Assessment of technical skills based on learning curve analyses in laparoscopic surgery training

Cervical cancer is the most common gynecologic malignancy and the fourth most common cancer in women worldwide. Over the last two decades, minimally invasive surgery (MIS) emerged as the mainstay in the surgical management of cervical cancer, bringing advantages such as lower operative morbidity and shorter hospital stay compared to open surgery while maintaining comparable oncologic outcomes in numerous retrospective studies. However, in 2018, a prospective phase III randomized controlled trial, “Laparoscopic Approach to Carcinoma of the Cervix (LACC)”, unexpectedly reported that MIS was associated with a statistically significant poorer overall survival and disease-free survival compared to open surgery in patients with early-stage cervical cancer. Various hypotheses have been raised by the authors to try to explain these results, but the LACC trial was not powered to answer those questions. In this study, through an exhaustive literature review, we wish to explore some of the potential causes that may explain the poorer oncologic outcomes associated with MIS, including the type of MIS surgery, the size of the lesion, the impact of CO2 pneumoperitoneum, prior conization, the use of uterine manipulator, the use of protective measures, and the effect of surgical expertise/learning curve.

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“…The number of cases performed (surgical volume) is one of the factors that unquestionably impact surgical efficiency [ 55 , 56 ].…”

Section: The Effect Of Surgical Expertise/learning Curvementioning

confidence: 99%

Minimally Invasive Surgery for Cervical Cancer in Light of the LACC Trial: What Have We Learned?

Touhami

Plante

2022

Current Oncology

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“…Trials exceeding the time limit were marked as "did not finish" and were excluded from the analysis. The ForceSense system recorded previously validated force-based parameters for the objective assessment of tissue handling skills [11][12][13][14].…”

Section: Main Study Parametersmentioning

confidence: 99%

“…2). The pre-test consisted of two previously validated fundamental laparoscopic skill (FLS) tasks [13][14][15]. Participants completed three trials per task as a baseline assessment.…”

Section: Study Protocolmentioning

confidence: 99%

Validation of the portable virtual reality training system for robotic surgery (PoLaRS): a randomized controlled trial

et al. 2021

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Background As global use of surgical robotic systems is steadily increasing, surgical simulation can be an excellent way for robotic surgeons to acquire and retain their skills in a safe environment. To address the need for training in less wealthy parts of the world, an affordable surgical robot simulator (PoLaRS) was designed. Methods The aim of this pilot study is to compare learning curve data of the PoLaRS prototype with those of Intuitive Surgical’s da Vinci Skills Simulator (dVSS) and to establish face- and construct validity. Medical students were divided into two groups; the test group (n = 18) performing tasks on PoLaRS and dVSS, and the control group (n = 20) only performing tasks on the dVSS. The performance parameters were Time, Path length, and the number of collisions. Afterwards, the test group participants filled in a questionnaire regarding both systems. Results A total of 528 trials executed by 38 participants were measured and included for analyses. The test group significantly improved in Time, Path Length and Collisions during the PoLaRS test phase (P ≤ 0.028). No differences was found between the test group and the control group in the dVSS performances during the post-test phase. Learning curves showed similar shapes between both systems, and between both groups. Participants recognized the potential benefits of simulation training on the PoLaRS system. Conclusions Robotic surgical skills improved during training with PoLaRS. This shows the potential of PoLaRS to become an affordable alternative to current surgical robot simulators. Validation with similar tasks and different expert levels is needed before implementing the training system into robotic training curricula.

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“…A combination of performance parameters has been classified, representing tissue manipulation and instrument handling skills, which enables objective assessment of laparoscopic skills [16]. Our research group reported earlier successful implementation of objective performance parameters in basic laparoscopic skills training of first-year surgical residents, enabling objective assessment of learning curves [17].…”

mentioning

confidence: 99%

“…Objective assessment of the learning curve is essential to determine when proficiency levels have been acquired [17][18][19][20]. It is demonstrated that baseline performances of psychomotor ability uniquely predict the learning curve during laparoscopic skills training with virtual reality simulators [21,22].…”

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confidence: 99%

Prediction of laparoscopic skills: objective learning curve analysis

et al. 2022

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Introduction Prediction of proficiency of laparoscopic skills is essential to establish personalized training programs. Objective assessment of laparoscopic skills has been validated in a laparoscopic box trainer with force, motion and time recognition. The aim of this study is to investigate whether acquiring proficiency of laparoscopic skills can be predicted based on performance in such a training box. Methods Surgical residents in their first year of training performed six different tasks in the Lapron box trainer. Force, motion and time data, three objective measures of tissue manipulation and instrument handling, were collected and analyzed for the six different tasks. Linear regression tests were used to predict the learning curve and the number of repetitions required to reach proficiency. Results A total of 6010 practice sessions performed by 42 trainees from 13 Dutch hospitals were assessed and included for analysis. Proficiency level was determined as a mean result of seven experts performing 42 trials. Learning curve graphs and prediction models for each task were calculated. A significant relationship between force, motion and time during six different tasks and prediction of proficiency was present in 17 out of 18 analyses. Conclusion The learning curve of proficiency of laparoscopic skills can accurately be predicted after three repetitions of six tasks in a training box with force, path length and time recognition. This will facilitate personalized training programs in laparoscopic surgery.

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Assessment of technical skills based on learning curve analyses in laparoscopic surgery training

Cited by 23 publications

References 51 publications

Minimally Invasive Surgery for Cervical Cancer in Light of the LACC Trial: What Have We Learned?

Minimally Invasive Surgery for Cervical Cancer in Light of the LACC Trial: What Have We Learned?

Validation of the portable virtual reality training system for robotic surgery (PoLaRS): a randomized controlled trial

Prediction of laparoscopic skills: objective learning curve analysis

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