A practical MRI grading system for osteoarthritis of the knee: Association with Kellgren–Lawrence radiographic scores

Park, Heejin; Kim, Sam Soo; Lee, So Yeon; Park, Noh-Hyuck; Park, Jiyeon; Choi, Younghoon; Jeon, Hyun-Jun

doi:10.1016/j.ejrad.2012.02.023

Cited by 63 publications

(44 citation statements)

References 13 publications

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“…However, this is a patient‐reported tool that may suffer from respondent biases (reporting and information). We avoided these biases by using a standard clinical index (KL) that has been widely accepted among specialists of rheumatology as a standard measure of OA progression …”

Section: Discussionmentioning

confidence: 99%

“…The KL scale is a radiological measure of OA severity that is reported by a rheumatologist . This has been identified by the WHO as a standard scale for cross‐sectional studies …”

Section: Methodsmentioning

confidence: 99%

“…Osteoarthritis (OA) is a chronic degenerative disease that causes much disability and pain, especially among older adults . The main characteristic of the disease is a gradual loss of cartilage in the joints . The joints most affected by the disease are knees, hips and hands .…”

Section: Introductionmentioning

confidence: 99%

“…1 The main characteristic of the disease is a gradual loss of cartilage in the joints. 2 The joints most affected by the disease are knees, hips and hands. 3,4 OA is a worldwide health problem that involves about 8-15% of the general population.…”

Section: Introductionmentioning

confidence: 99%

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Psychometric examination of the Persian version of Osteoarthritis Knee and Hip Quality of Life questionnaire

et al. 2014

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Section: Discussionmentioning

confidence: 99%

“…The KL scale is a radiological measure of OA severity that is reported by a rheumatologist . This has been identified by the WHO as a standard scale for cross‐sectional studies …”

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Psychometric examination of the Persian version of Osteoarthritis Knee and Hip Quality of Life questionnaire

et al. 2014

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“…At first we confirmed OA patients and combined clinical record data with Kellgren-Lawrence (KL) grades. The KL grading system is considered the gold standard for initial assessment of knee osteoarthritis severity in radiographs [18, 19]. KL grades come from X-ray images examination.…”

Section: Methodsmentioning

confidence: 99%

An interpretable boosting model to predict side effects of analgesics for osteoarthritis

Liu

Fei

et al. 2018

BMC Syst Biol

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BackgroundOsteoarthritis (OA) is the most common disease of arthritis. Analgesics are widely used in the treat of arthritis, which may increase the risk of cardiovascular diseases by 20% to 50% overall.There are few studies on the side effects of OA medication, especially the risk prediction models on side effects of analgesics. In addition, most prediction models do not provide clinically useful interpretable rules to explain the reasoning process behind their predictions. In order to assist OA patients, we use the eXtreme Gradient Boosting (XGBoost) method to balance the accuracy and interpretability of the prediction model.ResultsIn this study we used the XGBoost model as a classifier, which is a supervised machine learning method and can predict side effects of analgesics for OA patients and identify high-risk features (RFs) of cardiovascular diseases caused by analgesics. The Electronic Medical Records (EMRs), which were derived from public knee OA studies, were used to train the model. The performance of the XGBoost model is superior to four well-known machine learning algorithms and identifies the risk features from the biomedical literature. In addition the model can provide decision support for using analgesics in OA patients.ConclusionCompared with other machine learning methods, we used XGBoost method to predict side effects of analgesics for OA patients from EMRs, and selected the individual informative RFs. The model has good predictability and interpretability, this is valuable for both medical researchers and patients.

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Preoperative glycaemic control, number of pain locations, structural knee damage, self‐reported central sensitisation, satisfaction and personal control are predictive of 1‐year postoperative pain, and change in pain from pre‐ to 1‐year posttotal knee arthroplasty

Vervullens,

Meert,

Smeets

et al. 2024

Knee surg. sports traumatol. arthrosc.

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PurposeThe aim of this study was to identify preoperative predictors for 1‐year posttotal knee arthroplasty (TKA) pain and pre‐ to post‐TKA pain difference in knee osteoarthritis (KOA) patients.MethodsFrom March 2018 to July 2023, this prospective longitudinal cohort study enrolled KOA patients awaiting TKA from four hospitals in Belgium and the Netherlands. Different biopsychosocial predictors were assessed preoperatively by questionnaires and physical examinations (input variables). The Knee injury and Osteoarthritis Outcome Score (KOOS) subscale pain was used to measure pain intensity. The absolute KOOS subscale pain score 1‐year post‐TKA and the difference score (ΔKOOS = 1‐year postoperative − preoperative) were used as primary outcome measures (output variables). Two multivariable linear regression analyses were performed.ResultsTwo hundred and twenty‐three participants were included after multiple imputation. Worse absolute KOOS subscale pain scores 1‐year post‐TKA and negative or closer to zero ΔKOOS subscale pain scores were predicted by self‐reported central sensitisation, lower KOA grade and preoperative satisfaction, and higher glycated haemoglobin, number of pain locations and personal control (adjusted R2 = 0.25). Additional predictors of negative or closer to zero ΔKOOS subscale pain scores were being self‐employed, higher preoperative pain and function (adjusted R2 = 0.37).ConclusionThis study reports different biopsychosocial predictors for both outcomes that have filtered out other potential predictors and provide value for future studies on developing risk assessment tools for the prediction of chronic TKA pain.Protocol RegistrationThe protocol is registered at clinicaltrials.gov (NCT05380648) on 13 May 2022.Level of EvidenceLevel II.

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A practical MRI grading system for osteoarthritis of the knee: Association with Kellgren–Lawrence radiographic scores

Cited by 63 publications

References 13 publications

Psychometric examination of the Persian version of Osteoarthritis Knee and Hip Quality of Life questionnaire

Psychometric examination of the Persian version of Osteoarthritis Knee and Hip Quality of Life questionnaire

An interpretable boosting model to predict side effects of analgesics for osteoarthritis

Preoperative glycaemic control, number of pain locations, structural knee damage, self‐reported central sensitisation, satisfaction and personal control are predictive of 1‐year postoperative pain, and change in pain from pre‐ to 1‐year posttotal knee arthroplasty

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