Global trends in research of venous thromboembolism associated with lower limb joint arthroplasty: A bibliometric analysis
Bibliographic record
Abstract
This study aims to visualize publications related to venous thromboembolism (VTE) and lower limb joint arthroplasty to identify research frontiers and hotspots, providing references and guidance for further research. We retrieved original articles published from 1985 to 2022 and their recorded information from the Web of Science Core Collection. The search strategy used terms related to knee or hip arthroplasty and thromboembolic events. Microsoft Excel was used to analyze the annual publications and citations of the included literature. The rest of the data were analyzed using the VOSviewer, citespace and R and produced visualizations of these collaborative networks. We retrieved 3543 original articles and the results showed an overall upward trend in annual publications. The United States of America had the most significant number of publications (Np) and collaborative links with other countries. McMaster University had the greatest Np. Papers published by Geerts WH in 2008 had the highest total link strength. Journal of Arthroplasty published the most articles on the research of VTE associated with lower limb joint arthroplasty. The latest research trend mainly involved "general anesthesia" "revision" and "tranexamic acid." This bibliometric study revealed that the research on VTE after lower limb joint arthroplasty is developing rapidly. The United States of America leads in terms of both quantity and quality of publications, while European and Canadian institutions and authors also make significant contributions. Recent research focused on the use of tranexamic acid, anesthesia selection, and the VTE risk in revision surgeries.
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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 | 0.006 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.146 | 0.187 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".