The relationship of radiographic findings with pain, function, and quality of life in patients with knee osteoarthritis

Özden, Fatih; Karaman, Özgür; Tuğay, Nazan; Kılınç, Cem Yalın; Kılınç, Rabia Mihriban; Tuğay, Baki Umut

doi:10.1016/j.jcot.2020.04.006

Cited by 18 publications

(16 citation statements)

References 37 publications

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“…Finally, systems such as the KL grade fail to capture the range of reported pain and function at various levels of knee joint degeneration [17][18][19][20] . Figure 2 demonstrates this in a violin plot of patient pain compared with KL grade.…”

Section: Model Evaluationmentioning

confidence: 99%

“…Clinicians may not be as good at this as we think, even when it comes to the first step of determining the degree to which pain originates from structural factors within the knee 15 . Clinicians rely on the Kellgren-Lawrence (KL) grade to gauge the structural severity of osteoarthritis by radiographs 16 , yet the KL grade does not explain pain very well [17][18][19][20] . It is not uncommon for clinicians to see patients with severe degenerative changes on radiographs (high KL grades) and relatively little pain, as well as those with relatively mild degenerative changes on radiographs (low KL grades) and severe pain.…”

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confidence: 99%

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An Algorithmic Approach to Understanding Osteoarthritic Knee Pain

Hill,

Byrum,

Zou

et al. 2023

JBJS Open Access

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Background: Osteoarthritic knee pain is a complex phenomenon, and multiple factors, both within the knee and external to it, can contribute to how the patient perceives pain. We sought to determine how well a deep neural network could predict osteoarthritic knee pain and other symptoms solely from a single radiograph view. Methods: We used data from the Osteoarthritis Initiative, a 10-year observational study of patients with knee osteoarthritis. We paired >50,000 weight-bearing, posteroanterior knee radiographs with corresponding Knee Injury and Osteoarthritis Outcome Score (KOOS) pain, symptoms, and activities of daily living subscores and used them to train a series of deep learning models to predict those scores solely from raw radiographic input. We created regression models for specific score predictions and classification models to predict whether the modeled KOOS subscore exceeded a range of thresholds. Results: The root-mean-square errors were 15.7 for KOOS pain, 13.1 for KOOS symptoms, and 14.2 for KOOS activities of daily living. Modeling was performed to predict whether pain was above or below given pain thresholds, and was able to predict extreme pain (KOOS pain < 40) with an area under the curve (AUC) of 0.78. Notably, the system was also able to correctly predict numerous cases where the Kellgren-Lawrence (KL) grade assigned by the radiologist was 0 but patient pain was high, and cases where the KL grade was 4 but patient pain was low. Conclusions: A deep neural network can be trained to predict the osteoarthritic knee pain that a patient experienced and other symptoms with reasonable accuracy from a single posteroanterior view of the knee, even using low-resolution images. The system can predict pain and dysfunction that the traditional KL grade does not capture. Deep learning applied to raw imaging inputs holds promise for disentangling sources of pain within the knee from aggravating factors external to the knee. Level of Evidence: Diagnostic Level III. See Instructions for Authors for a complete description of levels of evidence.

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Section: Model Evaluationmentioning

confidence: 99%

mentioning

confidence: 99%

An Algorithmic Approach to Understanding Osteoarthritic Knee Pain

Hill,

Byrum,

Zou

et al. 2023

JBJS Open Access

View full text Add to dashboard Cite

show abstract

“…In our study, clinical symptom severity at baseline was included as a covariate in the nonlinear mixed-effects models, which was not investigated in the study by Kim et al[ 27 ] According to previous cross-sectional studies, KL grades were not significantly correlated with symptoms of pain and physical function at baseline in patients with knee osteoarthritis, indicating absence of collinearity between radiographic and clinical factors [ 41 , 42 ]. The tests for collinearity in our study also showed similar results.…”

Section: Discussionmentioning

confidence: 99%

Using multivariate nonlinear mixed-effects model to investigate factors influencing symptom improvement after high tibial osteotomy in combination with bone marrow concentrate injection for medial compartment knee osteoarthritis: a prospective, open-label study

Cheng

Liang

Chu³

et al. 2023

BMC Musculoskelet Disord

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Purpose To investigate the effects of various demographic, structural, radiographic, and clinical factors on the prognosis of patients with medial compartmental knee osteoarthritis with varus deformity undergoing medial opening wedge high tibial osteotomy (HTO) in combination with bone marrow concentrate (BMC) injection. Methods In this prospective study, 20 patients underwent medial opening wedge HTO in combination with BMC injection with 12 months of follow-up. The structural and radiographic outcomes were evaluated by femorotibial angle and posterior tibial slope angle. The clinical outcomes were evaluated by visual analogue scale (VAS), Western Ontario and McMaster Universities Arthritis Index (WOMAC), and The Knee injury and Osteoarthritis Outcome Score (KOOS). Multivariate nonlinear mixed-effects models with asymptotic regressions were used to model the trajectory of symptom improvement. Results Medial opening wedge HTO in combination with BMC corrected the malalignment of the knee and led to significant symptom relief. The improvement of clinical symptoms reached a plateau 6 months after the surgery. Greater symptom severity at baseline and lower Kellgren-Lawrance (KL) grades were correlated with better post-operative clinical outcomes. Body-Mass-Index (BMI), femorotibial angle, age, and sex may also play a role in influencing the extent of symptom relief. Conclusion Symptom severity at baseline is important for prognosis prediction. In clinical practice, we suggest that the evaluation of clinical features and functional status of the patients be more emphasised.

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“…Discordance between physical functional performance and self-reported activity limitation is considered a rationale to use both self-reported outcome measures and performance tests as complimentary assessments [40][41][42]. Moreover, discordance raises another issue for selecting measures to assess the convergent validity of these physical performance tests.…”

Section: Discussionmentioning

confidence: 99%

Validity of the Osteoarthritis Research Society International (OARSI) recommended performance-based tests of physical function in individuals with symptomatic Kellgren and Lawrence grade 0–2 knee osteoarthritis

Lee

Kao

Liang

et al. 2022

BMC Musculoskelet Disord

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Background Performance-based physical tests have been widely used as objective assessments for individuals with knee osteoarthritis (KOA), and the core set of tests recommended by the Osteoarthritis Research Society International (OARSI) aims to provide reliable, valid, feasible and standardized measures for clinical application. However, few studies have documented their validity in roentgenographically mild KOA. Our goal was to test the validity of five performance-based tests in symptomatic KOA patients with X-ray findings of Kellgren and Lawrence (K-L) grade 0–2. Methods We recruited a convenience sample of thirty KOA patients from outpatient clinics and 30 age- and sex-matched asymptomatic controls from the community. They performed five OARSI-recommended physical tests and the KOA group answered the Western Ontario and McMaster Universities (WOMAC) Osteoarthritis Index. The tests included the 9-step stair-climbing test (9 s-SCT), timed up and go (TUG) test, 30-second chair-stand test (30sCST), 40-m fast walking-test (40MFPW) and 6-minute walking test (6MWT). The discriminant validity of these physical tests were assessed by comparisons between the KOA and control groups, receiver operating curve and multivariate logistic regression analysis. The convergent/divergent validity was assessed by correlation between the physical tests results and the three subscale scores of the WOMAC in the KOA group. Results The KOA group had significantly worse performance than the control group. The percentage of difference was the largest in the 9 s-SCT (57.2%) and TUG tests (38.4%). Meanwhile, Cohen’s d was above 1.2 for the TUG test and 6MWT (1.2 ~ 2.0), and between 0.8 and 1.2 for the other tests. The areas under the curve to discriminate the two groups were mostly excellent to outstanding, except for the 30sCST. Convergent validity was documented with a moderate correlation between the 9 s-SCT and the physical function (WOMAC-PF) subscale scores (Spearman’s ρ = 0.60). Conclusions The OARSI recommended core set was generally highly discriminative between people with K-L grade 0–2 KOA and their controls, but convergent/divergent validity was observed only in the 9 s-SCT. Further studies are required to evaluate the responsiveness of these tests and understand the discordance of physical performance and self-reported measures.

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The relationship of radiographic findings with pain, function, and quality of life in patients with knee osteoarthritis

Cited by 18 publications

References 37 publications

An Algorithmic Approach to Understanding Osteoarthritic Knee Pain

An Algorithmic Approach to Understanding Osteoarthritic Knee Pain

Using multivariate nonlinear mixed-effects model to investigate factors influencing symptom improvement after high tibial osteotomy in combination with bone marrow concentrate injection for medial compartment knee osteoarthritis: a prospective, open-label study

Validity of the Osteoarthritis Research Society International (OARSI) recommended performance-based tests of physical function in individuals with symptomatic Kellgren and Lawrence grade 0–2 knee osteoarthritis

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