The mean age of the step count population was 63.1 ± 8.3 years and 64.31% were female, 35.69% were male. The mean body mass index was 31.1 ± 5.9 kg/m. 2. For those who reported multiple stairs at home, the mean age was 62.6 ± 8.3 years and 62.3% were female. The mean body mass index was 30.7 ± 5.4 kg/m. 2. . As expected, the immediate post-op (2–4 days) step count (median 1257.5 steps, IQR 523 – 2267) was significantly lower than preop (median 4160 steps, IQR 2669 – 6034, p < 0.001). Approximately 50% of patients returned to preoperative step counts by 1.5 months postoperatively with a median 4,504 steps (IQR, 2711, 6121, p=0.8230, Figure 1). Improvements in step count continued throughout the remainder of follow-up with the 6-month follow-up visit (median 5517 steps, IQR 3888 – 7279) showing the greatest magnitude (p<0.001). In patients who reported stairs in their homes, approximately 64% of subjects returned to pre-op flight counts by 3 months (p=0.085), followed similar trends with significant improvements at 6 months (p=0.003). Finally, there was no difference in age, sex, BMI, or operative knee between those that returned to mean preoperative step or flight counts by 1.5 months and 3 months, respectively. Discussion and Conclusion. These data demonstrated a recovery curve similar to previously reported curves for patient reported outcome measures in the arthroplasty arena. Patients and surgeons may use this information to help set goals for recovery following total and unicondylar knee arthroplasty using objective activity measures. For any figures or tables, please contact the authors directly

Aims. Minimally invasive fixation of pelvic fragility fractures is recommended to reduce pain and allow early mobilization. The purpose of this study was to evaluate the outcome of two different stabilization techniques in bilateral fragility fractures of the sacrum (BFFS). Methods. A non-randomized, prospective study was carried out in a level 1 trauma centre. BFFS in 61 patients (mean age 80 years (SD 10); four male, 57 female) were treated surgically with bisegmental transsacral stablization (BTS; n = 41) versus spinopelvic fixation (SP; n = 20). Postoperative full weightbearing was allowed. The outcome was evaluated at two timepoints: discharge from inpatient treatment (TP1; Fitbit tracking, Zebris stance analysis), and ≥ six months (TP2; Fitbit tracking, Zebris analysis, based on modified Oswestry Disability Index (ODI), Majeed Score (MS), and the 12-Item Short Form Survey 12 (SF-12). Fracture healing was assessed by CT. The primary outcome parameter of functional recovery was the per-day step count; the secondary parameter was the subjective outcome assessed by questionnaires. Results. Overall, no baseline differences were observed between the BTS and SP cohorts. In total, 58 (BTS = 19; SP = 39) and 37 patients (BTS = 14; SP = 23) could be recruited at TP1 and TP2, respectively. Mean steps per day at TP1 were median 308 (248 to 434) in the BTS group and 254 (196 to 446) in the SP group. At TP2, median steps per day were 3,759 (2,551 to 3,926) in the BTS group and 3,191 (2,872 to 3,679) in the SP group, each with no significant difference. A significant improvement was observed in each group (p < 0.001) between timepoints. BTS patients obtained better results than SP patients in ODI (p < 0.030), MS (p = 0.007), and SF-12 physical status (p = 0.006). In all cases, CT showed sufficient fracture healing of the posterior ring. Conclusion. Both groups showed significant outcome improvement and sufficient fracture healing. Both techniques can be recommended for BFFS, although BTS was superior with respect to subjective outcome. Step-count tracking represents a reliable method to evaluate the mobility level. Cite this article: Bone Joint J 2021;103-B(3):462–468

Aims. The direct anterior (DA) approach has been associated with rapid patient recovery after total hip arthroplasty (THA) but may be associated with more frequent femoral complications including implant loosening. The objective of this study was to determine whether the addition of a collar to the femoral stem affects implant migration, patient activity, and patient function following primary THA using the DA approach. Methods. Patients were randomized to either a collared (n = 23) or collarless (n = 26) cementless femoral stem implanted using the DA approach. Canal fill ratio (CFR) was measured on the first postoperative radiographs. Patients underwent a supine radiostereometric analysis (RSA) exam postoperatively on the day of surgery and at two, four, six, 12, 26, and 52 weeks postoperatively. Patient-reported outcome measures (Western Ontario and McMaster Universities Osteoarthritis (WOMAC) Index, the 12-item Short Form Health Survey Mental and Physical Score, and University of California, Los Angeles (UCLA) Activity Score) were measured preoperatively and at each post-surgery clinic visit. Activity and function were also measured as the weekly average step count recorded by an activity tracker, and an instrumented timed up-and-go (TUG) test in clinic, respectively. Results. Comparing the RSA between the day of surgery baseline exam to two weeks postoperatively, subsidence was significantly lower (mean difference 2.23 mm (SD 0.71), p = 0.023) with collared stems, though these patients had a greater CFR (p = 0.048). There was no difference (p = 0.426) in subsidence between stems from a two-week baseline through to one year postoperatively. There were no clinically relevant differences in PROMs; and there was no difference in the change in activity (p = 0.078) or the change in functional capacity (p = 0.664) between the collared stem group and the collarless stem group at any timepoint. Conclusion. Presence of a collar on the femoral stem resulted in reduced subsidence during the first two postoperative weeks following primary THA using the DA approach. However, the clinical implications are unclear, and larger studies examining patient activity and outcomes are required. Cite this article: Bone Joint J 2020;102-B(12):1654–1661

Increasing pressure to use rapid recovery care pathways when treating patients undergoing total hip arthroplasty (THA) is evident in current health care systems for numerous reasons. Patient autonomy and health care economics has challenged the ability of THA implants to maintain functional integrity before achieving bony union. Although collared stems have been shown to provide improved axial stability, it is unclear if this stability correlates with activity levels or results in improved early function to patients compared to collarless stems. This study aims to examine the role of implant design on patient activity and implant fixation. The early follow-up period was examined as the majority of variation between implants is expected during this time-frame. Patients (n=100) with unilateral hip OA who were undergoing primary THA surgery were recruited pre-operatively to participate in this prospective randomized controlled trial. All patients were randomized to receive either a collared (n=50) or collarless (n=50) cementless femoral stem. Patients will be seen at nine appointments (pre-operative, < 2 4 hours post-operation, two-, four-, six-weeks, three-, six-months, one-, and two-years). Patients completed an instrumented timed up-and-go (TUG) test using wearable sensors at each visit, excluding the day of their surgery. Participants logged their steps using Fitbit activity trackers and a seven-day average prior to each visit was recorded. Patients also underwent supine radiostereometric analysis (RSA) imaging < 2 4 hours post-operation prior to leaving the hospital, and at all follow-up appointments. Nineteen collared stem patients and 20 collarless stem patients have been assessed. There were no demographic differences between groups. From < 2 4 hours to two weeks the collared implant subsided 0.90 ± 1.20 mm and the collarless implant subsided 3.32 ± 3.10 mm (p=0.014). From two weeks to three months the collared implant subsided 0.65 ± 1.54 mm and the collarless implant subsided 0.45 ± 0.52 mm (p=0.673). Subsidence following two weeks was lower than prior to two weeks in the collarless group (p=0.02) but not different in the collared group. Step count was reduced at two weeks compared to pre-operatively by 4078 ± 2959 steps for collared patients and 4282 ± 3187 steps for collarless patients (p=0.872). Step count increased from two weeks to three months by 6652 ± 4822 steps for collared patients and 4557 ± 2636 steps for collarless patients (p=0.289). TUG test time was increased at two weeks compared to pre-operatively by 4.71 ± 5.13 s for collared patients and 6.54 ± 10.18 s for collarless patients (p=0.551). TUG test time decreased from two weeks to three months by 7.21 ± 5.56 s for collared patients and 8.38 ± 7.20 s for collarless patients (p=0.685). There was no correlation between subsidence and step count or TUG test time. Collared implants subsided less in the first two weeks compared to collarless implants but subsequent subsidence after two weeks was not significantly different. The presence of a collar on the stem did not affect patient activity and function and these factors were not correlated to subsidence, suggesting that initial fixation is instead primarily related to implant design

Aims

A retrospective longitudinal study was conducted to compare directly volumetric wear of retrieved polyethylene inserts to predicted volumetric wear modelled from individual gait mechanics of total knee arthroplasty (TKA) patients.

Background. There is increasing impetus to use rapid recovery care pathways when treating patients undergoing total hip arthroplasty (THA). The direct anterior (DA) approach is a muscle sparing technique that is believed to support these new pathways. Implants designed for these approaches are available in both collared and collarless variations and understanding the impact each has is important for providing the best treatment to patients. Purpose/Aim of Study. This study aims to examine the role of implant design on implant fixation and patient recovery. Materials and Methods. Patients (n=50) with unilateral hip OA who were undergoing primary DA THA surgery were recruited pre-operatively to participate in this prospective randomized controlled trial. All patients were randomized to receive either a collared (n=25) or collarless (n=25) cementless, fully hydroxyapatite coated femoral stem. Patients were seen at nine appointments (pre-operative, <24 hours post-operation, two-, four-, six-weeks, three-, six-months, one-, and two-years). Patients underwent supine radiostereometric analysis (RSA) imaging <24 hours post-operation prior to leaving the hospital, and at all follow-up appointments. Patients also completed an instrumented timed up-and-go (TUG) test using wearable sensors at each visit, excluding the day of their surgery. Participants logged their steps using Fitbit activity trackers and a seven-day average prior to each visit was recorded. Findings/Results. Twenty-two patients that received a collared stem and 27 patients that received a collarless stem have been assessed. There were no demographic differences between groups. From <24 hours to two weeks the collared implants subsided 0.90 ± 1.20 mm and the collarless implants subsided 3.80 ± 3.37 mm (p=0.001). From two weeks to three months the collared implants subsided 0.67 ± 1.61 mm and the collarless implants subsided 0.45 ± 0.46 mm (p=0.377). Step count was reduced at two weeks to 3108 ± 1388 steps for collared patients and 2340 ± 1685 steps for collarless patients (p=0.072). Step count was increased at three months to 8939 ± 3494 steps for collared patients and 6114 ± 2529 steps for collarless patients (p=0.034). TUG test time was increased at two weeks compared to pre-operatively by 3.45 ± 6.01 s for collared patients and 2.29 ± 4.92 s for collarless patients (p=0.754). TUG test time decreased from two weeks to three months by 6.30 ± 6.05 s for collared patients and 5.68 ± 4.68 s for collarless patients (p=0.922). Conclusions. Collared implants subsided less in the first two weeks compared to collarless implants but subsequent subsidence after two weeks was not significantly different. Presence of a collar on the stem impacted patient activity but not function. This suggests that both the implant design as well as the surgical technique may play a role in the patient's early post-operative experience

Introduction. A smartphone-based care platform allows a customizable educational and exercise interface with patients, allowing many to recover after surgery without the need for formal physical therapy (PT). Furthermore, advances in wearable technology to monitor physical activity (PA) provides patients and physicians quantifiable metrics of the patient's recovery. The purpose of this study is to determine the feasibility of a smartphone-based exercise educational platform after primary knee arthroplasty as well as identifying factors that may predict the need for formal physical therapy. Methods. This study is part of a multi-institution, prospective study of patients after primary total knee arthroplasty (TKA) and partial knee arthroplasty (PKA) enrolled in a smartphone with smartwatch-based episode of care platform that recorded multimodal PA (steps, kcal, stairs). Postoperatively, all patients initially followed the smartphone-based exercise program. At the surgeon's discretion, patients were prescribed therapy if needed. The outcome of this study was the need for PT outside the app-based exercise program as well as time to return to preoperative step count. Variables assessed were preoperative weekly step counts (steps/day), weekly postoperative activity level (weekly step count compared to preoperative level), compliance with the exercise program (>75% completion) and patient demographic data including gender, age, BMI and narcotic use. One hundred eighty-eight patients were included in analysis: 45 PKA (24%) and 143 TKA (76%). Step count data was available on 135 patients and physical therapy data on 174. Results. Overall educational compliance was 91% and exercise compliance 34%. By 4-weeks postop, 45.6% of patients reached or exceeded their preoperative step count, including 60% of PKA and 41% of TKA (p=0.05). There was no significant difference in reaching step count based on gender (p=0.7), BMI <40kg/m2 (p=0.9) or age <65-years old (p=0.67). Sixty-three percent of patients that were compliant with the exercise program reached the step count compared to 40% of patients that weren't complaint (p=0.01). One hundred thirty-three patients (76.4%) completed the app-based exercise program without the need for PT, which included 81.4% of PKA patients and 75% of TKA patients (p=0.38). Weekly compliance with the exercise program (>75%) was significantly associated with not needing PT (p<0.001). Other factors that were significantly associated with the need for PT were a high physical activity level in postoperative week 1 (p<0.001) and a low physical activity level in postoperative week 2 (p=0.002). Conclusion. A high percentage of patients after primary knee arthroplasty were able to successfully complete the smartphone-based exercise program without the need for PT. Compliance with the exercise program was an important predictor of success. Postoperative activity level may also indicate the need for therapy as patients who were very active in the first postoperative week and then saw a decline in activity in the second week were more likely to be prescribed PT. With this platform, surgeons can monitor a patient's exercise compliance and postoperative activity level allowing many to recover at home, while being able to identify those within the first few weeks who may need structured physical therapy. For figures, tables, or references, please contact authors directly

Objectives

Our primary aim was to describe migration of the Exeter stem with a 32 mm head on highly crosslinked polyethylene and whether this is influenced by age. Our secondary aims were to assess functional outcome, satisfaction, activity, and bone mineral density (BMD) according to age.

Aims

The purpose of this exploratory study was to investigate if the 24-hour activity profile (i.e. waking activities and sleep) objectively measured using wrist-worn accelerometry of patients scheduled for total hip arthroplasty (THA) improves postoperatively.

The first three months following Total Knee Arthroplasty (TKA) provide an early window into a patient's functional outcomes, with the change of function in this time yielding valuable insight. 20 patients due to undergo primary TKA were recruited to the study. Data were recorded at three time points; pre-assessment clinic (PAC) before the operation, 6-weeks-post-operation (6WKs), at 12-weeks-post-operation (12WKs). Functional activity levels were monitored during early post-operative recovery for changes in early functional outcome, and allowed a comparison of metrics at each time point. This included direct functional testing of power output, timed functional performance in clinic, patient reported outcome measures, and multiday activity monitoring devices. Maximal power output symmetry (Power) was similar at 6WKs vs PAC (p = 0.37). At 12WKs, it had increased (p < 0.05). Timed functional performance (Performance) remained similar across all three time points (p = 0.27). Patient reported activities of daily living (ADL) performance significantly increased at 6WKs vs PAC (p < 0.05). At 12WKs, it remained similar (p = 0.10). Patient daily step count significantly decreased at 6WKs vs PAC (p < 0.05). By 12WKs, this had increased to similar levels to PAC (p = 0.30). Within the functional outcome measures, strong post-operative correlations were observed between Power and Performance (r = 0.62), Power and ADL (r = 0.49), and Performance and ADL (r = 0.61). Despite reduced measured step count and similar functional performance, patients report improved ADL at 6WKs. When symmetrical power output and measured step count have improved at 12WKs, patients report similar ADL to that at 6WKs. Multiple measures are required to get a full picture, however this highlights the different aspects measured by different tools