Search Results (159)

Background: Large positive responses to placebo are common in clinical trials and pose a major challenge when evaluating different treatments, including new foods. Standard between-group comparisons may fail to detect true effects when placebo improvements are significant. We aimed to demonstrate how a simple dose–response correlation method can help differentiate genuine positive responses from those experienced with placebo through secondary analysis of a randomized controlled clinical trial of powdered Rosa-canina fruits. Methods: Data were reanalyzed from a multicenter, double-blind, randomized, placebo-controlled trial (N = 120; ClinicalTrials.gov NCT01459939) evaluating the effects of standardized Rosa-canina powder in hip and knee osteoarthritis (OA). Participants received fixed doses, leading to variability in mg/kg exposure due to different body weights. Pearson correlations between dose/kg and changes in WOMAC pain and function at 6 and 12 weeks were calculated separately for the active and placebo groups. Standard between-group comparisons were also performed. Results: Both groups showed significant improvement, over 50%, with no statistically significant differences between them in WOMAC pain or function. However, only the active group, which received a food supplement, exhibited a consistent negative correlation between body weight and symptom improvement at 6 and 12 weeks, suggesting greater benefit with higher dose per kilogram of body weight. No dose–response relationship was observed in the placebo recipients. Therefore, weight-stratified plots revealed an exposure–response gradient in the active group. Conclusions: Dose–response correlation analysis uncovered positive effects of Rosa-canina as a nutrient that were not detectable through standard between-group comparisons. This is consistent with findings from earlier rose-hip research. This low-cost, easy-to-implement method may help distinguish active effects from placebo responses in trials with large nonspecific improvements. Incorporating such analyses could improve the identification of nutrients containing biologically active preparations and support dose selection in future clinical research. Full article

Background: Patient-reported outcome measures (PROMs) provide important insights into recovery after anterior cruciate ligament reconstruction (ACLR). Previous research suggests that males and females recover differently after ACLR, with females reporting greater pain, slower functional gains, and lower psychological readiness at later stages of rehabilitation. However, it is unknown if patient-reported outcomes differ by sex early after ACLR. To address this gap, we conducted a cross-sectional analysis comparing patient-reported outcome measures between sexes three months after ACLR. We hypothesized that females would report worse PROMs compared to males. Methods: This cross-sectional analysis used data from a prospectively maintained ACL reconstruction cohort. Fifty-six individuals (female: 23 and male: 33) with primary, unilateral ACLR completed PROMs three months after surgery. These PROMs included the Knee Injury and Osteoarthritis Outcome Score (KOOS; Symptoms, Pain, Activities of Daily Living, Sport and Recreation, Quality of Life), International Knee Documentation Committee (IKDC) subjective score, Knee Outcome Survey–Activities of Daily Living Scale (KOS-ADLS), Anterior Cruciate Ligament–Return to Sport After Injury (ACL-RSI), and the Tampa Scale of Kinesiophobia (TSK). All outcomes were expressed on a 0 to 100 percent scale, with higher scores indicating better outcomes, except for TSK, where lower scores indicated better outcomes. Normality was assessed within sex, using the Shapiro–Wilk test. Two-tailed independent-samples t-tests with Welch correction were used for approximately normal variables; otherwise, Mann–Whitney U tests were utilized (α = 0.05). Several outcomes had limited statistical power to detect MCID-sized differences, and findings for these measures should be interpreted cautiously. Results: No significant differences between sexes were found for any of the PROMs. Males trended towards having better KOOS Sport and Recreation and IKDC, but these were not statistically significant, and the effect sizes were small-to-moderate. Conclusions: No statistically significant sex-based differences were detected in PROMs at approximately 3 months after ACLR, indicating that any sex-related divergences between these measures may not occur until later in recovery. Full article

Osteoarthritis (OA) is a severe and progressive joint disease that usually affects elderly people. The consequence of this disease in its advanced stage is the need for total knee arthroplasty (TKA). Over the years, there has been a constant increase in the number of TKA procedures, with a predicted increase to 1.26 million procedures by 2030. Diagnostics are based on conventional radiography, although advanced techniques such as radiostereometry, SPECT/CT and PET/CT, which enable early detection of micromigration, are gaining increasing recognition. Vibroarthrography (VAG) is a proposed supplement to diagnostics, enabling the assessment of the characteristics of vibrations and friction of joint surfaces, thus supporting the process of early detection of endoprosthesis instability. The combination of conventional and alternative diagnostic methods, including vibroarthrography, may improve the detection of early TKA loosening. This may also result in increased implant durability. The aim of this article is to review the current state of knowledge on the classification and analysis of endoprosthesis loosening mechanisms. In addition, classic and modern methods of detecting and monitoring loosening are discussed, with particular emphasis on vibroarthrography as a potential tool for early diagnosis. Full article

Background: Knee osteoarthritis (OA) is a leading cause of disability globally. Conventional physiotherapy, while effective, faces barriers including accessibility and adherence. Telerehabilitation augmented by wearable sensor technology and AI-driven feedback offers a scalable alternative. Objective: This pilot randomized controlled trial compared the feasibility, safety, and preliminary clinical effectiveness of a sensor-based telerehabilitation protocol using the KneE-PAD patient monitoring approach which was also combined with an avatar-guided visual feedback add-on tool. Although this approach is capable of AI-driven postural error detection, this feature was not enabled during the current study, and feedback was provided solely through visual cues. Methods: Twenty adults with radiographically confirmed Kellgren–Lawrence grade 1 to 3 knee OA were randomized into two groups (Control/Intervention groups, n = 10 in each). The control group received in-person physiotherapy, while the intervention group engaged in remote rehabilitation supported by wearable sEMG and IMU sensors. The 8-week program included supervised and home-based sessions. Primary outcomes were WOMAC scores (Functionality/Pain), quadriceps strength, and sEMG-derived neuromuscular activation. Secondary outcomes included Timed Up and Go test (TUG), psychological measures (HADS, TSK), and self-efficacy measure (ASES). Analyses employed both parametric and non-parametric statistics including an effect size estimation. Results: Both groups demonstrated significant improvements in WOMAC total scores (Intervention: −11.8 points; Control: −6.4 points), exceeding the minimal clinically important difference (MCID) for knee OA. Strength and mobility also improved significantly in both groups, with the Intervention group showing superior gains in sEMG measures (RMS: p = 0.0077; Peak-to-Peak: p < 0.005), indicating enhanced neuromuscular adaptation. TUG performance improved more in the intervention group (–3.17 s vs. –2.57 s, p = 0.037). Psychological outcomes favored the control group, particularly in depression scores (HADS-D, t(18) = 2.37, p = 0.03). Adherence was high (94.8%), with zero attrition and no adverse events. Conclusions: The KneE-PAD monitoring approach offers a feasible and clinically effective alternative to conventional physiotherapy, enhancing neuromuscular outcomes through real-time sensor feedback. These findings support the viability of intelligent telerehabilitation for scalable OA care and inform the design of future large-scale trials. Full article

This study proposes a hybrid analytical framework for detecting chondromalacia using vibroacoustic (VAG) signals from patients with knee osteoarthritis (OA) and healthy controls (HCs). The methodology combines nonlinear signal decomposition, feature extraction, and deep learning classification. Raw VAG signals, recorded with a custom multi-sensor system during open (OKC) and closed (CKC) kinetic chain knee flexion–extension, underwent preprocessing (denoising, segmentation, normalization). Ensemble Empirical Mode Decomposition (EEMD) was used to isolate Intrinsic Mode Functions (IMFs), and Detrended Fluctuation Analysis (DFA) computed local (α₁) and global (α₂) scaling exponents as well as breakpoint location. Frequency–energy features of IMFs were statistically assessed and selected via Neighborhood Component Analysis (NCA) for support vector machine (SVM) classification. Additionally, reconstructed α₁/α₂-based signals and raw signals were converted into continuous wavelet transform (CWT) scalograms, classified with convolutional neural networks (CNNs) at two resolutions. The SVM approach achieved the best performance in CKC conditions (accuracy 0.87, AUC 0.91). CNN classification on CWT scalograms also demonstrated robust OA/HC discrimination with acceptable computational times at higher resolutions. Results suggest that combining multiscale decomposition, nonlinear fluctuation analysis, and deep learning enables accurate, non-invasive detection of cartilage degeneration, with potential for early knee pathology diagnosis. Full article

Background and Objectives: Evaluating osteoarthritis (OA) care quality is increasingly relevant for service improvement and benchmarking purposes. The Osteoarthritis Quality Indicator questionnaire (OA-QI) measures patient-reported guideline-concordant care; however, no version has been tested in Italian primary care or bilingual contexts. This study aimed to introduce the OA-QI version 3 (OA-QI v3) in German and Italian, assess its applicability in practice, and examine its acceptability and reliability. Materials and Methods: A cross-sectional survey was conducted using the South Tyrolean General Practice Research Network. Thirty-eight general practitioners recruited 266 patients with hip or knee OA. Patients completed the OA-QI v3 in German or Italian, with subsamples for comprehensibility testing (n = 38) and retest reliability after 14 days (n = 36). Test–retest reliability was analyzed using percent agreement, Cohen’s κ, intraclass correlation coefficients (ICC), and standard error of measurement. The smallest detectable change was analyzed to estimate factual change. Results: Response rate reached 95% of the targeted patients. Patient feedback showed good comprehensibility and ease of use in both languages. Adherence to recommended quality indicators varied, with strengths in physical activity advice, NSAID prescription, and pain assessment, but gaps in weight management, occupational counseling, and assistive devices. Test–retest reliability ranged from fair to substantial at the item level (κ = 0.33–0.69) and was moderate for the total score (ICC = 0.55, 95% CI 0.28–0.74). While measurement error restricted individual-level interpretation, reliability at the practice or institutional level supports application for benchmarking and quality monitoring. Conclusions: The OA-QI v3 was feasible, acceptable, and reliable for group-level assessments in South Tyrol. These findings position OA-QI v3 as a practical tool for identifying care gaps and guiding quality improvement, while providing important lessons for the full validation of the German and Italian versions in larger cross-national samples. Full article

The tissue covering the bones in synovial joints is called articular cartilage. Chondrocytes produce and maintain the extracellular matrix and, based on their shape and the orientation of the collagen fibers, articular cartilage is separated into four histological zones: superficial, middle, deep, and calcified zones. Osteoarthritis is a degenerative joint disorder in which mechanical, biochemical, and inflammatory factors contribute to the disruption of the balance between extracellular matrix synthesis and degradation. This article aims to review the literature published to date by identifying the techniques most used in immunohistochemistry and histology for the detection and grading of knee osteoarthritis in rabbit/rat models. A systematic review was carried out using databases to find publications that assessed osteoarthritis in rabbit/rat knee models using histological and immunohistochemical methods. Out of 766 initial articles, 56 met the criteria. Hematoxylin–Eosin and Safranin O demonstrated clear distinctions between healthy and osteoarthritis cartilage. Immunohistochemical findings showed decreased expression of type II collagen and increased expression of matrix metalloproteinases and caspase-3 in osteoarthritis cartilage. Although both have limitations, histology stains are useful for evaluating cartilage structure and osteoarthritis progression. On the other hand, immunohistochemistry techniques support established osteoarthritis processes, including apoptosis, metalloproteinases activity, and collagen degradation. Future research should explore additional pathways to improve osteoarthritis understanding. Full article

Knee osteoarthritis (OA) is a prevalent condition in older adults that often results in impaired gait and balance, increased risk of falls, and reduced quality of life. Conventional clinical assessments may not adequately capture these deficiencies. This study investigated the gait and balance of elderly individuals with knee OA using wearable inertial measurement units (IMUs). Forty-four participants with Kellgren–Lawrence grade 2–3 knee OA (71.23 ± 5.75 years) and forty-five age-matched controls (70.87 ± 4.30 years) completed dynamic balance (balance board), static balance (single-leg stance), ‘timed up and go’ (TUG), and normal walking tasks. Between 2 and 8 IMUs, depending on the task, were placed on the head, chest, waist, knees, ankles, soles, and balance board to record kinematic data. Balance was quantified using absolute angular velocity and linear acceleration, with group differences analyzed by MANOVA and Bonferroni-adjusted univariate tests. The participants with knee OA exhibited greater gait asymmetry, although the difference was not significant. However, they consistently demonstrated higher absolute angular velocities than controls across most body segments during static and dynamic tasks, indicating reduced postural stability. No group differences were observed in TUG performance. These findings suggest that IMU-based measures, particularly angular velocity, are sensitive to balance impairment detection in knee OA. Incorporating IMU technology into clinical assessments may facilitate early identification of instability and guide targeted interventions to reduce fall risk. Full article

Objectives: Materials with ceramic surface treatments have been adopted in total knee arthroplasty (TKA) to limit polyethylene wear and thus extend implant longevity. This study evaluated, at a single center, mid-term survivorship and clinical outcomes for a mobile-bearing knee prosthesis with a titanium–niobium nitride (TiNbN) coating. Methods: A total of 150 patients who underwent primary cemented TKA using the same TiNbN-coated mobile-bearing prosthesis were identified through the institutional database. Of these, 102 patients (102 knees) attended the follow-up examination and provided informed consent to participate in this study. All patients underwent comprehensive clinical and radiological assessment. Primary outcomes were the Forgotten Joint Score (FJS) and the Knee Injury and Osteoarthritis Outcome Score (KOOS). Results: After a mean follow-up period of 7.9 years, two revision surgeries were recorded. One revision was performed due to late periprosthetic joint infection, while the other involved synovectomy and liner exchange due to persistent stiffness and pain. At 9 years follow-up, overall survivorship of the TiNbN-coated TKA was 97.1% (95% CI, 88.4–99.3%). Mean FJS and KOOS were 70.0 (range 29–100) and 70.6 (range 24–98), respectively. No sex-based differences were detected in clinical outcomes or implant survivorship. Conclusions: The TiNbN-coated mobile-bearing knee prosthesis demonstrated favorable mid-term survivorship and patient-reported outcomes. These findings support its use as a treatment option for knee osteoarthritis, with performance comparable to contemporary TKA designs. Full article

Background and objectives: Patient-specific components (PSC) represent an innovative option for total knee arthroplasty (TKA) in advanced osteoarthritis. Their effectiveness, however, closely relies on accurate positioning. Our study investigates the accuracy achieved by means of an inertial-based extramedullary cutting guide and the postoperative clinical and radiographic outcomes. Methods and materials: This was a prospective, single-arm, pilot study involving patients undergoing primary TKA with YourKnee^TM PSC. Femoral and tibial bone resections were performed using the Perseus inertial-based extramedullary cutting guide. Postoperative mechanical alignment and component positioning were assessed by computed tomography. Clinical outcomes were evaluated preoperatively and at 1, 3, 6, and 12 months postoperatively by main knee function and clinical outcome measures. Results: The study population included a small cohort (n= 12, four females/eight males, mean age 69 ± 5.65 years, mean BMI 25.7 ± 3.8 kg/m², KL grade > 3) with no control group. The mean absolute error between the planned and obtained Hip–Knee–Ankle angle was 1.36° ± 1.06 and within ±3° of all cases. Mean coronal alignment error was 1.87° ± 0.87 and 1.67° ± 0.75 for the femoral and tibial components, respectively. The mean sagittal alignment error was 1.89° ± 1.24 and 2.45° ± 0.87 for the femoral and the tibial components, respectively. Patients showed significant improvement in clinical and functional scores within the first 6 months: OKS increased from 20.64 ± 2.77 at the preoperative screening to 42.27 ± 4.34 (p < 0.0001), total KSS rose from 90.64 ± 17.25 to 169.36 ± 23.57 (p < 0.0001), and FJS reached 85.09 ± 17.14 at 6 months (p = 0.0031), indicating excellent functional recovery and forgotten joint effect. Knee ROM improved from 90.91° ± 11.14 to 110.36° ± 8.44 (p < 0.0001). After 6 months, outcome scores plateaued, suggesting an early stabilization of clinical benefits. No signs of radiolucency were detected on X-rays at 3- and 12-month follow-ups. Conclusions: The Perseus inertial-based extramedullary cutting guide used in combination with the YourKnee^TM PSCs resulted in accurate intraoperative prosthesis positioning and significant improvements in clinical and functional outcomes at 6 months after surgery. Despite the small sample size and absence of a control group, the results suggest that such combination represents a viable option to conventional surgical instrumentation and current off-the-shelf prosthetic designs. Full article

Sleep is a vital physiological process for recovery and health. In people with knee osteoarthritis (OA), disrupted sleep is common and linked to worse clinical outcomes. Commercial sleep trackers provide an accessible option to monitor sleep in this population, but their accuracy for detecting sleep, wake, and sleep stages remains uncertain. This study compared nighttime sleep data from polysomnography (PSG) and Fitbit Sense in individuals with knee OA and insomnia. Data were collected from 53 participants (60.4% women, mean age 51 ± 8.2 years) over 62 nights using simultaneous PSG and Fitbit recording. Fitbit Sense showed high accuracy (85.76%) and sensitivity (95.95%) for detecting sleep but lower specificity (50.96%), indicating difficulty separating quiet wakefulness from sleep. Agreement with PSG was higher on nights with longer total sleep time, higher sleep efficiency, shorter sleep onset, and fewer awakenings, suggesting better performance when sleep is less fragmented. The device showed limited precision in classifying sleep stages, often misclassifying deep and REM sleep as light sleep. Despite these issues, Fitbit Sense may serve as a useful complementary tool for monitoring sleep duration, timing, and regularity in this population. However, sleep stage and fragmentation data should be interpreted cautiously in both clinical and research settings. Full article

Osteochondritis Dissecans (OCD) is a joint condition characterized by damage to the surface of the joint and the underlying subchondral bone, leading to early-onset osteoarthritis. It predominantly affects the knee, elbow, and ankle, with higher prevalence in juveniles actively participating in sports, which complicates the condition due to slow healing processes and prolonged restrictions on physical activities. This review aims to summarize current knowledge on OCD in athletes, with emphasis on sport-specific risk factors, diagnosis, and treatment, to support clinical decision-making and future research. We conducted searches in the PubMed and Embase databases, covering the period from 2014 to 2024. The keywords used in the search covered most common sports in combination with term osteochondritis dissecans. This review examines the impacts of various sports on the development of OCD, analyzing prevalence and risk factors, with a focus on sports-specific risks across athletic disciplines like football, basketball, baseball, and gymnastics. The significance of early detection, intervention, and sport-specific conditioning is underscored to prevent the condition and manage it effectively. Moreover, the review highlights the positive prognosis for athletes, particularly adolescents, recovering from OCD, with a high rate of return to sport. Understanding the sports-specific risks, ensuring early intervention, and adopting a cautious, stepwise return to sport are critical for managing OCD effectively, thereby safeguarding the health and careers of athletes. Full article

Total Knee Arthroplasty (TKA) is a well-established surgical intervention for the management of end-stage knee osteoarthritis. While the procedure is generally successful, postoperative rehabilitation remains a key determinant of long-term functional outcomes. Traditional rehabilitation protocols, particularly those requiring in-person clinical visits, often encounter limitations in accessibility, patient adherence, and personalization. In response, emerging sensor technologies have introduced innovative solutions to support and enhance recovery following TKA. This review provides a thematically organized synthesis of the current landscape and future directions of sensor-assisted rehabilitation in TKA. It examines four main categories of technologies: wearable sensors (e.g., IMUs, accelerometers, gyroscopes), smart implants, pressure-sensing systems, and mobile health (mHealth) platforms such as ReHub^® and BPMpathway. Evidence from recent randomized controlled trials and systematic reviews demonstrates their effectiveness in tracking mobility, monitoring range of motion (ROM), detecting gait anomalies, and delivering real-time feedback to both patients and clinicians. Despite these advances, several challenges persist, including measurement accuracy in unsupervised environments, the complexity of clinical data integration, and digital literacy gaps among older adults. Nevertheless, the integration of artificial intelligence (AI), predictive analytics, and remote rehabilitation tools is driving a shift toward more adaptive and individualized care models. This paper concludes that sensor-enhanced rehabilitation is no longer a future aspiration but an active transition toward a smarter, more accessible, and patient-centered paradigm in recovery after TKA. Full article

Background/Objectives: Knee osteoarthritis (KOA) is a prevalent disorder affecting both older adults and younger individuals, leading to compromised joint function and mobility. Early and accurate detection is critical for effective intervention, as treatment options become increasingly limited as the disease progresses. Traditional diagnostic methods rely heavily on the expertise of physicians and are susceptible to errors. The demand for utilizing deep learning models in order to automate and improve the accuracy of KOA image classification has been increasing. In this research, a unique deep learning model is presented that employs autoencoders as the primary mechanism for feature extraction, providing a robust solution for KOA classification. Methods: The proposed model differentiates between KOA-positive and KOA-negative images and categorizes the disease into its primary severity levels. Levels of severity range from “healthy knees” (0) to “severe KOA” (4). Symptoms range from typical joint structures to significant joint damage, such as bone spur growth, joint space narrowing, and bone deformation. Two experiments were conducted using different datasets to validate the efficacy of the proposed model. Results: The first experiment used the autoencoder for feature extraction and classification, which reported an accuracy of 96.68%. Another experiment using autoencoders for feature extraction and Extreme Learning Machines for actual classification resulted in an even higher accuracy value of 98.6%. To test the generalizability of the Knee-DNS system, we utilized the Butterfly iQ+ IoT device for image acquisition and Google Colab’s cloud computing services for data processing. Conclusions: This work represents a pioneering application of autoencoder-based deep learning models in the domain of KOA classification, achieving remarkable accuracy and robustness. Full article

Background: Assessment of gait function is crucial for optimising rehabilitation outcomes. The gait analysis and motion score (GAMS) summarises qualitative and quantitative gait parameters from treadmill-based analyses to evaluate functional walking status. Objectives: To assess the sensitivity of the GAMS for detecting short-term changes, its test–retest reliability, and its correlation with the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) and the Timed Up and Go (TUG) test. Methods: A retrospective analysis of 94 inpatient rehabilitation patients with hip, knee, or ankle impairments was performed. Changes in GAMS, WOMAC, and TUG scores and their interrelationships were assessed at both admission and discharge. Results: GAMS, WOMAC, and TUG showed significant improvements over time, with medium effect sizes (η² = 0.303 to 0.434; p < 0.001). No significant differences in outcome measures were observed between groups. Moderate to strong correlations were found between pre- and post-rehabilitation scores for GAMS, TUG, and WOMAC (r = 0.58 to r = 0.90), indicating good test–retest reliability. A significant low negative correlation between GAMS and TUG was observed for all patients at admission (r = −0.30, p = 0.003) and discharge (r = −0.26, p = 0.030). No significant correlations were observed between GAMS and WOMAC in any patient group. Baseline GAMS scores significantly influenced change scores. Conclusions: GAMS is a sensitive and reliable tool for detecting short-term changes in gait parameters. GAMS and TUG assess related but distinct constructs, with GAMS and WOMAC assessing different domains of gait function. Therefore, GAMS provides complementary information not captured by WOMAC or TUG. Full article