Category Ranking
98%
Total Visits
921
Avg Visit Duration
2 minutes
Citations
20
Article Abstract
Background: Total knee arthroplasty (TKA) is an important management strategy for patients with knee osteoarthritis (OA) refractory to conservative management. Postoperative range of motion (ROM) exercise is important to recover patients' activities of daily living. Continuous passive motion (CPM) is a machine that provides passive ROM exercises of the knee joint in a pre-defined arc of motion. The short- and long-term effects of CPM exercise are controversial. We hypothesized that the inconsistent results of the CPM exercise are due to poor fitting of CPM machines and measurement errors. This study aims to present a protocol for investigating a new type of CPM machine that could be applied in a sitting position in comparison with the conventional type of CPM machine for patients with unilateral TKAs.
Methods: This study presents the protocol of a prospective, multicenter, single-blinded, three-armed randomized controlled trial (RCT). One hundred and twenty-six patients receiving unilateral TKAs will be recruited at the physical medicine and rehabilitation clinics of two urban tertiary medical hospitals. The patients were randomly divided into three groups with a 1:1:1 allocation. The intervention group will receive two weeks of post-operative rehabilitation using a new type of CPM machine. The control group will receive 2 weeks of post-operative rehabilitation using conventional CPM machines. The third group will receive post-operative rehabilitation with both types of CPM machines. The primary outcome will be the change in the passive ROM of the affected knee joint from baseline to 2 weeks after baseline assessment. The secondary outcomes will be pain and functional measurements, and will include patient-reported outcomes and performance tests surveyed at multiple time points up to 3 months after TKA.
Discussion: This is the first RCT to investigate the effect of a new type of CPM machine. The results of this RCT will determine whether the position of the patients during CPM exercise is important in post-operative rehabilitation protocols after TKAs and will provide evidence for the development of proper rehabilitation guidelines after TKAs.
Trial Registration: Clinical Research Information Service of Republic of Korea, KCT0005520, Registered on 21 October 2020, https://cris.nih.go.kr/cris/search/detailSearch.do/21750.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9188049 | PMC |
| http://dx.doi.org/10.1186/s12891-022-05507-2 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
A novel approach of [F]FDG PET-based individual metabolic radiomics network to predict cognitive impairment in multiple system atrophy.
Neuroimage
August 2025
College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, 310014, China; Department of Nuclear Medicine and Medical PET Center, The Second Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310009, China; Institute of Nuclear Medicine and M
Purpose: Many efforts have been tried to evaluate multiple system atrophy (MSA)-related cognitive impairment, however, there is still lacking of effective approach. In this study, for the first time, we developed the individual metabolic radiomics networks (IMRN) using [F]FDG PET imaging to investigate brain metabolic connectivity patterns of MSA and validated the usefulness of IMRN-based predictive model for MSA-related cognitive impairment.
Methods: In this retrospective study, we recruited 115 MSA patients with [F]FDG PET/CT scans.
Functional brain networks predicting different symptoms of schizophrenia based on connectome-based predictive modeling: A multi-site fMRI study.
Asian J Psychiatr
August 2025
Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China. Electronic address:
Previous findings on brain functional alterations across different symptoms of schizophrenia (SCZ) patients had yielded inconsistent results. Small sample sizes could contribute to this inconsistency. To overcome this limitation, we conducted a multi-site study to explore the neural mechanisms underlying different symptoms in SCZ.
View Article and Find Full Text PDFEvaluating the Progression of Retinal Sensitivity Loss in Geographic Atrophy Using Machine-Learning-Based Structure-Function Correlation (OMEGA 2).
Invest Ophthalmol Vis Sci
August 2025
Institute of Molecular and Clinical Ophthalmology Basel (IOB), Basel, Switzerland.
Purpose: The purpose of this study was to evaluate the effectiveness of different machine-learning models in predicting retinal sensitivity in geographic atrophy (GA) secondary to age-related macular degeneration (AMD) and compare the progression of sensitivity loss using observed versus inferred data over time.
Methods: Thirty patients with GA (37 eyes) were recruited for the OMEGA study. Participants underwent fundus-controlled perimetry (microperimetry) and spectral-domain optical coherence tomography (SD-OCT) imaging at baseline and follow-up visits at weeks 12, 24, and 48.
Non-invasive breath testing to detect colorectal cancer: protocol for a multicentre, case-control development and validation study (COBRA2 study).
BMC Cancer
July 2025
Department of Surgery and Cancer, Hammersmith Hospital Campus, Imperial College London, Du Cane Road, London, W12 0NN, UK.
Background: Colorectal cancer (CRC) is the fourth most common cancer in the United Kingdom. The five-year survival rate from CRC is only 10% when discovered at a late stage, but can exceed 90% if diagnosed early. Symptoms related to CRC can be non-specific, and therefore the decision to refer for a colonoscopy can be challenging.
View Article and Find Full Text PDFCognitive link adaptation via modulation scheme classification in narrowband networks under AWGN and SUI channel conditions.
Sci Rep
July 2025
College of Electrical and Mechanical Engineering, National University of Sciences and Technology, Islamabad, Pakistan.
The demand for faster data transfer rates rises along with the number of mobile devices, such as smartphones and IoT gadgets, which makes the radio spectrum more crowded. The forthcoming 5G wireless communication technology seeks to significantly enhance data speeds and spectrum efficiency by dynamically adjusting to fluctuating channel conditions. This research presents a new approach in the form of a hierarchical machine learning system for automation of modulation classification and adaptive parameter selection that optimizes spectral efficiency for different communication channels.
View Article and Find Full Text PDF