We developed and externally validated a machine-learning model integrating maternal risk modifiers with fetal biometry for prediction of shoulder dystocia (ShD). The model was significantly more accurate than was prediction based on estimated fetal weight either alone or combined with maternal diabetes and was able to stratify the risk of ShD and neonatal injury in the context of suspected macrosomia. What are the clinical implications of this work? We demonstrated the potential clinical efficacy of applying this model to stratify the risk of ShD and related newborn injury among women carrying a fetus with estimated fetal weight ≥ 4000 g.

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Highlights Detection of uncommon sentinel lymph nodes (SLN) was related to lower BMI and the use of Tc 99 &blue dye or ICG. Detection of SLN in the para -aortic, parametrium and pre-sacral regions was related to recent surgical year. Detection of SLN in the para -aortic, parametrium and pre-sacral regions was also related to the presence of positive nodes. It seems that surgical parameters as opposed to tumor characteristics are the main predictors for uncommon SLN.

We aimed to identify the trends and patterns of robotic surgery research in obstetrics and gynecology since its implementation. We used data from Clarivate’s Web of Science platform to identify all articles published on robotic surgery in obstetrics and gynecology. A total of 838 publications were included in the analysis. Of these, 485 (57.9%) were from North America and 281 (26.0%) from Europe. 788 (94.0%) articles originated in high-income countries and none from low-income countries. The number of publications per year reached a peak of 69 articles in 2014. The subject of 344 (41.1%) of articles was gynecologic oncology, followed by benign gynecology (n = 176, 21.0%) and urogynecology (n = 156, 18.6%). Articles discussing gynecologic oncology had lower representation in low- and middle-income countries (LMIC) (32.0% vs. 41.6%, p < 0.001) compared with high income countries. After 2015 there has been a higher representation of publications from Asia (19.7% vs. 7.7%) and from LMIC (8.4% vs. 2.6%), compared to the preceding years. In a multivariable regression analysis, journal’s impact factor [aOR 95% CI 1.30 (1.16–1.41)], gynecologic oncology subject [aOR 95% CI 1.73 (1.06–2.81)] and randomized controlled trials [aOR 95% CI 3.67 (1.47–9.16)] were associated with higher number of citations per year. In conclusion, robotic surgery research in obstetrics & gynecology is dominated by research in gynecologic oncology and reached a peak nearly a decade ago. The disparity in the quantity and quality of robotic research between high income countries and LMIC raises concerns regarding the access of the latter to high quality healthcare resources such as robotic surgery.