Robotic vs. Conventional Laparoscopy for Treating Deep Endometriosis

In a recent study published in the journal JCM, researchers comprehensively compared the efficacy of two minimally invasive surgical techniques for treating deep endometriosis: conventional laparoscopy (CL) and robotic-assisted laparoscopy (RAL). They aimed to evaluate the perioperative and postoperative outcomes of both techniques in a sample of Mexican patients with deep endometriosis.

Conventional vs Robotic Laparoscopy for Endometriosis
Study: Robotic Surgery vs. Laparoscopy for Endometriosis. Image Credit: Peter Porrini/Shutterstock.com

Background

Minimally invasive surgery has several benefits over open surgery for the treatment of endometriosis, such as lower rates of complications, infection, and pain, and shorter hospital stays.

Endometriosis is a chronic condition affecting millions of women worldwide, causing pelvic pain, infertility, and reduced quality of life. It occurs when endometrial tissue, which typically lines the uterus, grows outside the uterine cavity, forming lesions that can invade organs such as the bladder, ureters, and rectum. This is known as deep endometriosis, and it requires surgical treatment to remove the affected tissues and restore normal function.

CL uses small incisions and a camera to guide the surgeon’s instruments, while RAL employs a robotic system to enhance the surgeon’s vision, precision, and dexterity. CL has limitations, including a two-dimensional view, limited range of motion, hand tremors, and ergonomic challenges for the surgeon. RAL addresses these limitations by providing a three-dimensional view, increased range of motion, tremor filtering, and improved ergonomics. However, RAL is associated with higher costs, longer operative times, and a learning curve.

Previous studies have compared CL and RAL for the treatment of endometriosis, but the results were inconsistent and controversial. Some studies report better outcomes with RAL in terms of blood loss, pain, and complications, while others show no significant difference or even worse outcomes with RAL. Most of these studies have been conducted in developed countries where RAL is more widely available. Therefore, there is a lack of evidence on the use and efficacy of RAL for endometriosis treatment in developing countries, where RAL is less common and more expensive.

About the Research

In this paper, the authors conducted a comparative study including 93 patients diagnosed with endometriosis and treated with either CL or RAL minimally invasive surgery between March 2015 and August 2023 at a tertiary hospital in Mexico City. The hospital’s surgical orientation committee determined the type of surgery, considering the patient’s comorbidities, abdominal surgical history, and endometriosis severity.

The researchers used the endometriosis infiltrating the rectovaginal septum, uterosacral ligaments, vagina, and/or bowel (ENZIAN) classification to grade the depth and location of endometriosis lesions. Other factors considered included age, body mass index (BMI), previous medical treatment, and extrauterine locations of endometriosis.

The study evaluated several key outcomes including operative time, blood loss, postoperative length of stay, postoperative pain, and perioperative complications. It also analyzed correlations between these outcomes and factors such as the ENZIAN classification, the Charlson Comorbidity Index, and BMI. Statistical tests were used to compare outcomes between the CL and RAL groups and to assess the significance of correlations.

Research Findings

The RAL group presented a significantly higher BMI compared to the CL group, but the groups remained similar in terms of age, comorbidities, ENZIAN classification, previous medical treatment, and extrauterine location of endometriosis. No significant difference was shown in operative time or blood loss between the two groups, although the RAL group experienced a longer operative time and less blood loss than the CL group.

However, a significant difference was found in postoperative length of stay and postoperative pain, with the RAL group having a shorter stay and less pain than the CL group. There was no significant difference in perioperative complications between the two groups, although the CL group had one case of conversion to open surgery and the RAL group had three cases of surgical injuries.

The researchers also found that operative time was significantly correlated with blood loss and hospitalization length in both groups, but not with the ENZIAN classification or the Charlson Comorbidity Index. Additionally, hospitalization length was significantly correlated with blood loss in both groups and with BMI only in the CL group.

Conclusion

In summary, both RAL and CL proved effective for treating endometriosis in Mexican patients. RAL showed benefits over CL with less postoperative pain and shorter hospital stays, improving quality of life and reducing healthcare costs. Moving forward, the researchers recommended long-term studies to compare both techniques and assess RAL's impact on endometriosis recurrence and fertility. They also emphasized the need for more evidence on RAL's use and effectiveness in developing countries, where it is less available and more expensive.

Journal Reference

Bandala, C.; Cifuentes-Chacón, J.P.; Cortes-Vázquez, A.; Ruz-Barros, R.; Garrocho-Hernández, L.; Cortes-Algara, A. Efficacy between Conventional Laparoscopy and Robotic Surgery in Mexican Patients with Endometriosis: A Comparative Study. J. Clin. Med. 2024, 13, 3576. https://doi.org/10.3390/jcm13123576, https://www.mdpi.com/2077-0383/13/12/3576

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Article Revisions

  • Jun 25 2024 - Title changed from "Conventional vs Robotic Laparoscopy for Endometriosis" to "Robotic vs. Conventional Laparoscopy for Treating Deep Endometriosis"
Muhammad Osama

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Muhammad Osama

Muhammad Osama is a full-time data analytics consultant and freelance technical writer based in Delhi, India. He specializes in transforming complex technical concepts into accessible content. He has a Bachelor of Technology in Mechanical Engineering with specialization in AI & Robotics from Galgotias University, India, and he has extensive experience in technical content writing, data science and analytics, and artificial intelligence.

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