Multi-Institutional Trends in Gynecological Robotic Surgery in India: A Real-World Scenario

Abstract

Background Robot-assisted laparoscopic surgery in gynecology has grown exponentially compared to laparoscopic surgery. The probable reasons for the increased uptake of robotics are a shorter learning curve, three-dimensional vision, and increased dexterity compared to laparoscopic surgery, and precise surgery as compared to open surgery. This study compares the time trends of various parameters in robotic gynecological surgery in India over a decade. Material and methods In India, a retrospective analysis of all robot-assisted laparoscopic surgery for gynecologic diseases in five tertiary care hospitals was conducted between July 2011 and June 2021. Data were collected regarding demographic profiles, clinical and disease characteristics, and indications for surgery. Details related to surgery were collected, such as the number of ports, console and docking time, the procedure performed, total operative time, average blood loss, blood transfusion, and length of hospital stay. All the parameters collected were grouped into five years, and a comparison was made between the first five years (2011-2015) and the second five years (2016-2021). Statistical analysis, including descriptive statistics and trend analysis, was performed. Results During the 10 years, the total number of cases included was 1,501, out of which 764 were benign cases and 737 were pre-malignant/malignant cases. The common indications were uterine leiomyoma (31.2%) and carcinoma endometrium (28%). The mean age for benign cases was significantly lower than that for malignant cases (40.84 years and 55.42 years, respectively). Mean blood loss was significantly lower for benign indications (97.48 mL) than for oncological surgery (184.67 mL) and needed fewer transfusions. The mean length of stay (LOS) for benign (2.07 days) and malignant/ pre-malignant cases (2.32 days) and the mean BMI for benign (28.40) and for oncological patients (28.47) were similar in both groups. The docking time reduced significantly in the last five years. Conclusion The current retrospective study demonstrates an increasing uptake of robotic technology in gynecological surgery in India. Of the total cohort of cases, 70.9% of patients underwent gynecological robotic surgery in the last five years. A burst of adaptability happened for malignant cases in 2017 and benign cases in 2018, probably due to the increased availability of robotic platforms and improved awareness of technology and training among medical professionals. The number of cases has grown exponentially over the last five years in both benign and malignant/ pre-malignant scenarios; however, there has been a downward trend in the robotic surgery performed in the previous couple of years due to the uncertainty of the COVID pandemic.

Keywords: gynecological surgery; india; minimally invasive surgery; robotic-assisted surgery; trend analysis.

Figure 1. Trend shows the year-wise distribution of robot-assisted laparoscopy surgery for both benign and malignant/ pre-malignant cases in gynecology.

Blue line indicates trend of total gynecological cases that underwent robot-assisted laparoscopic surgery. Orange line indicates trend of benign gynecological cases that underwent robot-assisted laparoscopic surgery. Gray line indicates trend of malignant gynecological cases that underwent robot-assisted laparoscopic surgery.

Figure 2. Bar diagram showing benign and malignant/pre-malignant cases operated on during the first five years versus the last five years of study.

Total benign gynecological cases operated by robotic platform (blue) in the first five years were 240 and that in the last five years were 510 cases. Total malignant gynecological cases operated by robotic platform (green) in the first five years were 192  and that in the last five years were 559 cases.

Figure 3. The bar diagram showing the comparison between the mean console time (in minutes) for malignant/pre-malignant and benign gynecological cases operated during 2011 to 2015 and 2016 to 2021.