Top 100 most-cited original articles, systematic reviews/meta-analyses in robotic surgery: A scientometric study

How predictive is peer review for gauging impact? The association between reviewer rating scores, publication status, and article impact measured by citations in a pain subspecialty journal

BACKGROUND

Peer review represents a cornerstone of the scientific process, yet few studies have evaluated its association with scientific impact. The objective of this study is to assess the association of peer review scores with measures of impact for manuscripts submitted and ultimately published.

METHODS

3173 manuscripts submitted to Regional Anesthesia & Pain Medicine (RAPM) between August 2018 and October 2021 were analyzed, with those containing an abstract included. Articles were categorized by topic, type, acceptance status, author demographics and open-access status. Articles were scored based on means for the initial peer review where each reviewer's recommendation was assigned a number: 5 for 'accept', 3 for 'minor revision', 2 for 'major revision' and 0 for 'reject'. Articles were further classified by whether any reviewers recommended 'reject'. Rejected articles were analyzed to determine whether they were subsequently published in an indexed journal, and their citations were compared with those of accepted articles when the impact factor was <1.4 points lower than RAPM's 5.1 impact factor. The main outcome measure was the number of Clarivate citations within 2 years from publication. Secondary outcome measures were Google Scholar citations within 2 years and Altmetric score.

RESULTS

422 articles met inclusion criteria for analysis. There was no significant correlation between the number of Clarivate 2-year review citations and reviewer rating score (r=0.038, p=0.47), Google Scholar citations (r=0.053, p=0.31) or Altmetric score (p=0.38). There was no significant difference in 2-year Clarivate citations between accepted (median (IQR) 5 (2-10)) and rejected manuscripts published in journals with impact factors >3.7 (median 5 (2-7); p=0.39). Altmetric score was significantly higher for RAPM-published papers compared with RAPM-rejected ones (median 10 (5-17) vs 1 (0-2); p<0.001).

CONCLUSIONS

Peer review rating scores were not associated with citations, though the impact of peer review on quality and association with other metrics remains unclear.

Bibliometric and visualized analysis of hydrogels in organoids research

Over the past decades, there has been ongoing effort to develop complex biomimetic tissue engineering strategies for in vitro cultivation and maintenance of organoids. The defined hydrogels can create organoid models for various organs by changing their properties and various active molecules. An increasing number of researches has been done on the application of hydrogels in organoids, and a large number of articles have been published on the topic. Although there have been existing reviews describing the application of hydrogels in the field of organoids, there is still a lack of comprehensive studies summarizing and analyzing the overall research trends in this field. The citation can be used as an indicator of the scientific influence of an article in its field. This study aims to evaluate the application of hydrogels in organoids through bibliometric analysis, and to predict the hotspots and developing trends in this field.

A Bibliometric Analysis of Artificial Intelligence Applications in Spine Care

BACKGROUND

 With the rapid development of science and technology, artificial intelligence (AI) has been widely used in the diagnosis and prognosis of various spine diseases. It has been proved that AI has a broad prospect in accurate diagnosis and treatment of spine disorders.

METHODS

 On May 7, 2022, the Web of Science (WOS) Core Collection database was used to identify the documents on the application of AI in the field of spine care. HistCite and VOSviewer were used for citation analysis and visualization mapping.

RESULTS

 A total of 693 documents were included in the final analysis. The most prolific authors were Karhade A.V. and Schwab J.H. United States was the most productive country. The leading journal was Spine. The most frequently used keyword was spinal. The most prolific institution was Northwestern University in Illinois, USA. Network visualization map showed that United States was the largest network of international cooperation. The keyword "machine learning" had the strongest total link strengths (TLS) and largest number of occurrences. The latest trends suggest that AI for the diagnosis of spine diseases may receive widespread attention in the future.

CONCLUSIONS

 AI has a wide range of application in the field of spine care, and an increasing number of scholars are committed to research on the use of AI in the field of spine care. Bibliometric analysis in the field of AI and spine provides an overall perspective, and the appreciation and research of these influential publications are useful for future research.

Implementation of a Virtual Reality Based Digital-Twin Robotic Minimally Invasive Surgery Simulator

The rapid development of computers and robots has seen robotic minimally invasive surgery (RMIS) gradually enter the public's vision. RMIS can effectively eliminate the hand vibrations of surgeons and further reduce wounds and bleeding. However, suitable RMIS and virtual reality-based digital-twin surgery trainers are still in the early stages of development. Extensive training is required for surgeons to adapt to different operating modes compared to traditional MIS. A virtual-reality-based digital-twin robotic minimally invasive surgery (VRDT-RMIS) simulator was developed in this study, and its effectiveness was introduced. Twenty-five volunteers were divided into two groups for the experiment, the Expert Group and the Novice Group. The use of the VRDT-RMIS simulator for face, content, and structural validation training, including the peg transfer module and the soft tissue cutting module, was evaluated. Through subjective and objective evaluations, the potential roles of vision and haptics in robot surgery training were explored. The simulator can effectively distinguish surgical skill proficiency between experts and novices.

Reproducibility challenges in robotic surgery

Reproducibility of results is, in all research fields, the cornerstone of the scientific method and the minimum standard for assessing the value of scientific claims and conclusions drawn by other scientists. It requires a systematic approach and accurate description of the experimental procedure and data analysis, which allows other scientists to follow the steps described in the published work and obtain the “same results.” In general and in different research contexts with “same” results, we mean different things. It can be almost identical measures in a fully deterministic experiment or “validation of a hypothesis” or statistically similar results in a non-deterministic context. Unfortunately, it has been shown by systematic meta-analysis studies that many findings in fields like psychology, sociology, medicine, and economics do not hold up when other researchers try to replicate them. Many scientific fields are experiencing what is generally referred to as a “reproducibility crisis,” which undermines the trust in published results, imposes a thorough revision of the methodology in scientific research, and makes progress difficult. In general, the reproducibility of experiments is not a mainstream practice in artificial intelligence and robotics research. Surgical robotics is no exception. There is a need for developing new tools and putting in place a community effort to allow the transition to more reproducible research and hence faster progress in research. Reproducibility, replicability, and benchmarking (operational procedures for the assessment and comparison of research results) are made more complex for medical robotics and surgical systems, due to patenting, safety, and ethical issues. In this review paper, we selected 10 relevant published manuscripts on surgical robotics to analyze their clinical applicability and underline the problems related to reproducibility of the reported experiments, with the aim of finding possible solutions to the challenges that limit the translation of many scientific research studies into real-world applications and slow down research progress.

Global trends and hotspots in research of robotic surgery in oncology: A bibliometric and visual analysis from 2002 to 2021

BACKGROUND

With the development of robotic surgery in the field of oncology, an increasing number of relevant research papers have been published. In order to explore the research hotspots and trends in this field, a bibliometric and visual analysis was performed for the first time.

METHODS

The literature records related to oncology robotic surgery were obtained from the Web of Science Core Collection database and imported into the software VOSviewer 1.6.18, CiteSpace 6.1.R3, and the Bibliometric Online Analysis Platform for analysis.

RESULTS

A total of 6,964 publications, including 5,635 articles and 1,329 reviews, were included in this study. Over the past 20 years, annual publications and citations have experienced rapid growth, particularly in the last two years. The United States was the country with the most publications, while Yonsei University in South Korea was the most productive institution. The Journal of Robotic Surgery and the Journal of Urology were the journals with the most publications and citations, respectively. Mottrie A from Belgium and Ficarra V from Italy were the authors with the highest number of publications and citations, respectively. The keywords "robotic surgical procedure", "laparoscopic surgery", "prostate cancer", "colorectal cancer", "gastric cancer", "resection", "complications classification", "open surgery", "transoral robotic surgery", "pathological outcomes", and "robot-assisted surgery" reflect the research hotspots and trends of oncology robotic surgery.

CONCLUSION

The therapeutic advantages of robotic surgery in oncology are not yet prominent, and further randomized controlled trials with multicenter and large samples are needed to evaluate the advantages of robotic surgery compared with laparoscopic surgery and open surgery in the treatment of tumors from multiple outcome indicators.