Impact of Operative Room Noise on Laparoscopic Performance - A Prospective, Randomized Crossover Trial

INTRODUCTION

Surgeons are often exposed to different types of operative room (OR) noise, for instance machine alarms, phone calls, and interacting objects. The aim of this study was to evaluate the effect of OR noise on the surgeons' laparoscopic performance.

METHODS

A total of 30 laparoscopic novices participated in this single-center, prospective, randomized cross-over trial after completing a standardized laparoscopic training until reaching proficiency. Afterward, all participants performed four different laparoscopic tasks (peg transfer, circle cutting, balloon resection, suture, and knot) twice, once under noise exposure (intervention group), and once without any noise (control group). Primary endpoints were the force exertion and motion analyses. To assess the psychological workload the NASA task load index score was used.

RESULTS

The error rates varied and were significantly different between the noise and the control group. More complex tasks like the circle cutting and suture and knot task revealed higher error rates concerning precision (circle cutting: P < 0.01; suture and knot: P < 0.01). In line with increased error rates in the circle cutting task, increased NASA task load index scores were observed in this task (P = 0.03). However, no significant differences were found in force parameters, such as the maximal force exertion (peg transfer: P = 0.43; circle cutting: P = 0.54; balloon resection: P = 0.64; suture and knot: P = 0.63) and the mean force exertion (peg transfer: P = 0.43; circle cutting: P = 0.54; balloon resection: P = 0.64; suture and knot: P = 0.63) between the groups.

CONCLUSIONS

Exposure to normal OR noise led to higher error rates in two of four tasks. This effect could be linked to an increased psychological workload that was present under normal OR noise exposure. However, normal OR noise does not appear to impact surgical novices' laparoscopic task performance regarding applied forces and instrument motion.

Evaluation of objective tools and artificial intelligence in robotic surgery technical skills assessment: a systematic review

BACKGROUND

There is a need to standardize training in robotic surgery, including objective assessment for accreditation. This systematic review aimed to identify objective tools for technical skills assessment, providing evaluation statuses to guide research and inform implementation into training curricula.

METHODS

A systematic literature search was conducted in accordance with the PRISMA guidelines. Ovid Embase/Medline, PubMed and Web of Science were searched. Inclusion criterion: robotic surgery technical skills tools. Exclusion criteria: non-technical, laparoscopy or open skills only. Manual tools and automated performance metrics (APMs) were analysed using Messick's concept of validity and the Oxford Centre of Evidence-Based Medicine (OCEBM) Levels of Evidence and Recommendation (LoR). A bespoke tool analysed artificial intelligence (AI) studies. The Modified Downs-Black checklist was used to assess risk of bias.

RESULTS

Two hundred and forty-seven studies were analysed, identifying: 8 global rating scales, 26 procedure-/task-specific tools, 3 main error-based methods, 10 simulators, 28 studies analysing APMs and 53 AI studies. Global Evaluative Assessment of Robotic Skills and the da Vinci Skills Simulator were the most evaluated tools at LoR 1 (OCEBM). Three procedure-specific tools, 3 error-based methods and 1 non-simulator APMs reached LoR 2. AI models estimated outcomes (skill or clinical), demonstrating superior accuracy rates in the laboratory with 60 per cent of methods reporting accuracies over 90 per cent, compared to real surgery ranging from 67 to 100 per cent.

CONCLUSIONS

Manual and automated assessment tools for robotic surgery are not well validated and require further evaluation before use in accreditation processes.PROSPERO: registration ID CRD42022304901.

Craniotomy Simulator with Force Myography and Machine Learning-Based Skills Assessment

Craniotomy is a fundamental component of neurosurgery that involves the removal of the skull bone flap. Simulation-based training of craniotomy is an efficient method to develop competent skills outside the operating room. Traditionally, an expert surgeon evaluates the surgical skills using rating scales, but this method is subjective, time-consuming, and tedious. Accordingly, the objective of the present study was to develop an anatomically accurate craniotomy simulator with realistic haptic feedback and objective evaluation of surgical skills. A CT scan segmentation-based craniotomy simulator with two bone flaps for drilling task was developed using 3D printed bone matrix material. Force myography (FMG) and machine learning were used to automatically evaluate the surgical skills. Twenty-two neurosurgeons participated in this study, including novices (n = 8), intermediates (n = 8), and experts (n = 6), and they performed the defined drilling experiments. They provided feedback on the effectiveness of the simulator using a Likert scale questionnaire on a scale ranging from 1 to 10. The data acquired from the FMG band was used to classify the surgical expertise into novice, intermediate and expert categories. The study employed naïve Bayes, linear discriminant (LDA), support vector machine (SVM), and decision tree (DT) classifiers with leave one out cross-validation. The neurosurgeons' feedback indicates that the developed simulator was found to be an effective tool to hone drilling skills. In addition, the bone matrix material provided good value in terms of haptic feedback (average score 7.1). For FMG-data-based skills evaluation, we achieved maximum accuracy using the naïve Bayes classifier (90.0 ± 14.8%). DT had a classification accuracy of 86.22 ± 20.8%, LDA had an accuracy of 81.9 ± 23.6%, and SVM had an accuracy of 76.7 ± 32.9%. The findings of this study indicate that materials with comparable biomechanical properties to those of real tissues are more effective for surgical simulation. In addition, force myography and machine learning provide objective and automated assessment of surgical drilling skills.

When Does Da Vanci Robotic Surgical Systems Come Into Play?

The emergent of medical science and technology has risen the minimally invasive surgery. Da Vinci Robotic Surgical Systems (RSS) is the trend at present. Compared with the past surgical methods, many studies related to RSS tend to explore postoperative outcomes and quality of life or compare the advantages and disadvantages than the other surgery. Few studies to understand the patients' willing who use RSS. This study mainly explores the patients' willingness and adopts the Technology Acceptance Model (TAM) as the theoretical foundation, and appended the trust concept to discuss. The study was a retrospective study and used a structured questionnaire to conduct a survey. The subjects included the patients with single-disease who had used RSS in a Medical Center of Southern Taiwan but excluded the patients with multiple disorder. This study conducted SPSS 22.0 and Smart PLS 2.0 software for statistical analysis, which included descriptive statistical analysis and applied Partial Least Squares (PLS) analysis to test the research model and to examine the established hypotheses. A total of 136 cases were collected in this study. Study validation was tested. Trust positively affects Perceived Usefulness (β = 0.550) and Perceived Ease of Use (β = 0.300). Perceived Ease of Use positively affects Perceived Usefulness (β = 0.188). Perceived Usefulness positively affects Attitude Toward Using (β = 0.589. Attitude Toward Using positively affects Behavioral Intention (β = 0.446. The relationship between perceived Ease of Use and Attitude toward Using was insignificant. Additionally, the relationship between Perceived Usefulness and Behavioral Intention was insignificant. In the research results, we found that patients are mostly in the middle and high age groups, and if the patient himself feels that RSS is extremely helpful to his illness, the intensity of his choice of intention will be high. In comparison, the information related to RSS has been clearly known, it does not directly affect the selection intention. According to age, most of the choices of RSS is based on safety and risk considerations, and it is beneficial to the patient himself, but RSS is also more expensive. We recommended that the government consider ββ reimbursing the RSS process in health insurance programs to meet the needs and expectations of patients.

Top 100 most-cited original articles, systematic reviews/meta-analyses in robotic surgery: A scientometric study

The aim of this study was to explore and analyze the main features of the top 100 most-cited original articles, systematic reviews (SRs)/meta-analyses (MAs) in the field of robotic surgery, through scientometric analysis. VOSviewer and Excel 2019 were employed to conduct this scientometric study. We found that the majority of original articles (72/100) were published during the 2000s, while the majority of the top 100 most-cited SRs/MAs (91/100) during the 2010s. The USA was the most dominant country (n = 78), Henry Ford Health System was the most productive institution (n = 10), and Menon M was the largest contributing first author (n = 5) of the top 100 most-cited original articles. The USA was the most dominant country (n = 33), University of Padua was the most productive institution (n = 9), and Ficarra V was the largest contributing first author (n = 4) of the top 100 most-cited SRs/MAs. The top 100 most-cited original articles in robotic surgery have focused on the feasibility, outcomes and learning curve of robotic surgery for various neoplasms and cancers. The top 100 most-cited SRs/MAs have focused on the differences between robotic surgery and other types of surgery, with respect to the learning curve, costs, outcomes and experience in treating neoplasms, cancer and other diseases. In the future, the formation of cross-institutional and cross-disciplinary cooperation teams should be promoted and corresponding regulations and standards for specific diseases should be developed to regulate and promote the development of robotic surgery.

The impact of noise in the operating theatre: a review of the evidence

INTRODUCTION

Noise has been recognised to have a negative impact on performance and wellbeing in many settings. Average noise levels have been found to range between 51dB and 79dB in operating theatres. Despite these levels of noise, there is little research investigating their effect on surgical team functioning.

METHODS

A literature review to look at the impact of noise in the operating theatre was performed on MEDLINE, which included the search terms 'noise' OR 'distraction' AND 'technical skill' OR 'Surgical skill' OR 'Operating Room'. Only 10 of 307 articles identified were deemed relevant.

FINDINGS

Eight of ten studies found noise to be detrimental to communication and surgical performance, particularly regarding total errors and time to task completion. No studies found noise to be beneficial. Two studies found case-irrelevant verbal communication to be a frequent form of noise pollution in operating theatres; this is both perceived by surgeons to be distracting and delays patient care.

CONCLUSION

Noise and irrelevant verbal communications were both found to be harmful to surgical performance, surgeon experience and team functioning.

Effects of Flow Disruptions on Mental Workload and Surgical Performance in Robotic-Assisted Surgery

BACKGROUND

Robotic systems introduced new surgical and technical demands. Surgical flow disruptions are critical for maintaining operating room (OR) teamwork and patient safety. Specifically for robotic surgery, effects of intra-operative disruptive events for OR professionals' workload, stress, and performance have not been investigated yet. This study aimed to identify flow disruptions and assess their association with mental workload and performance during robotic-assisted surgery.

METHODS

Structured expert-observations to identify different disruption types during 40 robotic-assisted radical prostatectomies were conducted. Additionally, 216 postoperative reports on mental workload (mental demands, situational stress, and distractions) and performance of all OR professionals were collected.

RESULTS

On average 15.8 flow disruptions per hour were observed with the highest rate after abdominal insufflation and before console time. People entering the OR caused most flow disruptions. Disruptions due to equipment showed the highest severity of interruption. Workload significantly correlated with severity of disruptions due to coordination and communication.

CONCLUSIONS

Flow disruptions occur frequently and are associated with increased workload. Therefore, strategies are needed to manage disruptions to maintain OR teamwork and safety during robotic-assisted surgery.