scholarly journals Effects of resistance training on gait velocity and knee adduction moment in knee osteoarthritis patients: a systematic review and meta-analysis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Shuoqi Li ◽  
Wei Hui Ng ◽  
Sumayeh Abujaber ◽  
Shazlin Shaharudin
Keyword(s):  
Systematic Review ◽  
Resistance Training ◽  
Knee Osteoarthritis ◽  
Meta Analysis ◽  
Knee Adduction Moment ◽  
Gait Velocity ◽  
Knee Oa ◽  
Registration Number ◽  
Potential Benefits ◽  
Mean Differences

AbstractThe systematic review aimed to analyze the effects of resistance training in knee osteoarthritis (OA) rehabilitation from a biomechanical perspective. A meta-analysis was performed to determine the potential benefits of resistance training on patients with knee OA. Relevant studies based on the inclusion and exclusion criteria were selected from CENTRAL, PubMed, Scopus, and Web of Science databases inception to August 2020. Outcome measures included gait velocity and knee adduction moment (KAM). The mean differences of the data with a 95% confidence interval were analyzed using STATA 15.1 software The search identified eight studies that satisfied all the inclusion criteria, in which 164 patients were involved in gait velocity studies and another 122 patients were part of KAM studies. Analysis of the pooled data showed that resistance training significantly improved the gait velocity in patients with knee OA (p < 0.01, z = 2.73), ES (95% CI) = 0.03 (0.01, 0.06) m/s. However, resistance training had no significant effect on improving KAM in patients with knee OA (p = 0.98, z = 0.03), ES (95% CI) = 0.00 (− 0.16, 0.16) percentage of body weight × height (%BW × Ht). Therefore, resistance training may enhance gait velocity but not KAM in knee OA patients. The protocol was registered at PROSPERO (registration number: CRD42020204897).

scholarly journals Effects of mechanical interventions in the management of knee osteoarthritis: protocol for an OA Trial Bank systematic review and individual participant data meta-analysis

BMJ Open ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. e043026
Author(s):  
Erin M Macri ◽  
Michael Callaghan ◽  
Marienke van Middelkoop ◽  
Miriam Hattle ◽  
Sita M A Bierma-Zeinstra
Keyword(s):  
Systematic Review ◽  
Knee Osteoarthritis ◽  
Broad Class ◽  
Meta Analysis ◽  
Individual Participant Data ◽  
Knee Oa ◽  
International Regulations ◽  
Individual Participant ◽  
Registration Number ◽  
Mechanical Intervention

IntroductionKnee osteoarthritis (OA) is a prevalent and disabling musculoskeletal condition. Biomechanical factors may play a key role in the aetiology of knee OA, therefore, a broad class of interventions involves the application or wear of devices designed to mechanically support knees with OA. These include gait aids, bracing, taping, orthotics and footwear. The literature regarding efficacy of mechanical interventions has been conflicting or inconclusive, and this may be because certain subgroups with knee OA respond better to mechanical interventions. Our primary aim is to identify subgroups with knee OA who respond favourably to mechanical interventions.Methods and analysisWe will conduct a systematic review to identify randomised clinical trials of any mechanical intervention for the treatment of knee OA. We will invite lead authors of eligible studies to share individual participant data (IPD). We will perform an IPD meta-analysis for each type of mechanical intervention to evaluate efficacy, with our main outcome being pain. Where IPD are not available, this will be achieved using aggregate data. We will then evaluate five potential treatment effect modifiers using a two-stage approach. If data permit, we will also evaluate whether biomechanics mediate the effects of mechanical interventions on pain in knee OA.Ethics and disseminationNo new data will be collected in this study. We will adhere to institutional, national and international regulations regarding the secure and confidential sharing of IPD, addressing ethics as indicated. We will disseminate findings via international conferences, open-source publication in peer-reviewed journals and summaries posted on websites serving the public and clinicians.PROSPERO registration numberCRD42020155466.

Astrocyte Biomarkers in Alzheimer Disease: A Systematic Review and Meta-analysis

Neurology ◽  
2021 ◽  
pp. 10.1212/WNL.0000000000012109
Author(s):  
Bruna Bellaver ◽  
João Pedro Ferrari-Souza ◽  
Lucas Uglione da Ros ◽  
Stephen F Carter ◽  
Elena Rodriguez-Vieitez ◽  
...  
Keyword(s):  
Systematic Review ◽  
Web Of Science ◽  
Meta Analysis ◽  
Effect Sizes ◽  
Significant Progress ◽  
Exclusion Criteria ◽  
Mao B ◽  
Positron Emission ◽  
Registration Number ◽  
Mean Differences

Objective:To perform a systematic review and meta-analysis to determine whether fluid and imaging astrocyte biomarkers are altered in Alzheimer's disease (AD).Methods:PubMed and Web of Science databases were searched for articles reporting fluid or imaging astrocyte biomarkers in AD. Pooled effect sizes were determined with mean differences (SMD) using the Hedge’s G method with random-effects to determine biomarker performance. Adapted questions from QUADAS-2 were applied for quality assessment. A protocol for this study has been previously registered in PROSPERO (registration number: CRD42020192304).Results:The initial search identified 1,425 articles. After exclusion criteria were applied, 33 articles (a total of 3,204 individuals) measuring levels of GFAP, S100B, YKL-40 and AQP4 in the blood and cerebrospinal fluid (CSF), as well as MAO-B, indexed by positron emission tomography 11C-deuterium-L-deprenyl ([11C]-DED), were included. GFAP (SMD = 0.94; 95% CI = 0.71-1.18) and YKL-40 (SMD = 0.76; CI 95% = 0.63-0.89) levels in the CSF, S100B levels in the blood (SMD = 2.91; CI 95% = 1.01-4.8) were found significantly increased in AD patients.Conclusions:Despite significant progress, applications of astrocyte biomarkers in AD remain in their early days. The meta-analysis demonstrated that astrocyte biomarkers are consistently altered in AD and supports further investigation for their inclusion in the AD clinical research framework for observational and interventional studies.

scholarly journals Hypertonic dextrose injections (prolotherapy) in the treatment of symptomatic knee osteoarthritis: A systematic review and meta-analysis

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Regina WS Sit ◽  
Vincent CH Chung ◽  
Kenneth D. Reeves ◽  
David Rabago ◽  
Keith KW Chan ◽  
...  
Keyword(s):  
Systematic Review ◽  
Knee Osteoarthritis ◽  
Primary Outcome ◽  
Meta Analysis ◽  
Knee Oa ◽  
Composite Scale ◽  
Symptomatic Knee Osteoarthritis ◽  
Symptomatic Knee ◽  
Pain Subscale ◽  
Hypertonic Dextrose

Abstract Hypertonic dextrose injections (prolotherapy) is an emerging treatment for symptomatic knee osteoarthritis (OA) but its efficacy is uncertain. We conducted a systematic review with meta-analysis to synthesize clinical evidence on the effect of prolotherapy for knee OA. Fifteen electronic databases were searched from their inception to September 2015. The primary outcome of interest was score change on the Western Ontario and McMaster Universities Arthritis Index (WOMAC). Three randomized controlled trials (RCTs) of moderate risk of bias and one quasi–randomized trial were included, with data from a total of 258 patients. In the meta-analysis of two eligible studies, prolotherapy is superior to exercise alone by a standardized mean difference (SMD) of 0.81 (95% CI: 0.18 to 1.45, p = 0.012), 0.78 (95% CI: 0.25 to 1.30, p = 0.001) and 0.62 (95% CI: 0.04 to 1.20, p = 0.035) on the WOMAC composite scale; and WOMAC function and pain subscale scores respectively. Moderate heterogeneity exists in all cases. Overall, prolotherapy conferred a positive and significant beneficial effect in the treatment of knee OA. Adequately powered, longer-term trials with uniform end points are needed to better elucidate the efficacy of prolotherapy.

scholarly journals Hallux valgus orthosis characteristics and effectiveness: a systematic review with meta-analysis

BMJ Open ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. e047273
Author(s):  
Mei-Ying Kwan ◽  
Kit-Lun Yick ◽  
Joanne Yip ◽  
Chi-Yung Tse
Keyword(s):  
Systematic Review ◽  
Hallux Valgus ◽  
Outcome Measurement ◽  
Meta Analysis ◽  
Outcome Data ◽  
Risk Of Bias ◽  
Eligibility Criteria ◽  
Systematic Analysis ◽  
Registration Number ◽  
Mean Differences

ObjectiveThe treatment effect of orthoses for hallux valgus (HV) is unclear with little interventional studies, the design involves multiple complex factors, and therefore a systematic analysis with meta-analysis is necessary. The objective of this systematic review and meta-analysis is to determine whether current foot orthoses are effective in treating HV.DesignSystematic review with meta-analysis.Data sourcesElectronic databases (PubMed, Scopus, Cinahl and Medline) are searched up to February 2020.Eligibility criteria for selecting studiesInterventional studies with content focus on HV orthosis design and any of the outcomes related to effectiveness for treating HV are included. The standardised mean differences are calculated. The risk of bias in included studies is assessed using the Cochrane Collaboration’s risk of bias tools.ResultsIn total, 2066 articles are identified. Among them, nine are selected and quality rated, and data are extracted and closely examined. A meta-analysis is conducted, where appropriate. The main causes of potential bias are missing outcome data and outcome measurement error. The results show that orthosis with a toe separator has the best effect of correcting the HV angle (standardised mean difference: 0.50, 95% CI: 0.189 to 0.803).ConclusionThe orthoses design with a toe separator or an element that allows for the foot anatomic alignment is critical for reducing the HV angle and relieving foot pain. The results contribute to a better selection of treatment for patients.PROSPERO registration numberCRD42021260403.

Safety of Intra-Articular Hyaluronic Acid for Knee Osteoarthritis: Systematic Review and Meta-Analysis of Randomized Trials Involving More than 8,000 Patients

Cartilage ◽  
2019 ◽  
pp. 194760351988878
Author(s):  
Larry E. Miller ◽  
Samir Bhattacharyya ◽  
William R. Parrish ◽  
Michael Fredericson ◽  
Brad Bisson ◽  
...  
Keyword(s):  
Systematic Review ◽  
Hyaluronic Acid ◽  
Adverse Events ◽  
Knee Osteoarthritis ◽  
Randomized Controlled Trials ◽  
Meta Analysis ◽  
Controlled Trials ◽  
Knee Oa ◽  
Randomized Controlled ◽  
Symptomatic Knee

Objective The objective of this systematic review and meta-analysis was to report the safety of intra-articular hyaluronic acid (IAHA) in patients with symptomatic knee osteoarthritis (OA). Methods We identified randomized controlled trials reporting the safety of IAHA versus IA saline in adults with symptomatic knee OA. Main safety outcomes were adverse events (AEs), local AEs, serious adverse events (SAEs), study withdrawals, and AE-related study withdrawals. Results A total of 35 randomized controlled trials with 38 group comparisons comprising 8,078 unique patients (IAHA: 4,295, IA saline: 3,783) were included in the meta-analysis. Comparing IAHA with IA saline over a median of 6 months follow-up, there were no differences in the risk of AEs (42.4% vs. 39.7%, risk ratio [RR] = 1.01, 95% CI = 0.96-1.07, P = 0.61), SAEs (1.8% vs. 1.2%, RR = 1.44, 95% CI = 0.91-2.26, P=0.12), study withdrawals (12.3% vs. 12.7%, RR = 0.99, 95% CI = 0.87-1.12, P = 0.83), or AE-related study withdrawals (2.7% vs. 2.1%, RR = 1.37, 95% CI = 0.97-1.93, P = 0.08). Local AEs, all of which were nonserious, were more common with IAHA vs. IA saline (14.5% vs. 11.7%, RR = 1.21, 95% CI = 1.07-1.36, P = 0.003) and typically resolved within days. Conclusion IAHA was shown to be safe for use in patients with symptomatic knee OA. Compared with IA saline, IAHA is associated with an increased risk of nonserious, transient local reactions. There was no evidence to suggest any additional safety risks of IAHA.

scholarly journals High molecular weight Intraarticular hyaluronic acid for the treatment of knee osteoarthritis: a network meta-analysis

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Charles D. Hummer ◽  
Felix Angst ◽  
Wilson Ngai ◽  
Craig Whittington ◽  
Sophie S. Yoon ◽  
...  
Keyword(s):  
Molecular Weight ◽  
Hyaluronic Acid ◽  
Knee Osteoarthritis ◽  
Treated Patient ◽  
Meta Analysis ◽  
Credible Interval ◽  
Pain Scale ◽  
Womac Pain ◽  
Knee Oa ◽  
Mean Differences

Abstract Background The 2013 American Academy of Orthopaedic Surgeons (AAOS) guidelines made strong recommendations against intraarticular hyaluronic acid (IAHA) for patients with knee osteoarthritis (OA), as evidence supporting improvements in pain did not meet the minimal clinically important improvement (MCII) threshold. However, there may be important distinctions based on IAHA molecular weight (MW). Hence our objective was to evaluate the efficacy of IAHAs in knee OA based on molecular weight. Methods Randomized controlled trials were searched within MEDLINE, Embase, and CENTRAL and selected based on AAOS criteria. A pain measure hierarchy and longest follow-up were used to select one effect size from each trial. Mean differences between interventions were converted to standardized mean differences (SMDs) and incorporated into a random-effects Bayesian network meta-analysis. High MW (HMW) was defined as ≥6000 kDa, and low MW (LMW) as < 750 kDa. Results HMW IAHA was associated with a statistically significant and possibly clinically significant improvement in pain (SMD − 0.57 (95% credible interval [Crl]: − 1.04, − 0.11), exceeding the − 0.50 MCII threshold. LMW IAHA had a lesser, non-significant improvement (− 0.23, 95% Crl: − 0.67, 0.20). Back-transforming SMDs to the WOMAC pain scale indicated a 14.65 (95% CI: 13.93, 15.62) point improvement over IA placebo, substantially better than the 8.3 AAOS MCII threshold. Conclusions Unlike LMW IAHA, HMW IAHA exceeded the MCII threshold for pain relief, suggesting that improvements can be subjectively perceived by the treated patient. Amalgamation of LMW and HMW may have blurred the benefits of IAHA in the past, leading to negative recommendations. Differentiation according to MW offers refined insight for treatment with IAHA.

scholarly journals Comparison of Efficacy among Three Radiofrequency Ablation Techniques for Treating Knee Osteoarthritis: A Systematic Review and Meta-Analysis

2021 ◽  
Vol 18 (14) ◽  
pp. 7424
Author(s):  
Shih-Hsiang Chou ◽  
Po-Chih Shen ◽  
Cheng-Chang Lu ◽  
Zi-Miao Liu ◽  
Yin-Chun Tien ◽  
...  
Keyword(s):  
Systematic Review ◽  
Radiofrequency Ablation ◽  
Knee Osteoarthritis ◽  
Baseline Level ◽  
Meta Analysis ◽  
Cochrane Library ◽  
Invasive Treatment ◽  
Knee Oa ◽  
Before And After

Radiofrequency ablation (RFA) was first introduced for treating knee osteoarthritis (OA) in 2010 and has emerged as a minimally invasive treatment option. Three RFA techniques have been adopted for treating knee OA, including conventional, pulsed, and cooled RFA. However, the efficacy among different RFA techniques in the treatment of knee OA is still unclear. Three electronic databases were systematically searched for relevant articles, including PubMed, Embase, and Cochrane Library. A meta-analysis of articles that investigated the use of RFA techniques in the treatment of knee OA was conducted to pool the effect size in pain before and after treatment. A total of 20 eligible articles (including 605 patients) were included for our meta-analysis. After treatment, the patients had significant improvements in pain for all three RFA techniques when compared with the baseline level for the 1, 3-, and 6-month follow-ups (p < 0.00001). However, there were no significant differences in the efficacy among the three RFA techniques for all follow-up visits (p > 0.05). The three RFA techniques demonstrated a significant improvement in pain for up to 6 months after treatment. Comparing the efficacy of the three RFA techniques in the treatment of knee OA, our results showed that no significant differences in pain relief among the three RFA techniques were observed at the 1-, 3-, 6, and 12-month follow-up visits.

scholarly journals Efficacy and safety of turmeric extracts in knee osteoarthritis: protocol for a systematic review and meta-analysis of randomised controlled trials

2020 ◽  
Author(s):  
Zhiqiang Wang ◽  
Ambrish Singh ◽  
Benny Antony
Keyword(s):  
Systematic Review ◽  
Knee Osteoarthritis ◽  
Methodological Quality ◽  
Randomised Controlled Trials ◽  
Meta Analysis ◽  
Risk Of Bias ◽  
Efficacy And Safety ◽  
Knee Oa ◽  
Randomised Controlled

AbstractTurmeric extracts have been used as a remedy for treating arthritis in traditional medicine. Recent years have witnessed the rise of different extracts from turmeric and randomised clinical trials (RCTs) evaluating the efficacy and safety of these extracts for the treatment of knee osteoarthritis (OA). This planned systematic review and meta-analysis aims to assess the efficacy and safety of turmeric extracts for the treatment of knee OA. Biomedical databases such as PubMed, Scopus, and Embase will be searched for RCTs reporting safety and efficacy of turmeric extracts for the treatment of knee OA. Cochrane risk of bias tool will be used to assess the methodological quality of the included studies, and a meta-analysis will be performed to pool the effect estimates.

scholarly journals Supervised Machine Learning for Aiding Diagnosis of Knee Osteoarthritis: A Systematic Review and Meta-Analysis

2020 ◽  
Author(s):  
Luca Parisi ◽  
Narrendar RaviChandran ◽  
Matteo Lanzillotta
Keyword(s):  
Machine Learning ◽  
Systematic Review ◽  
Knee Osteoarthritis ◽  
Gait Analysis ◽  
Meta Analysis ◽  
Supervised Machine Learning ◽  
Gait Patterns ◽  
Kinematic Data ◽  
Knee Oa ◽  
Symptomatic Knee

<p><b>Background</b></p> <p>Knee osteoarthritis (OA) remains a leading aetiology of disability worldwide. Clinical assessment of such knee-related conditions has improved with recent advances in gait analysis. Despite being a gold standard method, gait data acquired by motion capture (mocap) technology are highly non-linear and dimensional, which make traditional gait analysis challenging. Thus, extrinsic algorithms need to be used to make sense of gait data. Supervised Machine Learning (ML)-based classifiers outperform conventional statistical methods in revealing intrinsic patterns that can discern gait abnormalities when using mocap data, making them a suitable tool for aiding diagnosis of knee OA.</p> <p><b>Research question</b></p> <p>Studies have demonstrated the accuracy of supervised ML-based classifiers in gait analysis. However, these techniques have not gained wide acceptance amongst biomechanists for two reasons: the reliability of such methods has not been assessed and there is no consensus on which classifier or group of classifiers to select. Specifically, it is not clear whether classifiers that leverage optimal separating hyperplanes (OSH) or artificial neural networks (ANN) are more accurate and reliable.</p> <p><b>Methods</b></p> <p>A systematic review and meta-analysis were conducted to assess the capability of such algorithms to predict pathological kinematic and kinetic gait patterns as indicators of knee OA. With 153 eligible studies, 6 studies met the inclusion criteria for a subsequent meta-analysis, accounting for <a>273 healthy subjects and 313 patients </a>with symptomatic knee OA. The classification performance of supervised ML classifiers (OSH- or ANN-based) used in these studies was quantitatively assessed and compared across four following performance metrics: classification accuracy on the test set (ACC), sensitivity (SN), specificity (SP), and area under the receiver operating characteristic curve (AUC). </p> <p><b>Results</b></p> <p>There was no statistically significant discrepancy in the ACC between OSH- and ANN-based classifiers when dealing with kinetic and kinematic data concurrently, as well as when considering only kinematic data. However, there was a statistically significant difference in their SN and SP, with the ANN-based classifiers having higher SN and SP than OSH-based algorithms. As only one of the eligible studies reported AUC, this metric could not be assessed statistically across studies.</p> <p><b>Significance</b></p> <p>This study supports the use of ANN-based algorithms for classifying knee OA-related gait patterns as having a higher sensitivity and specificity than OSH-based classifiers. Considering their higher reliability, leveraging supervised ANN-based methods can aid biomechanists to diagnose knee OA objectively.</p>

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