Safe Implementation of a Next-Generation Surgical Robot: First Analysis of 2,083 Cases in the Versius Surgical Registry.

OBJECTIVE: To present the first report of data from the Versius Surgical Registry, a prospective, multicenter data registry with ongoing collection across numerous surgical indications, developed to accompany the Versius Robotic Surgical System into clinical practice. BACKGROUND: A data registry can be utilized to minimize risk to patients by establishing the safety and effectiveness of innovative medical devices and generating a thorough evidence base of real-world data. METHODS: Surgical outcome data were collected and inputted through a secure online platform. Preoperative data included patient age, sex, body mass index, surgical history, and planned procedures. Intraoperative data included operative time, complications during surgery, conversion from robot-assisted surgery to an alternative surgical technique, and blood loss. Postoperative outcome data included length of hospital stay, complications following surgery, serious adverse events, return to the operating room, readmission to the hospital, and mortality within 90 days of surgery. RESULTS: This registry analysis included 2083 cases spanning general, colorectal, hernia, gynecologic, urological, and thoracic indications. A considerable number of cases were recorded for cholecystectomy (n=539), anterior resection (n=162), and total laparoscopic hysterocolpectomy (n=324) procedures. The rates of conversion to an alternative technique, serious adverse events, and 90-day mortality were low for all procedures across all surgical indications. CONCLUSIONS: We report the large-scale analysis of the first 2083 cases recorded in this surgical registry, with substantial data collected for cholecystectomies, anterior resections, and total laparoscopic hysterectomies. The extensive surgical outcome data reported here provide real-world evidence for the safe implementation of the surgical robot into clinical practice.

Safe implementation of surgical innovation: a prospective registry of the Versius Robotic Surgical System.

Objectives: To describe a new, international, prospective surgical registry developed to accompany the clinical implementation of the Versius Robotic Surgical System by accumulating real-world evidence of its safety and effectiveness. Interventions: This robotic surgical system was introduced in 2019 for its first live-human case. With its introduction, cumulative database enrollment was initiated across several surgical specialties, with systematic data collection via a secure online platform. Main outcome measures: Pre-operative data include diagnosis, planned procedure(s), characteristics (age, sex, body mass index and disease status) and surgical history. Peri-operative data include operative time, intra-operative blood loss and use of blood transfusion products, intra-operative complications, conversion to an alternative technique, return to the operating room prior to discharge and length of hospital stay. Complications and mortality within 90 days of surgery are also recorded. Results: The data collected in the registry are analyzed as comparative performance metrics, by meta-analyses or by individual surgeon performance using control method analysis. Continual monitoring of key performance indicators, using various types of analyses and outputs within the registry, have provided meaningful insights that help institutions, teams and individual surgeons to perform most effectively and ensure optimal patient safety. Conclusions: Harnessing the power of large-scale, real-world registry data for routine surveillance of device performance in live-human surgery from first use will enhance the safety and efficacy outcomes of innovative surgical techniques. Data are crucial to driving the evolution of robot-assisted minimal access surgery while minimizing risk to patients. Trial registration number: CTRI/2019/02/017872.

A proof-of-concept model for the identification of the key events in the infection process with specific reference to Pseudomonas aeruginosa in corneal infections.

BACKGROUND: It is a common medical practice to characterise an infection based on the causative agent and to adopt therapeutic and prevention strategies targeting the agent itself. However, from an epidemiological perspective, exposure to a microbe can be harmless to a host as a result of low-level exposure or due to host immune response, with opportunistic infection only occurring as a result of changes in the host, pathogen, or surrounding environment. METHODS: We have attempted to review systematically the key host, pathogen, and environmental factors that may significantly impact clinical outcomes of exposure to a pathogen, using Pseudomonas aeruginosa eye infection as a case study. RESULTS AND DISCUSSION: Extended contact lens wearing and compromised hygiene may predispose users to microbial keratitis, which can be a severe and vision-threatening infection. P. aeruginosa has a wide array of virulence-associated genes and sensing systems to initiate and maintain cell populations at the corneal surface and beyond. We have adapted the well-known concept of the epidemiological triangle in combination with the classic risk assessment framework (hazard identification, characterisation, and exposure) to develop a conceptual pathway-based model that demonstrates the overlapping relationships between the host, the pathogen, and the environment; and to illustrate the key events in P. aeruginosa eye infection. CONCLUSION: This strategy differs from traditional approaches that consider potential risk factors in isolation, and hopefully will aid the identification of data and models to inform preventive and therapeutic measures in addition to risk assessment. Furthermore, this may facilitate the identification of knowledge gaps to direct research in areas of greatest impact to avert or mitigate adverse outcomes of infection.

Development of a self-regulated dynamic model for the propagation of Salmonella Typhimurium in pig farms.

A self-regulated epidemic model was developed to describe the dynamics of Salmonella Typhimurium in pig farms and predict the prevalence of different risk groups at slaughter age. The model was focused at the compartment level of the pig farms and it included two syndromes, a high and a low propagation syndrome. These two syndromes generated two different classes of pigs, the High Infectious and the Low Infectious, respectively, which have different shedding patterns. Given the two different classes and syndromes, the Infectious Equivalent concept was used, which reflected the combination of High and Low Infectious pigs needed for the high propagation syndrome to be triggered. Using the above information a new algorithm was developed that decides, depending on the Infectious Equivalent, which of the two syndromes should be triggered. Results showed that the transmission rate of S. Typhimurium for the low propagation syndrome is around 0.115, pigs in Low Infectious class contribute to the transmission of the infection by 0.61-0.80 of pigs in High Infectious class and that the Infectious Equivalent should be above 10-14% of the population in order for the high propagation syndrome to be triggered. This self-regulated dynamic model can predict the prevalence of the classes and the risk groups of pigs at slaughter age for different starting conditions of infection.

Development and application of a stochastic epidemic model for the transmission of Salmonella Typhimurium at the farm level of the pork production chain.

In previous work a deterministic model for the compartment level was built, taking into account the two different syndromes with which Salmonella Typhimurium appears at pig farms. Based on this model, a stochastic one was built in this work that simulated different compartmental sizes, taking into account compartments of 200 to 400 pigs. Multiple scenarios of starting conditions of infection (SCI) ranging from 0.25 to 100% were tested for each population size. The effect of each of these two factors on the probability of disease extinctions and the prevalence of each of the classes of the model and the risk groups of pigs were estimated. The results showed that the compartment population had an inverse effect on the probability of disease extinction. On the other hand, low SCI resulted in high levels of early extinctions reaching 45%, while higher SCI led to high levels of late extinctions. Early extinctions resulted in the absence of the pathogen from the compartment, while late extinctions did not assure it. This effect shows that reducing the population of the compartment combined with appropriate cleaning and good farming practices could have a positive effect in the reduction of the risk of introducing S. Typhimurium into the slaughtering procedure. On the other hand, the profile of seroprevalence at slaughter age allows for risk characterization of the farm, given the relative stability and the small variation for higher SCI.

Estimation of prevalence of Salmonella on pig carcasses and pork joints, using a quantitative risk assessment model aided by meta-analysis.

This risk assessment study aimed to estimate the prevalence of Salmonella on pig carcasses and pork joints produced in slaughterhouses, on the basis that within groups of slaughter there is a strong association between the proportion of Salmonella-positive animals entering the slaughter lines (x) and the resulting proportion of contaminated eviscerated pig carcasses (y). To this effect, the results of a number of published studies reporting estimates of x and y were assembled in order to model a stochastic weighted regression considering the sensitivities of the diverse Salmonella culture methods. Meta-analysis was used to assign weights to the regression and to estimate the overall effect of chilling on Salmonella incidence on pig carcasses. The model's ability to produce accurate estimates and the intrinsic effectiveness of the modeling capabilities of meta-analysis were appraised using Irish data for the input parameter of prevalence of Salmonella carrier slaughter pigs. The model approximated a Salmonella prevalence in pork joints from Irish boning halls of 4.0% (95% confidence interval, 0.3 to 12.0%) and was validated by the results of a large survey (n = 720) of Salmonella in pork joints (mean, 3.3%; 95% confidence interval, 2.0 to 4.6%) carried out in four commercial pork abattoirs as part of this research project. Sensitivity analysis reinforced the importance of final rinsing (r = -0.382) and chilling (r = -0.221) as stages that contribute to reducing considerably the occurrence of Salmonella on the final product, while hygiene practices during jointing seemed to moderate only marginally the amount of contaminated pork joints. Finally, the adequacy of meta-analysis for integrating different findings and producing distributions for use in stochastic modeling was demonstrated.

An appraisal of the use of meat-juice serology monitoring data for estimating prevalence of cecal Salmonella carriage of pigs at slaughter by means of herd-level and animal-level simulation.

Some attempts have been made to elucidate the association between positive serology and Salmonella detection by bacterial culture in individual pigs and pig herds. This study aimed to appraise whether the existing knowledge on such association provides grounds for the utilization of serology monitoring data for predicting Salmonella subclinical infection of pigs entering the abattoir. Serology test results of pig carcasses (taken at abattoirs) originating from 436 representative active herds in Ireland were utilized to estimate the overall cecal Salmonella carriage of Irish slaughter pigs. To this effect, two separate simulations were conducted using (i) herd-level regression data and (ii) animal-level sensitivity (0.2890) and specificity (0.8895) data, which were extracted from published articles. The herd-level approach estimated a moderate prevalence of cecal Salmonella carriage of 0.222 (sigma = 0.094; 95% confidence interval [CI]: 0.069 to 0.431), which matched closely the mean prevalence value from the surveys' validation data of Salmonella-positive cecal samples (n = 1,098) obtained at Irish abattoirs (0.215; 95% CI: 0.192 to 0.240). The animal-level simulation generated an output distribution with slightly more uncertainty (sigma = 0.102 and 95% CI: 0.146 to 0.537) and a higher estimate of cecal carriage (0.312), which was an effect of the low relative sensitivity of serology, common under field conditions. While the herd-level simulation appeared to be technically more appropriate, since its correlation is only moderate, further elucidation of other factors related to subclinical infection should be attained for their incorporation in prospective dynamic on-farm models, which would be useful in the ultimate goal of estimating the risk of carcass contamination during slaughter.