The top 100 most cited articles on total hip arthroplasty: a bibliometric analysis
Bibliographic record
Abstract
BACKGROUND: Over the past few decades, more and more articles about total hip arthroplasty have been published. We noticed, however, little is known about the characteristics and qualities of these studies. METHODS: The databases of Web of Science Core Collection, BIOSIS Citation Index, MEDLINE, etc. were utilized for the identification of articles published from 1990 to May 2019. Total hip arthroplasty-related articles were identified, and the 100 most cited articles were selected for subsequent analysis of citation count, citation density (citations/article age), authorship, theme, geographic distribution, time-related flux, level of evidence, and network analysis. RESULTS: The selected 100 articles were published mainly in the 1990s (46%) and 2000s (47%) with almost equal amount. Citations per article ranged from 994 to 191. Leading countries were the USA followed by Canada, England, and Sweden, all located in North America and Western Europe. The most highlighted study themes were postoperative thrombosis and surgical methods and materials. The most common level of evidence was level III (35%). The network analysis connoted that radiography, acetabulum, reoperation, and bone cement had a high degree of centrality in the 1990s, while cement had a high degree of centrality in the 2000s and 2010s. CONCLUSIONS: The time, area, and theme distribution of the top 100 most cited articles in the total hip arthroplasty have been thoroughly analyzed. It is noticeable that postoperative thromboembolism currently plays a major role in the field of total hip arthroplasty researches. However, most of them focus on the effectiveness of different treatments and drugs; little is known about its underlying mechanisms and influencing factors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.125 | 0.122 |
| 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) | 0.006 | 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".