Risk of venous thromboembolism in knee, hip and hand osteoarthritis: a general population-based cohort study
Bibliographic record
Abstract
OBJECTIVES: Osteoarthritis is a leading cause of immobility and joint replacement, two strong risk factors for venous thromboembolism (VTE). We aimed to examine the relation of knee, hip and hand osteoarthritis to the risk of VTE and investigate joint replacement as a potential mediator. METHODS: We conducted three cohort studies using data from The Health Improvement Network. Up to five individuals without osteoarthritis were matched to each case of incident knee (n=20 696), hip (n=10 411) or hand (n=6329) osteoarthritis by age, sex, entry time and body mass index. We examined the relation of osteoarthritis to VTE (pulmonary embolism and deep vein thrombosis) using a multivariable Cox proportional hazard model. RESULTS: VTE developed in 327 individuals with knee osteoarthritis and 951 individuals without osteoarthritis (2.7 vs 2.0 per 1000 person-years), with multivariable-adjusted HR being 1.38 (95% CI 1.23 to 1.56). The indirect effect (HR) of knee osteoarthritis on VTE through knee replacement was 1.07 (95% CI 1.01 to 1.15), explaining 24.8% of its total effect on VTE. Risk of VTE was higher in hip osteoarthritis than non-osteoarthritis (3.3 vs 1.8 per 1000 person-years; multivariable-adjusted HR=1.83, 95% CI 1.56 to 2.13). The indirect effect through hip replacement yielded an HR of 1.14 (95% CI 1.04 to 1.25), explaining 28.1% of the total effect. No statistically significant difference in VTE risk was observed between hand osteoarthritis and non-osteoarthritis (1.5 vs 1.6 per 1000 person-years; multivariable-adjusted HR=0.88, 95% CI 0.67 to 1.16). CONCLUSION: Our large population-based cohort study provides the first evidence that knee or hip osteoarthritis, but not hand osteoarthritis, was associated with an increased risk of VTE, and such an association was partially mediated through knee or hip replacement.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".