ReviewJournal of robotic surgery2026
Global research trends in robotic surgery for rectal cancer: a bibliometric and science-mapping analysis.
Review in Journal of robotic surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The learning curve of robotic esophagectomy: a systematic review with a proposed training and competency assessment framework.Frontiers in oncology · 2026Pooled it
- Short-term outcomes of robotic-assisted distal pancreatectomy using domestic KangDuo Surgical Robot-2000 System versus Da Vinci Xi system: a two-center prospective observational cohort study.Surgical endoscopy · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Robotic-assisted surgery has become an important modality in minimally invasive rectal cancer management because of its enhanced dexterity, three-dimensional visualization, and technical advantages in confined pelvic surgery. As the volume of research in this area continues to expand, a structured understanding of its scientific development is needed. This study aimed to map the global research landscape of robotic surgery in rectal tumor and rectal cancer through a bibliometric analysis of the published literature. A comprehensive search of Scopus, Web of Science Core Collection, and MEDLINE was performed, and records were screened using a PRISMA-guided selection process. The final dataset comprised 1,196 documents published between 2017 and 2026, including 1,168 journal articles and 28 conference/proceedings papers. Bibliometric performance indicators, citation analysis, and science-mapping approaches were applied using R (Bibliometrix/Biblioshiny) and VOSviewer to evaluate publication growth, influential sources, geographic and collaborative patterns, and thematic development. The results showed sustained growth over the study period, with the literature entering a more mature phase. The literature was concentrated in a limited number of core journals, led by Journal of Robotic Surgery, Surgical Endoscopy and Other Interventional Techniques, and Techniques in Coloproctology. The United States, Japan, and China were among the most productive countries, while thematic analyses showed a progression from early feasibility- and comparison-oriented research toward more specialized themes involving operative performance, postoperative outcomes, and oncologic quality. Overall, the field has developed into a mature and structured research domain with a strong clinical and outcome-driven focus. These findings provide a comprehensive overview of the intellectual, conceptual, and collaborative structure of robotic rectal surgery research and may help guide future investigation and international research cooperation.
Indexed as
Identifiers
42560635What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.