Cross-sectional assessment of cardiovascular risk factors in patients with knee osteoarthritis

Public Awareness and Attitudes Toward Lifestyle Modifications for Controlling Osteoarthritis and Their Relationship to Cardiovascular Risk Factors

Background Osteoarthritis (OA), common in older adults, leads to joint degradation and inflammation, with risk factors including age, obesity, and genetics. OA strongly indicates cardiovascular disease (CVD), with shared risk factors such as lack of exercise and muscle weakness. This study explores the awareness of OA and its relationship to CVD risk factors. Methodology This cross-sectional study in Al Ahsa, Saudi Arabia, involved an online self-administered questionnaire distributed via Google Forms to randomly selected adults, with ages ranging from 18 to 65 years. Informed consent was taken from all participants. Data was cleaned in Excel and analyzed using SPSS version 29 (IBM Corp., Armonk, NY, USA). Results Our study assessed the awareness of 381 participants about the relationship between OA and CVD. Most participants were female 312 (81.9%). Overall, 250 (65.6%) participants were aged 18-27, and 362 (95.0%) were Saudi nationals. Further, 210 (55.1%) participants had a bachelor's degree, and 223 (58.5%) were students. Healthcare exposure varied, with 207 (54.3%) having no background, and 157 (41.2%) being healthcare students. Notably, 152 (39.9%) knew someone diagnosed with OA, of whom 55 (14.4%) also had CVD. Significant predictors of awareness included studying in healthcare (Exp(B) = 3.325, p = 0.001), receiving OA information (Exp(B) = 2.222, p = 0.007), sources such as school/university (Exp(B) = 7.851, p = 0.000), and personal experience (Exp(B) = 4.768, p = 0.034). Conclusions This study showed a notable gap in awareness about the link between OA and CVD in Al Ahsa, Saudi Arabia. While those with healthcare exposure showed good knowledge, many lacked an understanding of their relationship. Targeted education, particularly for younger and non-healthcare-educated groups, is crucial for improving awareness and promoting effective lifestyle modifications to manage both OA and CVD risks.

Machine learning analysis of serum cholesterol's impact on knee osteoarthritis progression

The controversy surrounding whether serum total cholesterol is a risk factor for the graded progression of knee osteoarthritis (KOA) has prompted this study to develop an authentic prediction model using a machine learning (ML) algorithm. The objective was to investigate whether serum total cholesterol plays a significant role in the progression of KOA. This cross-sectional study utilized data from the public database DRYAD. LASSO regression was employed to identify risk factors associated with the graded progression of KOA. Additionally, six ML algorithms were utilized in conjunction with clinical features and relevant variables to construct a prediction model. The significance and ranking of variables were carefully analyzed. The variables incorporated in the model include JBS3, Diabetes, Hypertension, HDL, TC, BMI, SES, and AGE. Serum total cholesterol emerged as a significant risk factor for the graded progression of KOA in all six ML algorithms used for importance ranking. XGBoost algorithm was based on the combined best performance of the training and validation sets. The ML algorithm enables predictive modeling of risk factors for the progression of the KOA K-L classification and confirms that serum total cholesterol is an important risk factor for the progression of KOA.

Association between osteoarthritis and cardiovascular disease in elderly in Japan: an administrative claims database analysis

OBJECTIVE

To investigate whether osteoarthritis (OA) is a risk factor for cardiovascular disease (CVD); whether there are differences concerning ischaemic heart disease (IHD), congestive heart failure (CHF) and stroke; and whether there are differences between OA sites (hips, knees and hand) in predicting CVD onset.

DESIGN

Population-based matched case-control study.

SETTING

Health insurance claims data among Japanese patients.

PARTICIPANTS

Japanese patients aged ≥65 years with newly diagnosed CVD and hospitalised between January 2015 and December 2020 (cases) and age-matched and sex-matched 1:1 individuals (controls).

MAIN OUTCOME MEASURES

A conditional logistic regression model was used to estimate the adjusted ORs and their 95% CIs for CVD, IHD, CHF and stroke risk, adjusting for covariates.

RESULTS

A total of 79 296 patients were included, with respect to CVD (39 648 patients with newly diagnosed CVD and 39 648 controls). After adjustment for covariates, the exposure odds of knee OA (KOA), hip OA (HipOA) and hand OA (HandOA) for CVD were 1.192 (95% CI 1.115 to 1.274), 1.057 (95% CI 0.919 to 1.215) and 1.035 (95% CI 0.684 to 1.566), respectively, showing an association only for KOA. The exposure odds of KOA, HipOA and HandOA for IHD were 1.187 (95% CI 1.086 to 1.297), 1.078 (95% CI 0.891 to 1.306) and 1.099 (95% CI 0.677 to 1.784), respectively. The exposure odds of KOA, HipOA and HandOA for stroke were 1.221 (95% CI 1.099 to 1.356), 0.918 (95% CI 0.723 to 1.165) and 1.169 (95% CI 0.635 to 2.151), respectively. Similar to CVD, only KOA was associated with both. For CHF, neither KOA nor HipOA and HandOA were associated with CHF development.

CONCLUSION

This study confirms the association of KOA with CVD, particularly IHD and stroke, in the Japanese population. The finding that patients with KOA have a higher CVD risk can potentially assist in guiding future treatment strategies.

Efficacy of Herbal Medicine in Hand Osteoarthritis: A Narrative Review

OBJECTIVE

Osteoarthritis (OA) is one of the most prevalent joint disorders in the world that has placed an enormous economic and social burden on governments and healthcare sectors in many countries. Hand OA (HOA) is the most common peripheral arthritis, which is less investigated than knee and hip OA. Due to limited approved drug choices and adverse effects of long-term use of current regimens, we aimed to review the existing evidence that were used as oral herbal medicine to treat HOA.

METHODS

The PubMed database was searched for both observational and interventional studies that have investigated herbal medicine safety and efficacy in HOA, written in English and published between 2010 and 2022.

RESULTS

A total of 5 original articles fulfilled the inclusion criteria, and each article assessed a different herbal regimen. Overall, it seems desirable to add specific herbal treatments to the regimen of HOA patients, specifically in case of early stages of HOA.

CONCLUSION

Currently, the need for a low-risk alternative treatment in HOA patients is felt more than ever. There are reliable references relating to the safety of Korean red ginseng, GCSB-5, XLGB, and GS-GCu in these patients, although their efficacy was limited. Additionally, herbs like curcumin and Boswellia serrata have positively affected patients with knee osteoarthritis. However, there is a lack of strong evidence supporting their effectiveness in hand osteoarthritis (HOA). This emphasizes the potential benefits that these herbs may have for HOA patients.

The Relationship Between Echocardiographic Calcification Score and Grade of Knee Osteoarthritis

Background and objective It has been suggested that knee osteoarthritis (KOA) is associated with the development of calcification and an increased risk of cardiovascular (CV) disease, while the contribution of KOA grade is not clearly known enough. This study aimed to investigate the relationship between the grade of KOA, the echocardiographic calcification score (echo-CCS), and CV risk assessment. Methods This cross-sectional study involved 204 patients diagnosed with KOA and classified according to the Kellgren-Lawrence staging criteria. Echo-CCS was obtained according to the presence of calcification in the aortic valve, aortic root, mitral ring, papillary muscle and ventricular septum. Framingham risk score (FRS) was used for CV risk assessment. Results Calcification was detected in 79.4% of patients. The median FRS, echo-CCS, and high-sensitivity C-reactive protein (hs-CRP) levels increased as the KOA grade increased (p<0.05). A one-grade increase in KOA increased the odds of echo-CCS 1-2 group by 5.15 fold (vs. no calcification group) (OR=5.15, p=0.003), while it increased the odds of echo-CCS ≥3 group by 4.61 fold (vs. echo-CCS 1-2 group) (OR=4.61, p=0.003). Median echo-CSS and hs-CRP were higher in the high CV risk group than in the moderate and low CV risk groups. Conclusion The majority of patients with KOA had intracardiac calcification. An increased KOA grade was associated with higher echo-CSS and FRS. These findings indicate that patients with higher grades of KOA may be predisposed to developing subclinical atherosclerosis.

A clinical model to predict the progression of knee osteoarthritis: data from Dryad

BACKGROUND

Knee osteoarthritis (KOA) is a multifactorial, slow-progressing, non-inflammatory degenerative disease primarily affecting synovial joints. It is usually induced by advanced age and/or trauma and eventually leads to irreversible destruction of articular cartilage and other tissues of the joint. Current research on KOA progression has limited clinical application significance. In this study, we constructed a prediction model for KOA progression based on multiple clinically relevant factors to provide clinicians with an effective tool to intervene in KOA progression.

METHOD

This study utilized the data set from the Dryad database which included patients with Kellgren-Lawrence (KL) grades 2 and 3. The KL grades was determined as the dependent variable, while 15 potential predictors were identified as independent variables. Patients were randomized into training set and validation set. The training set underwent LASSO analysis, model creation, visualization, decision curve analysis and internal validation using R language. The validation set is externally validated and F1-score, precision, and recall are computed.

RESULT

A total of 101 patients with KL2 and 94 patients with KL3 were selected. We randomly split the data set into a training set and a validation set by 8:2. We filtered "BMI", "TC", "Hypertension treatment", and "JBS3 (%)" to build the prediction model for progression of KOA. Nomogram used to visualize the model in R language. Area under ROC curve was 0.896 (95% CI 0.847-0.945), indicating high discrimination. Mean absolute error (MAE) of calibration curve = 0.041, showing high calibration. MAE of internal validation error was 0.043, indicating high model calibration. Decision curve analysis showed high net benefit. External validation of the metabolic syndrome column-line graph prediction model was performed by the validation set. The area under the ROC curve was 0.876 (95% CI 0.767-0.984), indicating that the model had a high degree of discrimination. Meanwhile, the calibration curve Mean absolute error was 0.113, indicating that the model had a high degree of calibration. The F1 score is 0.690, the precision is 0.667, and the recall is 0.714. The above metrics represent a good performance of the model.

CONCLUSION

We found that KOA progression was associated with four variable predictors and constructed a predictive model for KOA progression based on the predictors. The clinician can intervene based on the nomogram of our prediction model.

KEY INFORMATION

This study is a clinical predictive model of KOA progression. KOA progression prediction model has good credibility and clinical value in the prevention of KOA progression.

Occulus-Guided Rehabilitation Approach in a Patient With Osteoarthritis Knee: A Case Report

Osteoarthritis (OA) is the most frequent musculoskeletal condition affecting the elderly's quality of life. Wear and tear, as well as the progressive deterioration of articular cartilage, are the causes of OA, also known as degenerative joint disease. There are two types of OA: primary and secondary. The condition can be treated both conservatively and surgically. Medication and physical therapy might be used to treat it conservatively. Physical rehabilitation can include advanced management through the use of virtual reality (VR). The other option for treatment is surgical management. We are presenting a case of a 52-year-old female who presented to musculoskeletal physiotherapy out patient department with complaints of left-sided knee pain, stiffness, and difficulty in sitting with crossed legs on the floor. On examination, crepitations were present. Knee range of motion and strength were significantly reduced. Physiotherapy treatment was planned for the same. In physiotherapy rehabilitation, Occulus-guided physiotherapy exercises were given to improve the strength and range of motion of the joint.

A Simple Nomogram for Predicting Osteoarthritis Severity in Patients with Knee Osteoarthritis

Objective

To explore the influencing factors of knee osteoarthritis (KOA) severity and establish a KOA nomogram model.

Methods

Inpatient data collected in the Department of Joint Surgery, Chengde Medical University Affiliated Hospital from January 2020 to January 2022 were used as the training cohort. Patients with knee osteoarthritis who were admitted to the Third Hospital of Hebei Medical University from February 2022 to May 2022 were taken as the external validation group of the model. In the training group, the least absolute shrinkage and selection operator (LASSO) method was used to screen the factors of KOA severity to determine the best prediction index. Then, after combining the significant factors from the LASSO and multivariate logistic regressions, a prediction model was established. All potential prediction factors were included in the KOA severity prediction model, and the corresponding nomogram was drawn. The consistency index (C-index), area under the receiver operating characteristic (ROC) curve (AUC), GiViTi calibration band, net classification improvement (NRI) index, and integrated discrimination improvement (IDI) index evaluation of a model predicted KOA severity. Decision curve analysis (DCA) and clinical influence curves were used to study the model's potential clinical value. The validation group also used the above evaluation indexes to measure the diagnostic efficiency of the model. Spearman correlation was used to investigate the relationship between nomogram-related markers and osteoarthritis severity.

Results

The total sample included 572 patients with knee osteoarthritis, including 400 patients in the training cohort and 172 patients in the validation cohort. The nomogram's predictive factors were age, pulse, absolute value of lymphocytes, mean corpuscular haemoglobin concentration (MCHC), and blood urea nitrogen (BUN). The C-index and AUC of the model were 0.802. The GiViTi calibration band (P = 0.065), NRI (0.091), and IDI (0.033) showed that the modified model can distinguish between severe KOA and nonsevere KOA. DCA showed that the KOA severity nomogram has clinical application value with threshold probabilities between 0.01 and 0.78. The external verification results also show the stability and diagnosis of the model. Age, pulse, MCHC, and BUN are correlated with osteoarthritis severity.

Conclusions

A nomogram model for predicting KOA severity was established for the first time that can visually identify patients with severe KOA and is novel for indirectly evaluating KOA severity by nonimaging means.