Prevalence and Characteristics of Knee Osteoarthritis Among the General Public in Saudi Arabia
Bibliographic record
Abstract
Background Knee osteoarthritis (OA) is a chronic and progressive knee joint condition that is influenced by multiple factors. This research aims to examine the prevalence and characteristics of knee OA among the general public in Saudi Arabia. Methodology This cross-sectional online survey was conducted in September 2023 in Saudi Arabia. This research used a previously developed questionnaire to validate the diagnosis of OA, which was performed in accordance with the diagnostic criteria established by the American College of Rheumatology (ACR). The Western Ontario and McMaster Universities Arthritis Index questionnaire (WOMAC) was used to examine the severity and characteristics of knee OA patients. A binary logistic regression analysis was conducted to determine the variables that influence the severity of knee OA and the likelihood of developing OA. Results A total of 1,019 individuals participated in this study. Around one-third of the participants (34.5%) fulfilled the ACR criteria for knee OA diagnosis. Overall, the mean WOMAC score was 34.1 (18.8) out of 96, which represents 35.5% of the maximum obtainable score and demonstrates a low degree of knee OA severity. The mean pain sub-scale score was 7.4 (3.8) out of 20, which represents 37.0% of the maximum obtainable score and demonstrates a low level of pain intensity. The mean stiffness sub-scale score was 2.7 (1.8) out of 8, which represents 33.8% of the maximum obtainable score and demonstrates a low degree of stiffness in joints. The mean physical function sub-scale score was 24.0 (14.0) out of 68, which represents 35.3% of the maximum obtainable score and demonstrates a low level of physical function difficulty. Females, older participants (above 40 years), those with high body mass index (28.8 kg/cm2 and higher), non-smokers, those with comorbidities, those who did not practice daily physical activity, those who had a family history of knee OA, and those who suffered from flat feet, rheumatoid arthritis, gout, lupus, or back or hip pain were more likely to develop knee OA and have severe OA (p < 0.05). Conclusions The findings of this study demonstrated a significant prevalence rate of knee OA and highlighted a discrepancy between the rates obtained by diagnostic criteria and those determined through clinical diagnosis. Several significant factors that contribute to the development of OA encompass lifestyle choices such as food and exercise, familial predisposition, genetic influences, and the presence of comorbidities. To effectively tackle this intricate matter, it is imperative to adopt a patient-centered strategy and prioritize early intervention.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".