Bibliometric analysis of the top 100 most-cited articles on tissue expander use in breast reconstruction: insights from CiteSpace, VOSviewer, and Bibliometrix
Bibliographic record
Abstract
Background: Tissue expanders are widely used in both immediate and delayed breast reconstruction after mastectomy. With advances in surgical techniques and biomaterials, this field has seen continuous development. This study aimed to analyze the top 100 most-cited articles on tissue expanders in breast reconstruction to identify research trends and progress in this field. Methods: The top 100 most cited articles were selected from the Web of Science Core Collection (WoSCC) for a systematic search. Comprehensive bibliometric analyses were conducted using VOSviewer, CiteSpace, and Bibliometrix. Additionally, clinical trial data were retrieved from ClinicalTrials.gov (https://www.clinicaltrials.gov) and the World Health Organization International Clinical Trials Registry Platform (ICTRP) (https://trialsearch.who.int). Results: The top-cited articles span multiple disciplines, with the USA contributing the highest number of publications. China, Canada, and the UK ranked second in terms of publication volume. Representative institutions included the University of Michigan and Memorial Sloan Kettering Cancer Center. Key authors included Cordeiro PG and Wilkins EG. Frequent keywords were “implant”, “mastectomy”, “complications”, and “radiotherapy”. The most cited article was by Chun YS et al. [2010]. Of the clinical trials, 66 were retrieved from ClinicalTrials.gov and 37 from ICTRP. After removing duplicates, a total of 78 trials focused on tissue expanders in breast reconstruction were included. Conclusions: Research on tissue expanders in breast reconstruction focuses on surgical optimization, complication management, biomaterials, and patient-reported outcome measures (PROMs). Current trends emphasize personalized reconstruction strategies and improved postoperative care. Challenges remain in addressing patient variability and biomaterial safety. Further research is needed to refine individualized approaches and improve clinical outcomes.
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 | 0.015 | 0.098 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.249 | 0.264 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".