Remote Patient Monitoring with Wearable Sensors Following Knee Arthroplasty

Evaluating Knee Recovery Beyond Patient Reports: A Comparative Study of Smart Implantable Device-Derived Gait Metrics Versus Patient-Reported Outcome Measures in Total Knee Arthroplasty

BACKGROUND

Total Knee Arthroplasty (TKA) is frequently performed for advanced osteoarthritis, with patient-reported outcome measures (PROMs) traditionally reporting on efficacy. These subjective evaluations, although useful, may inaccurately reflect post-TKA activity levels. With technological advancements, smart implantable devices (SIDs) offer objective, real-time gait metrics, potentially providing a more accurate postoperative recovery assessment. This study compares these objective metrics with PROMs to evaluate TKA success more effectively.

METHODS

We conducted a retrospective cohort study with 88 participants undergoing TKA using a SID. Eligible patients were aged 18 years or older and had advanced osteoarthritis. We excluded those who had bilateral TKAs, joint infections, or neuromuscular disease. The SID system collected daily gait metrics, including step count, distance traveled, walking speed, stride length, cadence, and functional knee range of motion. The PROMs, including Knee Injury and Osteoarthritis Outcome Score-Joint Replacement, Veterans Rand 12 Physical Component Summary, and Veterans Rand 12 Mental Component Summary, were analyzed against SID gait metrics. Among the 88 patients, 80 provided continuous data over 12 weeks.

RESULTS

All gait metrics, except stride length, significantly increased at the 12-week point (P < .05). The PROMs also significantly improved postoperatively (P < .05). Initial low positive correlations between 12-week PROMs and SID metrics decreased after adjusting for demographic variables, leaving only weak correlations between the Veterans Rand 12 Physical Component Summary and Knee Injury and Osteoarthritis Outcome Score-Joint Replacement with functional knee range of motion (r = 0.389, P = .002; r = 0.311, P = .014, respectively), and Veterans Rand 12 Mental Component Summary with step count (r = 0.406, P = .001) and distance traveled (r = 0.376, P = .003).

CONCLUSIONS

This study indicates that both PROMs and SID gait metrics show significant improvements post-TKA, though they correlate weakly with each other, suggesting a possible discrepancy between perceived recovery and actual functional improvement. The SID gait metrics might provide a valuable addition to traditional PROMs by offering an objective representation of physical capabilities unaffected by patient compliance or subjective perceptions of recovery. Further research is needed to validate these findings in larger populations and to explore whether integrating SID metrics can enhance long-term functional outcomes.

Mobile and Computer-Based Applications for Rehabilitation Monitoring and Self-Management After Knee Arthroplasty: Scoping Review

BACKGROUND

Successful post-knee replacement rehabilitation requires adequate access to health information, social support, and periodic monitoring by a health professional. Mobile health (mHealth) and computer-based technologies are used for rehabilitation and remote monitoring. The extent of technology use and its function in post-knee replacement rehabilitation care in low and middle-income settings are unknown.

OBJECTIVE

To inform future mHealth intervention development, we conducted a scoping review to map the features and functionality of existing technologies and determine users' perspectives on telerehabilitation and technology for self-management.

METHODS

We followed the Joanna Briggs Institute methodology for scoping reviews. We searched the Embase, Medline, PsycINFO via OVID, and Cochrane Central Register of Controlled Trials databases for manuscripts published from 2001 onward. We included original research articles reporting the use of mobile or computer-based technologies by patients, health care providers, researchers, or family members. Studies were divided into the following 3 categories based on the purpose: validation studies, clinical evaluation, and end user feedback. We extracted general information on study design, technology features, proposed function, and perspectives of health care providers and patients. The protocol for this review is accessible in the Open Science Framework.

RESULTS

Of the 5960 articles, 158 that reported from high-income settings contributed to the qualitative summary (64 studies on mHealth or telerehabilitation programs, 28 validation studies, 38 studies describing users' perceptions). The highest numbers of studies were from Europe or the United Kingdom and North America regarding the use of a mobile app with or without wearables and reported mainly in the last decade. No studies were from low and middle-income settings. The primary functions of technology for remote rehabilitation were education to aid recovery and enable regular, appropriate exercises; monitoring progress of pain (n=19), activity (n=20), and exercise adherence (n=30); 1 or 2-way communication with health care professionals to facilitate the continuum of care (n=51); and goal setting (n=23). Assessment of range of motion (n=16) and gait analysis (n=10) were the commonly validated technologies developed to incorporate into a future rehabilitation program. Few studies (n=14) reported end user involvement during the development stage. We summarized the reasons for satisfaction and dissatisfaction among users across various technologies.

CONCLUSIONS

Several existing mobile and computer-based technologies facilitate post-knee replacement rehabilitation care for patients and health care providers. However, they are limited to high-income settings and may not be extrapolated to low-income settings. A systematic needs assessment of patients undergoing knee replacement and health care providers involved in rehabilitation, involving end users at all stages of development and evaluation, with clear reporting of the development and clinical evaluation can make post-knee replacement rehabilitation care in resource-poor settings accessible and cost-effective.

Detecting differences in limb load asymmetry during walking between older adult fallers and non-fallers using in-shoe sensors

BACKGROUND

Previous studies have reported that clinical walk tests could not detect differences between fallers and non-fallers in older adults. With advancements in wearable technology, it may be possible to assess differences in loading parameters in clinical settings using portable data collection methods.

RESEARCH QUESTION

The purpose of this study was to determine if wearable sensors (loadsol®) are reliable for assessing asymmetry of contact time, peak force, loading rate (LR), and impulse in older adults and determine if the insole can detect differences in these parameters between fallers and non-fallers during walking.

METHODS

Fifty-five older adults (74.1 ± 6.1 years) walked at their maximum speed on a flat floor. Force data were collected from insoles (100 Hz) during a 10-m walk test. To assess reliability, an intraclass correlation coefficient [ICC(2,k)] was generated for each asymmetry variable. To determine differences between fallers and non-fallers, analysis of covariance (ANCOVA; covariate: body mass index) was completed for each variable.

RESULTS

The ICC of peak force asymmetry (PFA) was 0.942, but other ICCs were less than 0.75. The ANCOVA results indicate that the loadsol® can detect differences in PFA between fallers and non-fallers. The PFA was significantly greater in fallers than in non-fallers.

SIGNIFICANCE

The ability to collect force data while walking using loadsol® has the potential to broaden the research questions investigated, explore clinical applications, and increase generalizability.

Postoperative Activity and Knee Function of Patients after Total Knee Arthroplasty: A Sensor-Based Monitoring Study

Inertial measurement units (IMUs) are increasingly being used to assess knee function. The aim of the study was to record patients' activity levels and to detect new parameters for knee function in the early postoperative phase after TKA. Twenty patients (n = 20) were prospectively enrolled. Two sensors were attached to the affected leg. The data were recorded from the first day after TKA until discharge. Algorithms were developed for detecting steps, range of motion, horizontal, sitting and standing postures, as well as physical therapy. The mean number of steps increased from day 1 to discharge from 117.4 (SD ± 110.5) to 858.7 (SD ± 320.1), respectively. Patients' percentage of immobilization during daytime (6 a.m. to 8 p.m.) was 91.2% on day one and still 69.9% on the last day. Patients received daily continuous passive motion therapy (CPM) for a mean of 36.4 min (SD ± 8.2). The mean angular velocity at day 1 was 12.2 degrees per second (SD ± 4.4) and increased to 28.7 (SD ± 16.4) at discharge. This study shows that IMUs monitor patients' activity postoperatively well, and a wide range of interindividual motion patterns was observed. These sensors may allow the adjustment of physical exercise programs according to the patient's individual needs.

Advances in the application of wearable sensors for gait analysis after total knee arthroplasty: a systematic review

BACKGROUND

Wearable sensors have become a complementary means for evaluation of body function and gait in lower limb osteoarthritis. This study aimed to review the applications of wearable sensors for gait analysis after total knee arthroplasty (TKA).

METHODS

Five databases, including Web of Science Core Collection, Embase, Cochrane, Medline, and PubMed, were searched for articles published between January 2010 and March 2023, using predetermined search terms that focused on wearable sensors, TKA, and gait analysis as broad areas of interest.

RESULTS

A total of 25 articles were identified, involving 823 TKA patients. Methodologies varied widely across the articles, with inconsistencies found in reported patient characteristics, sensor data and experimental protocols. Patient-reported outcome measures (PROMs) and gait variables showed various recovery times from 1 week postoperatively to 5 years postoperatively. Gait analysis using wearable sensors and PROMs showed differences in controlled environments, daily life, and when comparing different surgeries.

CONCLUSION

Wearable sensors offered the potential to remotely monitor the gait function post-TKA in both controlled environments and patients' daily life, and covered more aspects than PROMs. More cohort longitudinal studies are warranted to further confirm the benefits of this remote technology in clinical practice.

Non-Invasive Assessment of Cartilage Damage of the Human Knee Using Acoustic Emission Monitoring: A Pilot Cadaver Study

OBJECTIVE

Knee osteoarthritis is currently one of the top causes of disability in older population, a rate that will only increase in the future due to an aging population and the prevalence of obesity. However, objective assessment of treatment outcomes and remote evaluation are still in need of further development. Acoustic emission (AE) monitoring in knee diagnostics has been successfully adopted in the past; however, a wide discrepancy among the adopted AE techniques and analyses exists. This pilot study determined the most suitable metrics to differentiate progressive cartilage damage and the optimal frequency range and placement of AE sensors.

METHODS

Knee AEs were recorded in the 100-450 kHz and 15-200kH frequency ranges from a cadaver specimen in knee flexion/extension. Four stages of artificially inflicted cartilage damage and two sensor positions were investigated.

RESULTS

AE events in the lower frequency range and the following parameters provided better distinction between intact and damaged knee: hit amplitude, signal strength, and absolute energy. The medial condyle area of the knee was less prone to artefacts and unsystematic noise. Multiple reopenings of the knee compartment in the process of introducing the damage negatively affected the quality of the measurements.

CONCLUSION

Results may improve AE recording techniques in future cadaveric and clinical studies.

SIGNIFICANCE

This was the first study to evaluate progressive cartilage damage using AEs in a cadaver specimen. The findings of this study encourage further investigation of joint AE monitoring techniques.

Remote Therapeutic Monitoring in Rheumatic and Musculoskeletal Diseases: Opportunities and Implementation

Therapeutic Monitoring (RTM) is a new program in the United States that began in 2022 allowing electronic patient-reported outcomes (ePRO) and other patient-generated data to be reviewed by clinical staff between visits so that patients can receive clinical attention as needed. Remote Therapeutic Monitoring simultaneously enhances the capacity to generate prospective longitudinal data that may be useful for secondary research purposes. As many governmental and private insurance programs in the United States now provide reimbursement for Remote Therapeutic Monitoring, increasing numbers of rheumatologists may be incentivized to provide this service for their patient populations. Launched in 2015, the ArthritisPower® Research Registry and associated mobile and desktop application, registered with the Food & Drug Administration (FDA) as a Class I medical device, enables patients to track their disease across dozens of domains and to securely participate in voluntary research studies. ArthritisPower, in partnership with Illumination Health, has developed infrastructure and a clinical workflow for Remote Therapeutic Monitoring that will help rheumatologists more closely track their patients' disease activity and flares, identify primary non-adherence, record changes in key health domains (e.g. fatigue, pain, physical function, mental health) and meet the needs for other data elements important for clinical care identified by individual providers. Ultimately, the approach to use digital health tools between visits seeks to improve clinical outcomes for patients with rheumatic and musculoskeletal diseases. This editorial review discusses the evolution of remote monitoring in rheumatologic care, describes the opportunities for physician reimbursement as of 2023, and provides a suggested workflow in order to establish Remote Therapeutic Monitoring within rheumatology practices.

Do the Revision Rates of Arthroplasty Surgeons Correlate With Postoperative Patient-reported Outcome Measure Scores? A Study From the Australian Orthopaedic Association National Joint Replacement Registry

BACKGROUND

Patient-reported outcome measures (PROMs) are a pragmatic and efficient means to evaluate the functional quality of arthroplasty beyond revision rates, which are used by most joint replacement registries to judge success. The relationship between these two measures of quality-revision rates and PROMs-is unknown, and not every procedure with a poor functional result is revised. It is logical-although still untested-that higher cumulative revision rates correlate inversely with PROMs for individual surgeons; more revisions are associated with lower PROM scores.

QUESTIONS/PURPOSES

We used data from a large national joint replacement registry to ask: (1) Does a surgeon's early THA cumulative percent revision (CPR) rate and (2) early TKA CPR rate correlate with the postoperative PROMs of patients undergoing primary THA and TKA, respectively, who have not undergone revision?

METHODS

Elective primary THA and TKA procedures in patients with a primary diagnosis of osteoarthritis that were performed between August 2018 and December 2020 and registered in the Australian Orthopaedic Association National Joint Replacement Registry PROMs program were eligible. THAs and TKAs were eligible for inclusion in the primary analysis if 6-month postoperative PROMs were available, the operating surgeon was clearly identified, and the surgeon had performed at least 50 primary THAs or TKAs. Based on the inclusion criteria, 17,668 THAs were performed at eligible sites. We excluded 8878 procedures that were not matched to the PROMs program, leaving 8790 procedures. A further 790 were excluded because they were performed by unknown or ineligible surgeons or were revised, leaving 8000 procedures performed by 235 eligible surgeons, including 4256 (53%; 3744 cases of missing data) patients who had postoperative Oxford Hip Scores and 4242 (53%; 3758 cases of missing data) patients who had a postoperative EQ-VAS score recorded. Complete covariate data were available for 3939 procedures for the Oxford Hip Score and for 3941 procedures for the EQ-VAS. A total of 26,624 TKAs were performed at eligible sites. We excluded 12,685 procedures that were not matched to the PROMs program, leaving 13,939 procedures. A further 920 were excluded because they were performed by unknown or ineligible surgeons, or because they were revisions, leaving 13,019 procedures performed by 276 eligible surgeons, including 6730 (52%; 6289 cases of missing data) patients who had had postoperative Oxford Knee Scores and 6728 (52%; 6291 cases of missing data) patients who had a postoperative EQ-VAS score recorded. Complete covariate data were available for 6228 procedures for the Oxford Knee Score and for 6241 procedures for the EQ-VAS. The Spearman correlation between the operating surgeon's 2-year CPR and 6-month postoperative EQ-VAS Health and Oxford Hip or Oxford Knee Score was evaluated for THA and TKA procedures where a revision had not been performed. Associations between postoperative Oxford and EQ-VAS scores and a surgeon's 2-year CPR were estimated based on multivariate Tobit regressions and a cumulative link model with a probit link, adjusting for patient age, gender, ASA score, BMI category, preoperative PROMs, as well as surgical approach for THA. Missing data were accounted for using multiple imputation, with models assuming they were missing at random and a worst-case scenario.

RESULTS

Of the eligible THA procedures, postoperative Oxford Hip Score and surgeon 2-year CPR were correlated so weakly as to be clinically irrelevant (Spearman correlation ρ = -0.09; p < 0.001), and the correlation with postoperative EQ-VAS was close to zero (ρ = -0.02; p = 0.25). Of the eligible TKA procedures, postoperative Oxford Knee Score and EQ-VAS and surgeon 2-year CPR were correlated so weakly as to be clinically irrelevant (ρ = -0.04; p = 0.004 and ρ = 0.03; p = 0.006, respectively). All models accounting for missing data found the same result.

CONCLUSION

A surgeon's 2-year CPR did not exhibit a clinically relevant correlation with PROMs after THA or TKA, and all surgeons had similar postoperative Oxford scores. PROMs, revision rates, or both may be inaccurate or imperfect indicators of successful arthroplasty. Missing data may limit the findings of this study, although the results were consistent under a variety of different missing data scenarios. Innumerable factors contribute to arthroplasty results, including patient-related variables, differences in implant design, and the technical quality of the procedure. PROMs and revision rates may be analyzing two different facets of function after arthroplasty. Although surgeon variables are associated with revision rates, patient factors may exert a stronger influence on functional outcomes. Future research should identify variables that correlate with functional outcome. Additionally, given the gross level of function that Oxford scores record, outcome measures that can identify clinically meaningful functional differences are required. The use of Oxford scores in national arthroplasty registries may rightfully be questioned.

LEVEL OF EVIDENCE

Level III, therapeutic study.

Readiness for implementation of novel digital health interventions for postoperative monitoring: a systematic review and clinical innovation network analysis

An increasing number of digital health interventions (DHIs) for remote postoperative monitoring have been developed and evaluated. This systematic review identifies DHIs for postoperative monitoring and evaluates their readiness for implementation into routine health care. Studies were defined according to idea, development, exploration, assessment, and long-term follow-up (IDEAL) stages of innovation. A novel clinical innovation network analysis used coauthorship and citations to examine collaboration and progression within the field. 126 DHIs were identified, with 101 (80%) being early stage innovations (IDEAL stage 1 and 2a). None of the DHIs identified had large-scale routine implementation. There is little evidence of collaboration, and there are clear omissions in the evaluation of feasibility, accessibility, and the health-care impact. Use of DHIs for postoperative monitoring remains at an early stage of innovation, with promising but generally low-quality supporting evidence. Comprehensive evaluation within high-quality, large-scale trials and real-world data are required to definitively establish readiness for routine implementation.

Remote Patient Monitoring Following Total Joint Arthroplasty

This review article presents the current state of remote patient monitoring (RPM) in total joint arthroplasty. RPM refers to the use of telecommunication with wearable and implantable technology to assess and treat patients. Several forms of RPM are discussed including telemedicine, patient engagement platforms, wearable devices, and implantable devices. The benefits to patients and physicians are discussed in the context of postoperative monitoring. Insurance coverage and reimbursement of these technologies are reviewed.

A comparison of machine learning models' accuracy in predicting lower-limb joints' kinematics, kinetics, and muscle forces from wearable sensors

A combination of wearable sensors' data and Machine Learning (ML) techniques has been used in many studies to predict specific joint angles and moments. The aim of this study was to compare the performance of four different non-linear regression ML models to estimate lower-limb joints' kinematics, kinetics, and muscle forces using Inertial Measurement Units (IMUs) and electromyographys' (EMGs) data. Seventeen healthy volunteers (9F, 28 ± 5 years) were asked to walk over-ground for a minimum of 16 trials. For each trial, marker trajectories and three force-plates data were recorded to calculate pelvis, hip, knee, and ankle kinematics and kinetics, and muscle forces (the targets), as well as 7 IMUs and 16 EMGs. The features from sensors' data were extracted using the Tsfresh python package and fed into 4 ML models; Convolutional Neural Networks (CNN), Random Forest (RF), Support Vector Machine, and Multivariate Adaptive Regression Spline for targets' prediction. The RF and CNN models outperformed the other ML models by providing lower prediction errors in all intended targets with a lower computational cost. This study suggested that a combination of wearable sensors' data with an RF or a CNN model is a promising tool to overcome the limitations of traditional optical motion capture for 3D gait analysis.

The Economic Impact of a Pilot Digital Day-Case Pathway for Knee Arthroplasty in a U.K. Setting

Knee replacements are an increasingly common procedure in the U.K. National Health Service (NHS). Importantly, the pathway for such procedures represents a prime opportunity to leverage digital technology, modernize and streamline the approach to care, and free up resources.

Methods

In this 21-patient pilot study, we assessed the impact of implementing a digital day-case pathway for knee replacement surgery at the Calderdale and Huddersfield NHS Foundation trust.

Results

Fourteen (67%) of the 21 eligible patients were treated as day cases, with an average length of stay of 8.8 hours. The pilot data were utilized to model the potential impact of implementing a digital day-case program more widely across the trust. This model showed increased efficiency over the entire episode of care, with reductions in physiotherapy appointments, preoperative visits, hospital days, and face-to-face consultations. Not only would these improvements free up capacity, but they would also result in an estimated saving of £240,540 to the trust while reducing the CO₂ footprint of knee replacements by 119,381 kg CO₂ emitted. A sensitivity analysis revealed that, even with substantial variation of several key variables within the pathway, a trust-wide digital day-case program would still be a cost-saving measure.

Conclusions

Overall, the present study supports the growing notion that digital technology can facilitate the transformation of care pathways, resulting in greater efficiency and financial savings for health-care providers while reducing the time patients spend in the hospital.

Level of Evidence

Therapeutic Level II. See Instructions for Authors for a complete description of levels of evidence.

Validation of 3D Knee Kinematics during Gait on Treadmill with an Instrumented Knee Brace

To test a novel instrumented knee brace intended for use as a rehabilitation system, based on inertial measurement units (IMU) to monitor home-based exercises, the device was compared to the gold standard of motion analysis. The purpose was to validate a new calibration method through functional tasks and assessed the value of adding magnetometers for motion analysis. Thirteen healthy young adults performed a 60-second gait test at a comfortable walking speed on a treadmill. Knee kinematics were captured simultaneously, using the instrumented knee brace and an optoelectronic camera system (OCS). The intraclass correlation coefficient (ICC) showed excellent reliability for the three axes of rotation with and without magnetometers, with values ranging between 0.900 and 0.972. Pearson's r coefficient showed good to excellent correlation for the three axes, with the root mean square error (RMSE) under 3° with the IMUs and slightly higher with the magnetometers. The instrumented knee brace obtained certain clinical parameters, as did the OCS. The instrumented knee brace seems to be a valid tool to assess ambulatory knee kinematics, with an RMSE of <3°, which is sufficient for clinical interpretations. Indeed, this portable system can obtain certain clinical parameters just as well as the gold standard of motion analysis. However, the addition of magnetometers showed no significant advantage in terms of enhancing accuracy.

Follow-up after arthroplasty surgery : a changing landscape

We aim to explore the potential technologies for monitoring and assessment of patients undergoing arthroplasty by examining selected literature focusing on the technology currently available and reflecting on possible future development and application. The reviewed literature indicates a large variety of different hardware and software, widely available and used in a limited manner, to assess patients' performance. There are extensive opportunities to enhance and integrate the systems which are already in existence to develop patient-specific pathways for rehabilitation.Cite this article: Bone Joint J 2022;104-B(10):1104-1109.

A Novel Walking Activity Recognition Model for Rotation Time Series Collected by a Wearable Sensor in a Free-Living Environment

Solutions to assess walking deficiencies are widespread and largely used in healthcare. Wearable sensors are particularly appealing, as they offer the possibility to monitor gait in everyday life, outside a facility in which the context of evaluation biases the measure. While some wearable sensors are powerful enough to integrate complex walking activity recognition models, non-invasive lightweight sensors do not always have the computing or memory capacity to run them. In this paper, we propose a walking activity recognition model that offers a viable solution to this problem for any wearable sensors that measure rotational motion of body parts. Specifically, the model was trained and tuned using data collected by a motion sensor in the form of a unit quaternion time series recording the hip rotation over time. This time series was then transformed into a real-valued time series of geodesic distances between consecutive quaternions. Moving average and moving standard deviation versions of this time series were fed to standard machine learning classification algorithms. To compare the different models, we used metrics to assess classification performance (precision and accuracy) while maintaining the detection prevalence at the level of the prevalence of walking activities in the data, as well as metrics to assess change point detection capability and computation time. Our results suggest that the walking activity recognition model with a decision tree classifier yields the best compromise in terms of precision and computation time. The sensor that was used had purposely low computing and memory capacity so that reported performances can be thought of as the lower bounds of what can be achieved. Walking activity recognition is performed online, i.e., on-the-fly, which further extends the range of applicability of our model to sensors with very low memory capacity.

Orthopedic Telemedicine Outpatient Practice Diagnoses Set during the First COVID-19 Pandemic Lockdown-Individual Observation

The COVID-19 pandemic has caused a substantial intensification of the telemedicine transformation process in orthopedics since 2020. In the light of the legal regulations introduced in Poland, from the beginning of the SARS-CoV-2 pandemic, physicians, including orthopedic surgeons, have had the opportunity to conduct specialist teleconsultations. Teleconsultations increase epidemiological safety and significantly reduce the exposure of patients and medical staff to direct transmission of the viral vector and the spread of infections. The study aimed to describe diagnoses and clinical aspects of consecutive orthopedic teleconsultations (TC) during the pandemic lockdown. The diagnoses were set according to the International Classification of Diseases (ICD-10). Hybrid teleconsultations used smartphones and obligatory Electronic Health Record (EHR) with supplemental voice, SMS, MMS, Medical images, documents, and video conferencing if necessary. One hundred ninety-eight consecutive orthopedic teleconsultations were served for 615 women and 683 men (mean age 41.82 years ± 11.47 years). The most frequently diagnosed diseases were non-acute orthopedic disorders "M" (65.3%) and injuries "S" (26.3%). Back pain (M54) was the most frequent diagnosis (25.5%). Although virtual orthopedic consultation cannot replace an entire personal visit to a specialist orthopedic surgeon, in many cases, teleconsultation enables medical staff to continue to participate in providing medical services at a sufficiently high medical level to ensure patient and physician. The unified approach to TC diagnoses using ICD-10 or ICD-11 may improve further research on telemedicine-related orthopedics repeatability. Future research directions should address orthopedic teleconsultations' practical aspects and highlight legal, organizational, and technological issues with their implementations.

The Intra- and Inter-Rater Reliability of a Hip Rotation Range-of-Motion Measurement Using a Smartphone Application in Academy Football (Soccer) Players

The clinical assessment of hip rotation range-of-motion (ROM) is important for managing hip and groin injuries in footballers. Previously published reliability studies on hip ROM have employed protocols that are difficult to replicate under everyday clinical conditions. This single trial, intra- and inter-rater reliability study included 41 male academy football (soccer) players, aged 14–15 years, from one European football academy. Passive hip internal rotation (IR) and external rotation (ER) ROM were measured in supine with hip and knee flexed to 90°. The ROM was determined using a smartphone application, with the smartphone attached to the lower leg. The tests were performed on two separate occasions, one week apart, by two different physiotherapists and on both sides (left and right hips). Reliability was evaluated using Intra-Class Correlation Coefficients (ICCs) and Minimal Detectable Change (MDC). Hip IR and ER ROM displayed moderate to good intra-rater agreement (ICCs 0.54–0.75), with MDCs ranging from 10.9° to 16.4°. Inter-rater reliability displayed poor to moderate reliability (ICCs 0.33–0.75), with MDCs ranging from 11.7° to 16.5°. A hip rotation ROM test using a smartphone application and a protocol closely reflecting everyday clinical conditions displayed moderate to good intra-rater reliability and poor to moderate inter-rater reliability. Due to the high MDCs, the practical applicability of this test procedure is limited and further refinement is necessary.