Risk factors for venous thromboembolism after knee arthroscopy: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Over the past few years, a growing number of knee arthroscopy (KA) procedures have been associated with an escalating incidence of postoperative venous thromboembolism (VTE), posing a significant threat to patient well-being. Nevertheless, the purpose of this study is to evaluate and synthesize the risk factors associated with VTE following KA, thereby establishing a scientific foundation for developing evidence-based clinical preventive measures. METHODS: We conducted a comprehensive search across the PubMed, Embase, Web of Science, and Cochrane Library databases for relevant literature spanning from January 1, 2019, to January 1, 2025. We meticulously reviewed all English-language observational studies about the risk factors associated with VTE after KA. The quality of the selected studies was critically appraised utilizing the Newcastle-Ottawa Scale (NOS). Subsequently, odds ratios (OR) and 95% confidence intervals (CI) were determined to assess the relationship between various risk factors and the incidence of VTE after KA. RESULTS: A total of 11 observational studies were included, all of which demonstrated moderate to high methodological quality. The studies involved 875,099 patients who underwent arthroscopic KA. The meta-analysis results indicated that the risk factors for venous thrombosis after KA include age over 30 years (OR = 1.59, 95% CI: [1.20, 2.12], P < 0.001), body mass index (BMI) over 25 (OR = 1.23, 95% CI: [1.07, 1.41], P = 0.004), and D-dimer over 0.62 mg/L (OR = 5.69, 95% CI: [1.41, 22.89], P = 0.014). CONCLUSION: Age over 30 years, BMI over 25, and D-dimer over 0.62 mg/L are significant risk factors for VTE following KA. Limited evidence also suggests an association between oral contraceptive use and a higher risk of VTE following KA.
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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 | 0.015 | 0.034 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.036 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".