A Comparison of the Clinical Outcomes in Uterine Cancer Surgery After the Introduction of Robotic-Assisted Surgery

The Utilization of e-Health in Lymphedema Care: A Narrative Review

Background: Electronic health (e-Health), refers to technologies that can be utilized to enhance patient care as well as collect and share health information. e-Health comprises several umbrella terms, including telehealth, mobile health, e-Health, wearables, and artificial intelligence. The types of e-Health technologies being utilized in lymphedema (LE) care are unknown. Method: In this narrative review, a search of published research on the utilization of e-Health technologies in LE-related care was conducted. Results: Five different types of e-Health modalities were found (robotics, artificial intelligence, electronic medical records, smart wearable devices, and instructive online information) spanning 14 use cases and 4 phases of care (preventative, diagnostic, assessment, and treatment phases). Broad e-Health utilization examples were found including robotic-assisted surgery to reduce the likelihood of LE after lymphadenectomy, machine learning to predict patients at risk of filarial-related LE, and a novel wearable device prototype designed to provide lymphatic drainage. Conclusions: e-Health has reported merit in the prevention, diagnoses, assessment, and treatment of LE with utilization demonstrating cutting edge applicability of e-Health for achieving optimal patient care and outcomes. As technology continues to advance, additional research into the utilization of e-Health in LE care is warranted.

Robotic-assisted surgery for endometrial cancer: a comparison of surgical and oncologic outcomes in patients with low and high BMI at an Indian tertiary care center

The robotic-assisted surgery for endometrial cancer (EC) is becoming increasingly important, owing to the superior surgical outcomes. However, efficacy data from India is limited, particularly for older women who are obese. We undertook this study to compare the surgical outcomes of robotic-assisted surgery among Indian EC patients with a BMI of < 30 and ≥ 30 kg/m2. A retrospective chart review was conducted for the period of May 2016 to October 2020. Data on patient demographics, medical history, clinical characteristics, and perioperative outcomes were collected by a single senior surgeon, followed by statistical analysis. A total of 99 patients; 39 in the BMI group < 30 and 60 in the BMI group ≥ 30 kg/m2 were included in the study. The mean age of the BMI groups < 30 and ≥ 30 kg/m2 was 60.92 ± 10.43 and 58.90 ± 8.52 years respectively (P = 0.2944). The mean total operating time was slightly higher in the BMI group < 30 kg/m2 (P = 0.8552) but the difference was not statistically significant. Similarly, the mean blood loss (P = 0.2041), length of hospital stays (P = 0.6564), early (P = 0.7758) and delayed complications (P = 0.1878) were less in the BMI group < 30 kg/m2 but the difference was not statistically significant either. At a median follow-up of 22.3 months, the number of recurrences (5.13% vs 3.33%) and deaths (2.56% vs 1.67%) were more in BMI < 30 kg/m2 group. Our study suggests that obese older women predisposed to multiple medical co-morbidities and surgical complications would especially benefit from robotic-assisted technology regardless of their BMI.

Robot-Assisted Surgery in the Treatment of Gynecological Carcinoma and Malignancies: Introduction to the da Vinci Robotic Surgery System

Robotic surgery is a surgical intervention that was developed from traditional manual surgeries because of the intrusive procedures it uses. It is now accomplished in hospitals worldwide, and comprehensive programs for the application of technology in the management of gynecological cancer are being developed. Robotic surgery should be straightforwardly compared with manual and traditional laparoscopy to see if the higher indirect costs are justified by some improvements in patient studies. This paper aims to evaluate the procedure of robotic surgery and its implementation in gynecological cancer to verify its safeness, practicability, and effectiveness. A higher chance of infections is usually in classical surgery, particularly in comparison to laparoscopic or robotic surgery. Surgical and hospital stay are much less with any of these new technologies than the aforementioned; however, the drawbacks are the scarcity of robot systems, their high price, and the realization that it is only appropriate in learning institutions with infrastructure and highly skilled surgeons. In conclusion, tissue engineering constitutes a significant discovery and approach for treating gynecological cancer with improved methods than some other types of traditional surgery, and it will likely become dominant technology shortly.

Artificial intelligence and lymphedema: State of the art

Background

Lymphedema practice is facing many challenges. Some of these challenges include eradication of tropical lymphedema, preclinical diagnosis of cancer-related lymphedema, and delivery of appropriate individualized care. The past two decades have witnessed an increasing implementation of artificial intelligence (AI) in health-care services. The nature of the challenges facing the lymphedema practice is suitable for AI applications.

Aim

The aim of this study was to explore the current AI applications in lymphedema prevention, diagnosis, and management and investigate the potential future applications.

Methods and Results

Four databases were searched: PubMed, Scopus, Web of Science, and EMBASE. We used the Preferred Reporting Items for Systematic Reviews and Meta-Analysis as our basis of organization. Our analysis showed that several domains of AI, including machine learning (ML), fuzzy models, deep learning, and robotics, were successfully implemented in lymphedema practice. ML can guide the eradication campaigns of tropical lymphedema by estimating disease prevalence and mapping the risk areas. Robotic-assisted surgery for gynecological cancer was associated with a lower risk for the lower limb lymphedema. Several feasible models were described for the early detection and diagnosis of lymphedema. The proposed models are more accurate, sensitive, and specific than current methods in practice. ML was also used to guide and monitor patients during the rehabilitation exercises.

Conclusion

AI offers a variety of solutions to the most challenging problems in lymphedema practice. Further, implementation into the practice can revolutionize many aspects of lymphedema prevention, diagnosis, and management.

Relevance to Patients

Lymphedema is a chronic debilitating disease that is affecting millions of patients. Developing new modalities for prevention, early diagnosis, and treatment are critical to improve the outcomes. AI offers a variety of solutions for some of the complexities of lymphedema management. In this systematic review, we summarize and discuss the latest AI advances in lymphedema practice.

A prospective observational study assessing the feasibility and factors affecting same-day discharge in patients undergoing robotic-assisted surgery for gynecological cancers

Although robotic-assisted surgery is being increasingly used in the management of gynecologic cancers, most surgeons discharge patients on the next day of surgery citing concerns about immediate post-operative complications. Present study was conducted to evaluate the safety, factors influencing and quality of life for gynaecological cancer patients undergoing same-day discharge after robotic-assisted surgery. This is single institutional prospective observational study as pragmatic cohort including all well-selected gynecological cancer patients undergoing robotic-assisted surgery from September 2017 to June 2019. Patients were divided into two study groups [Same-day discharge (SDD) group vs. Next-day discharge (NDD) group] according to day of discharge. The entire cohort included 152 patients (38 in SDD group and 114 in NDD group). The difference between both SDD vs. NDD was significant for parameters including Age ≥ 70 years (0% vs. 18.4%, p: 0.010); Operative time > 60 min (39.5% vs. 60.5%, p: 0.024); patients with third-party insurance covering surgery (2.6% vs. 25.4%, p: 0.005) and place of residence ≥ 60 km from hospital (13.1% vs. 51.8%, p: < 0.0001). The quality of life was similar in both groups and none of the patients required readmission or emergency room visits. Same-day discharge after robot-assisted surgery in gynecologic cancer patients is a safe and feasible option. Younger patients, short surgical time, surgery early in the day, no claim for third-party insurance, residing nearby hospital within 60 km radius were influencing factors favouring same-day discharge.

Comparative Survival Outcome of Robot-Assisted Staging Surgery Using Three Robotic Arms versus Open Surgery for Endometrial Cancer

PURPOSE

There is lack of data on direct comparison of survival outcomes between open surgery and robot-assisted staging surgery (RSS) using three robotic arms for endometrial cancer. The purpose of this study was to compare the overall survival (OS) and disease-free survival (DFS) between open surgery and RSS using three robotic arms for endometrial cancer.

MATERIALS AND METHODS

Consecutive women with endometrial cancer who underwent surgery between May 2006 and May 2018 were identified. Robotic procedures were performed using the da Vinci robotic system, and the robotic approach consisted of three robotic arms including a camera arm. Propensity score matching, as well as univariate and multivariate Cox regression of OS and DFS were performed according to clinicopathologic data and surgical method.

RESULTS

The study cohort included 423 unselected patients with endometrial cancer, of whom 218 underwent open surgery and 205 underwent RSS using three robotic arms. Propensity score-matched cohorts of 146 women in each surgical group showed no significant differences in survival: 5-year OS of 91% vs. 92% and DFS of 86% vs. 89% in the open and robotic cohorts, respectively (hazard ratio, 1.02; 95% confidence interval, 0.82-1.67). In the univariate analysis with OS as the endpoint, surgical method, age, stage, type II histology, grade, and lymph node metastasis were independently associated with survival. Surgical stage, grade, and type II histology were found to be significant independent predictors for OS in the multivariate analysis.

CONCLUSION

RSS using three robotic arms and laparotomy for endometrial carcinoma had comparable survival outcomes.

Long-Term Morbidity after Endometrial Cancer Surgery: a Comparison of Open vs. Robotic Approach

This retrospective study is looking into the long-term morbidity after endometrial cancer staging surgery and compares the long-term morbidity of patients who underwent open staging surgery vs. robotic approach. One hundred twenty-nine patients who underwent staging surgery for endometrial cancer from January 2014 until June 2017 were included in the analysis. Morbidities occurring 1 month after surgery-vault complications, incisional hernias, vault dehiscence, and lymphedema-were looked into. There were no statistically significant differences between the long-term complications in both groups (vault infection 5.1% vs. 1.4%, vaginal cuff dehiscence 1.6% vs. 0%, incisional hernia 6.8% vs. 0%, and lymphedema 11.8% vs. 10% in open vs robotic groups respectively). But as far as clinical significance was concerned, patients who underwent robotic staging surgery had a significant decrease in vaginal cuff complications and incisional hernia. Our study shows that robotic-assisted surgery can reduce even long-term morbidity in patients undergoing surgery for endometrial cancer.