Knee Flexion Contractures Are Associated with Worse Pain, Stiffness, and Function in Patients with Knee Osteoarthritis: Data from the Osteoarthritis Initiative

PM&R ◽  
2020 ◽  
Author(s):  
T Mark Campbell ◽  
Tim Ramsay ◽  
Guy Trudel
Keyword(s):  
Knee Osteoarthritis ◽  
Knee Flexion ◽  
Flexion Contractures ◽  
Osteoarthritis Initiative ◽  
And Function

scholarly journals The Inverse OARSI-OMERACT Criteria Is a Valid Indicator of the Clinical Worsening of Knee Osteoarthritis: Data from the Osteoarthritis Initiative

2020 ◽  
pp. jrheum.200145
Author(s):  
Jeffrey B. Driban ◽  
Matthew S. Harkey ◽  
Lori Lyn Price ◽  
Grace H. Lo ◽  
Timothy E. McAlindon
Keyword(s):  
Knee Osteoarthritis ◽  
Knee Pain ◽  
Knee Replacement ◽  
Walking Speed ◽  
Cox Model ◽  
Research Society ◽  
Osteoarthritis Initiative ◽  
Osteoarthritis Research Society ◽  
And Function ◽  
Relationship Of

Objective We assessed if the inverse Osteoarthritis Research Society International (OARSI) and Outcome Measures in Rheumatology (OMERACT) criteria relate to concurrent radiographic knee osteoarthritis (KOA) progression and decline in walking speed, as well as future knee replacement. Methods We conducted knee-based analyses of data from the Osteoarthritis Initiative. All knees had symptomatic OA: at least doubtful radiographic KOA (Kellgren-Lawrence grade ≥ 1) and knee pain ≥ 10/100 (Western Ontario and McMaster Universities Osteoarthritis Index pain) at the 12-month visit. The inverse of the OARSI-OMERACT responder criteria depended on knee pain and function, and global assessment of knee impact. We used generalized linear mixed models to assess the relationship of the inverse OARSI‑OMERACT criteria over 2 years (i.e., 12-month and 36-month visits) with worsening radiographic severity (any increase in Kellgren-Lawrence grade from 12 months to 36 months) and decline in self-selected 20-m walking speed of ≥ 0.1m/s (from 12 months to 36 months). We used a Cox model to assess time to knee replacement during the 6 years after the 36-month visit as an outcome. Results Among the 1746 analyzed, 19% met the inverse OARSI-OMERACT criteria. Meeting the inverse OARSI-OMERACT criteria was associated with almost double the odds of experiencing concurrent worsening in radiographic KOA severity (OR 1.89, 95% CI 1.32–2.70) or decline in walking speed (OR 1.82, 95% CI 1.37–2.40). A knee meeting the inverse OARSI-OMERACT criteria was more likely to receive a knee replacement after the 36-month visit (23%) compared with a nonresponder (10%; HR 2.54, 95% CI 1.89–3.41). Conclusion The inverse OARSI-OMERACT criteria for worsening among people with KOA had good construct validity in relation to clinically relevant outcomes.

scholarly journals Identification of Risk Factors and Machine Learning-Based Prediction Models for Knee Osteoarthritis Patients

2020 ◽  
Vol 10 (19) ◽  
pp. 6797
Author(s):  
Christos Kokkotis ◽  
Serafeim Moustakidis ◽  
Giannis Giakas ◽  
Dimitrios Tsaopoulos
Keyword(s):  
Machine Learning ◽  
Risk Factors ◽  
Knee Osteoarthritis ◽  
Prediction Models ◽  
Majority Vote ◽  
Vote Scheme ◽  
Multidisciplinary Data ◽  
Osteoarthritis Initiative ◽  
Reported Data ◽  
And Function

Knee Osteoarthritis (KOA) is a multifactorial disease that causes low quality of life, poor psychology and resignation from life. Furthermore, KOA is a big data problem in terms of data complexity, heterogeneity and size as it has been commonly considered in the literature with most of the reported studies being limited in the amount of information they can adequately process. The aim of this paper is: (i) To provide a robust feature selection (FS) approach that could identify important risk factors which contribute to the prediction of KOA and (ii) to develop machine learning (ML) prediction models for KOA. The current study considers multidisciplinary data from the osteoarthritis initiative (OAI) database, the available features of which come from heterogeneous sources such as questionnaire data, physical activity indexes, self-reported data about joint symptoms, disability and function as well as general health and physical exams’ data. The novelty of the proposed FS methodology lies on the combination of different well-known approaches including filter, wrapper and embedded techniques, whereas feature ranking is decided on the basis of a majority vote scheme to avoid bias. The validation of the selected factors was performed in data subgroups employing seven well-known classifiers in five different approaches. A 74.07% classification accuracy was achieved by SVM on the group of the first fifty-five selected risk factors. The effectiveness of the proposed approach was evaluated in a comparative analysis with respect to classification errors and confusion matrices to confirm its clinical relevance. The results are the basis for the development of reliable tools for the prediction of KOA progression.

scholarly journals AB0602 IMPACT OF SOCIOECONOMIC FACTORS ON PAIN AND FUNCTION IN KNEE OSTEOARTHRITIS: A SYSTEMATIC LITERATURE REVIEW

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 1337.2-1337
Author(s):  
T. W. Swinnen ◽  
M. Willems ◽  
I. Jonkers ◽  
F. P. Luyten ◽  
J. Vanrenterghem ◽  
...  
Keyword(s):  
Risk Factors ◽  
Literature Review ◽  
Knee Osteoarthritis ◽  
Socioeconomic Factors ◽  
Systematic Literature Review ◽  
Intervention Effects ◽  
Socioeconomic Outcomes ◽  
And Function ◽  
The Impact

Background:The personal and societal burden of knee osteoarthritis (KOA) urges the research community to identify factors that predict its onset and progression. A mechanistic understanding of disease is currently lacking but needed to develop targeted interventions. Traditionally, risk factors for KOA are termed ‘local’ to the joint or ‘systemic’ referring to whole-body systems. There are however clear indications in the scientific literature that contextual factors such as socioeconomic position merit further scientific scrutiny, in order to justify a more biopsychosocial view on risk factors in KOA.Objectives:The aims of this systematic literature review were to assess the inclusion of socioeconomic factors in KOA research and to identify the impact of socioeconomic factors on pain and function in KOA.Methods:Major bibliographic databases, namely Medline, Embase, CINAHL, Web of Science and Cochrane, were independently screened by two reviewers (plus one to resolve conflicts) to identify research articles dealing with socioeconomic factors in the KOA population without arthroplasty. Included studies had to quantify the relationship between socioeconomic factors and pain or function. Main exclusion criteria were: a qualitative design, subject age below 16 years and articles not written in English or Dutch. Methodological quality was assessed via the Cochrane risk of bias tools for randomized (ROB-II) and non-randomized intervention studies (ROBIN-I) and the Newcastle-Ottawa Scale for assessing the quality of non-randomised studies. Due to heterogeneity of studies with respect to outcomes assessed and analyses performed, no meta-analysis was performed.Results:Following de-duplication, 7639 articles were available for screening (120 conflicts resolved without a third reader). In 4112 articles, the KOA population was confirmed. 1906 (25%) were excluded because of knee arthroplasty and 1621 (21%) because of other issues related to the population definition. Socioeconomic factors could not be identified in 4058 (53%) papers and were adjusted for in 211 (3%) articles. In the remaining papers covering pain (n=110) and/or function (n=81), education (62%) and race (37%) were most frequently assessed as socioeconomic factors. A huge variety of mainly dichotomous or ordinal socioeconomic outcomes was found without further methodological justification nor sensitivity analysis to unravel the impact of selected categories. Although the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) was the most popular instrument to assess pain and function, data pooling was not possible as socioeconomic factors estimates were part of multilevel models in most studies. Overall results showed that lower education and African American race were consistent predictors of pain and poor function, but those effects diminished or disappeared when psychological aspects (e.g. discrimination) or poverty estimates were taken into account. When function was assessed using self-reported outcomes, the impact of socioeconomic factors was more clear versus performance-based instruments. Quality of research was low to moderate and the moderating or mediating impact of socioeconomic factors on intervention effects in KOA is understudied.Conclusion:Research on contextual socioeconomic factors in KOA is insufficiently addressed and their assessment is highly variable methodologically. Following this systematic literature review, we can highlight the importance of implementing a standardised and feasible set of socioeconomic outcomes in KOA trials1, as well as the importance of public availability of research databases including these factors. Future research should prioritise the underlying mechanisms in the effect of especially education and race on pain and function and assess its impact on intervention effects to fuel novel (non-)pharmacological approaches in KOA.References:[1]Smith TO et al. The OMERACT-OARSI Core Domain Set for Measurement in Clinical Trials of Hip and/or Knee Osteoarthritis J Rheumatol 2019. 46:981–9.Disclosure of Interests:None declared.

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