The aim of this study was to explore and analyze the main features of the top 100 most-cited original articles, systematic reviews (SRs)/meta-analyses (MAs) in the field of robotic surgery, through scientometric analysis. VOSviewer and Excel 2019 were employed to conduct this scientometric study. We found that the majority of original articles (72/100) were published during the 2000s, while the majority of the top 100 most-cited SRs/MAs (91/100) during the 2010s. The USA was the most dominant country (n = 78), Henry Ford Health System was the most productive institution (n = 10), and Menon M was the largest contributing first author (n = 5) of the top 100 most-cited original articles. The USA was the most dominant country (n = 33), University of Padua was the most productive institution (n = 9), and Ficarra V was the largest contributing first author (n = 4) of the top 100 most-cited SRs/MAs. The top 100 most cited original articles in robotic surgery have focused on the feasibility, outcomes and learning curve of robotic surgery for various neoplasms and cancers. The top 100 most-cited SRs/MAs have focused on the differences between robotic surgery and other types of surgery, with respect to the learning curve, costs, outcomes and experience in treating neoplasms, cancer and other diseases. In the future, the formation of cross-institutional and cross-disciplinary cooperation teams should be promoted and corresponding regulations and standards for specific diseases should be developed to regulate and promote the development of robotic surgery. (c) 2021 Asian Surgical Association and Taiwan Robotic Surgery Association. Publishing services by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by-nc-nd/4.0/).

Background: Soluble urokinase-type plasminogen activator receptor (suPAR) has the potential to diagnose infectious diseases. Due to the lack of reliable biomarkers and the importance of timely diagnosis for sepsis treatment, we conducted this systematic review and meta-analysis to evaluate the value of suPAR diagnosis and prognosis for sepsis. Methods: PubMed, Embase, Web of Science, and Cochrane Library databases were searched for studies, which reported the value of suPAR diagnosis and/or prognosis in patients with sepsis. Results: A total of 30 studies involving 6,906 patients were included. Sensitivity and specificity of suPAR for diagnosing sepsis were 0.76 [95% confidence interval (CI), 0.63-0.86] and 0.78 (95% CI, 0.72-0.83), respectively. The area under the summary receiver-operating characteristic curve (AUC) was 0.83 (95% CI, 0.80-0.86). Pooled sensitivity and specificity for predicting mortality were 0.74 (95% CI, 0.67-0.80) and 0.70 (95% CI, 0.63-0.76), respectively, with AUC of 0.78 (95% CI, 0.74-0.82). In addition, AUC for differentiating sepsis from systemic inflammatory response syndrome (SIRS) was 0.81 (95% CI, 0.77-0.84), and the sensitivity and specificity were 0.67 (95% CI, 0.58-0.76) and 0.82 (95% CI, 0.73-0.88), respectively. Conclusion: suPAR is a feasible biomarker for timely diagnosis and prognosis of sepsis. Compared with effective value of procalcitonin (PCT) identified by previous meta-analysis, suPAR has similar clinical guiding value, whereas suPAR exhibits higher specificity, which can facilitate the deficiencies of PCT. suPAR also shows a diagnostic value in differentiating sepsis from SIRS. Considering the lack of biomarkers for sepsis and the similar clinical value of suPAR and PCT, suPAR should be considered as a biomarker in clinical practice for sepsis.