A clinical study based on bidirectional Mendelian randomization: Correlation between generalized anxiety disorder and weight-bearing joints osteoarthritis
Bibliographic record
Abstract
Objectives: Bidirectional Mendelian randomization (MR) combined with clinical case analysis was used to elucidate the relationship between generalized anxiety disorder (GAD) caused by mental overload and the risk of weight-bearing joint (hip/knee) osteoarthritis (OA). Methods: We performed MR analyses using publicly released genome-wide association study summary statistics to measure the causal effects between mental overload and weight-bearing joint OA risk. The primary MR analysis utilized the inverse-variance weighted (IVW) method, complemented by additional methods, including simple mode, weighted mode, MR-Egger regression, and weighted median. The leave-one-out method was used for sensitivity analysis. Concurrently, data from patients with OA (Kellgren-Lawrence grades III-IV) who needed total knee/hip arthroplasty were collected. Patient assessments were conducted utilizing the Western Ontario and McMaster Universities arthritis index, Penn State worry questionnaire, and visual analogue scale. Results: Genetically predisposed GAD did not correlate with the risk of weight-bearing joint OA (IVW odds ratio [OR] = 0.840, 95 % confidence interval = 0.128, 5.50, P = 0.855). In reverse MR analyses, we detected no causal effect of weight-bearing OA on GAD (IVW OR = 1.00, 95 % CI = 0.985, 1.03, P = 0.687). In the clinical case evaluation, weight overload joint OA and GAD were highly correlated. Conclusion: MR analysis indicated no bidirectional causal effect of GAD caused by mental overload on weight-bearing joint (hip or knee) OA. Clinical studies support the finding that GAD is highly correlated with weight-bearing joint OA. However, whether there is a causal relationship between GAD caused by mental overload and weight-overloading joint OA requires further investigation.
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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 | 0.001 | 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".