Evidence map›Paper›PMID 40629094›Full record

ReviewJournal of robotic surgery2025

Global dynamics of robotic surgery research: a multi-method bibliometric investigation and focus on the top 100 most cited papers.

Siddig Ibrahim Abdelwahab, Manal Mohamed Elhassan Taha, Abdullah Farasani, Jobran M Moshi, Abrar Fahad Alshahrani, Ahmad Assiri, Saeed Alshahrani, Muhammad H Sultan, Khaled A Sahli, Hussam M Shubaily and 2 more

Abstract readReview
PubMed Publisher
In one paragraph

Review in Journal of robotic surgery, 2025. 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.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Siddig Ibrahim AbdelwahabHealth Research Center, Jazan University, Jazan, Saudi Arabia.
Manal Mohamed Elhassan TahaHealth Research Center, Jazan University, Jazan, Saudi Arabia.
Abdullah FarasaniDepartment of Medical Laboratory Technology, Faculty of Nursing and Health Sciences, Jazan University, Jazan, Saudi Arabia.
Jobran M MoshiDepartment of Medical Laboratory Technology, Faculty of Nursing and Health Sciences, Jazan University, Jazan, Saudi Arabia.
Abrar Fahad AlshahraniDepartment of Clinical Nutrition, Faculty of Nursing and Health Sciences, Jazan University, Jazan, Saudi Arabia.
Ahmad AssiriDepartment of Dermatology, Faculty of Medicine, Jazan University, Jazan, Saudi Arabia.
Saeed AlshahraniDepartment of Pharmacology and Toxicology, College of Pharmacy, Jazan University, Jazan, Saudi Arabia.
Muhammad H SultanDepartment of Pharmaceutics, College of Pharmacy, Jazan University, Jazan, Saudi Arabia.
Khaled A SahliSecurity Forces Hospitals Program, General Directorate of Medical Services, Ministry of Interior, Riyadh, Saudi Arabia.
Hussam M ShubailyDepartment of Pathology, Faculty of Medicine, Jazan University, Jazan, Saudi Arabia.
Omer Ahmed ElrhimaDepartment of Pathology, Faculty of Medicine, Jazan University, Jazan, Saudi Arabia.
Waseem HassanInstitute of Chemical Sciences, University of Peshawar, Peshawar, 25120, Khyber Pakhtunkhwa, Pakistan. waseem_anw@yahoo.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study utilizes the Scopus database and adopts a multi-layered approach to provide a comprehensive and detailed overview of robotic surgery research. Specifically, three complementary strategies: (a) a title-abstract-keyword (TAK) search, (b) a title-specific search, and (c) a focused analysis of the top 100 most cited papers were employed. The TAK approach retrieved 49,026 publications, substantially surpassing the 8,029 identified via the title-only method, demonstrating that incorporating abstracts and keywords provides broader coverage. Analysis of prolific authors revealed Mottrie, A. as the most productive researcher in the TAK dataset, while Fukuda, T. led in the title-only set. Leading institutions such as the Cleveland Clinic Foundation and Yonsei University College of Medicine exhibited markedly higher outputs under TAK criteria. Country-level analysis confirmed the United States as the dominant contributor in both datasets, though absolute counts dropped significantly when limited to titles. The Journal of Robotic Surgery emerged as the most productive source across both methods. Funding sponsor analysis highlighted the National Natural Science Foundation of China as the leading funder, with the TAK dataset revealing greater international sponsorship diversity. Citation analysis of the top 100 most cited documents, spanning 1993-2021, showed an average of 279.6 citations per article, with recent papers (2018-2021) achieving unprecedented citation velocity, suggesting earlier peaks in influence for newer publications. Keyword analysis of the top 150 most frequently occurring terms in the title-specific dataset helped to map key research directions. From the title-based corpus, the 100 most cited papers were analyzed, reporting their total citations, citations per paper, and citations per year. A detailed author-level analysis was performed, including publication count, citation impact, and scholarly indices (h-index, g-index, m-index), complemented by visualizations of collaboration networks. Moreover, this study incorporates a co-word analysis of the top 100 cited papers, using unigrams, bigrams, and trigrams to illustrate central themes. The top 20 most cited papers are briefly discussed. The findings offer updated, actionable insights for researchers, clinicians, and policymakers seeking to navigate this rapidly advancing field.

Indexed as

BibliometricsBiomedical ResearchRobotic Surgical ProceduresHumansBibliometric analysisCitation analysisCo-word analysisMost cited papersRobotic surgeryScopusTitle-abstract-keyword searchTitle-specific search

Identifiers

PMID40629094

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.