Low-fidelity Simulation Model Research Articles

Reducing trainee mistakes. Better performance with changing to a high-fidelity simulation system?

Postpartum hemorrhage is a significant cause of both maternal morbidity and mortality worldwide and is increasing in incidence. This study aimed to assess improvement and identify shortcomings in trainee performance in different simulation systems in the management of postpartum hemorrhage. To perform a pilot study evaluating and comparing high- and low-fidelity simulation models, assessing improvement in repeated performance with high-fidelity mode and identifying mistakes made assessed using Objective Structured Assessment of Technical Skills and thereby exploring what aspects of emergency management of postpartum hemorrhage should be prioritized in teaching settings and assessing what simulation setup is most effective in achieving competence. This was a prospective randomized, single-blinded, single-institution trial in a population of 17 junior obstetrical trainees at the Charité University Hospital Obstetric Simulation Center in Berlin. Trainees were randomized into 2 groups, with either initial low-fidelity simulation or high-fidelity simulation, followed by repeated assessment of performance, using the high-fidelity model simulation system. Individual simulation sessions were video-recorded and transcribed, and the timing of interventions was documented. Strandardized Objective Structured Assessment of Technical Skills forms were used as a checklist for performance. There was a statistically significant general improvement in performance (P=.02; 24.7-27.2 of 31.0 points; average of 8.7%) in the second cycle of simulation assessment and a statistically significant training effect (P=.043; 24.4-28.4 of 31.0 points; average of 12.9%) in the group that underwent repeat simulation assessment from the initial low-fidelity system to the high-fidelity system compared with the group using the same high-fidelity setup (P=.276; 25.0-25.8 of 31.0; average of 2.4%). There was an improvement in the performance when trainees underwent a repeated cycle of simulation assessment changing from a low-fidelity system to a high-fidelity system. Simulation assessment can identify mistakes and learning gaps that are important for obstetrical trainees. This study found that trainees make the same mistakes, regardless of which simulation model was initially used.

Vesicovaginal Fistula Repair Simulation Model and Hierarchical Task Analysis.

There is a need for surgeons skilled in vesicovaginal fistula (VVF) repair, yet training opportunities are limited. This study aimed to create a low-fidelity simulation model for transvaginal VVF repair, identify essential steps of VVF repair, and evaluate the model's ability to replicate essential steps. First, a low-fidelity VVF repair simulation model was designed and built by the authors. Next, a hierarchical task analysis was performed by urogynecologic surgeons with expertise in VVF repair. Each expert submitted an outline of tasks required to perform VVF repair. To control for bias, an education specialist de-identified, reviewed, and collated the submitted outlines. The education specialist then led a focus group, and through a modified Delphi process, the experts reached consensus on the essential steps. A separate group of urogynecologic surgeons then tested the model and completed an anonymous questionnaire assessing how well the model replicated the essential steps. Descriptive analyses were performed. Five experts submitted an outline of steps for transvaginal VVF repair, and 4 experts participated in a focus group to reach consensus on the essential steps. Nine urogynecologic surgeons, with a median of 10 years in practice (interquartile range, 7-12 years), tested the model and completed the postsimulation questionnaire. Most testers thought that tasks involving identification and closure of the fistula were replicated by the model. Testers thought that tasks involving cystoscopy or bladder filling were not replicated by the model. We developed a novel, low-fidelity transvaginal VVF repair simulation model that consistently replicated tasks involving identification and closure of the fistula.

10505 Low-Cost Low-Fidelity Simulation Model for Minor Gynecologic Procedures

10505 Low-Cost Low-Fidelity Simulation Model for Minor Gynecologic Procedures

Low-fidelity simulation models in urology resident's microsurgery training.

To evaluate the gain of microsurgical skills and competencies by urology residents, using low-fidelity experimental models. The study involved the use of training boards, together with a low-fidelity microsurgery simulator, developed using a 3D printer. The model consists in two silicone tubes, coated with a resin, measuring 10 cm in length and with internal and external diameters of 0.5 and 1.5 mm. The support for the ducts is composed by a small box, developed with polylactic acid. The evaluation of the gain of skills and competencies in microsurgery occurred throughout a training course consisting of five training sessions. The first sessions (S1-S4) took place at weekly intervals and the last session (S5) was performed three months after S4. During sessions, were analyzed: the speed of performing microsurgical sutures in the pre and post-training and the performance of each resident through the Objective Structure Assessment of Technical Skill (OSATS) and Student Satisfaction Self-Confidence tools in Learning (SSSCL). There was a decrease in the time needed to perform the anastomosis (p=0.0019), as well as a progressive increase in the score in the OSATS over during sessions S1 to S4. At S5, there was a slightly decrease in performance (p<0.0001), however, remaining within the expected plateau for the gain of skills and competences. The SSSCL satisfaction scale showed an overall approval rating of 96.9%, with a Cronback alpha coefficient of 83%. The low-fidelity simulation was able to guarantee urology residents a solid gain in skills and competencies in microsurgery.

Building a Hysteroscopic Simulation Model

<h3>Study Objective</h3> Demonstrate the construction and implementation of a low-fidelity simulation model for hysteroscopy training to Obstetrics and Gynecology (OB/Gyn) residents. <h3>Design</h3> OB/Gyn residency training program. <h3>Setting</h3> Community-based hospital program. <h3>Patients or Participants</h3> PGY1 through PGY4 OB/Gyne residents from a community-based program. <h3>Interventions</h3> A hysteroscopic simulation model was constructed using low-cost, reusable, and readily accessible materials and supplies. This hysteroscopic model is used to assess residents' identification of a normal cervical canal, junction of the cervical canal and lower uterine segment, and both fallopian tube ostia. The residents should also be able to identify normal intrauterine anatomy and pathology. Learners are taught basic instrument use with proper scope rotation to minimize uterine manipulation and torque. <h3>Measurements and Main Results</h3> The "bell pepper" model is typically used as part of basic hysteroscopy simulation. There are some deficiencies of that model with its inability to accurately simulate proper cervical entry and identify normal intrauterine anatomy. This hysteroscopic simulation model better demonstrates proper insertion technique with angled lens resulting in improved visualization of lateral structures without angling the scope. It also provides training of proper scope rotation using the light post as a guide. <h3>Conclusion</h3> Low fidelity simulation models can be easily implemented into an OB/Gyn residency curriculum to enhance residents' procedural knowledge and skill development. Building this hysteroscopic simulation model provides a useful, practical, and low-cost training tool for teaching basic hysteroscopy techniques.

Laparoscopic Myomectomy Simulation Model for Post-Graduate Learners: Mastering Enucleation

<h3>Study Objective</h3> The objectives of this video are to highlight the fundamentals of laparoscopic myomectomy for postgraduate learners, and to describe a low fidelity simulation model for fibroid enucleation during straight stick laparoscopic myomectomy. <h3>Design</h3> Surgical simulation pilot. <h3>Setting</h3> Surgical simulation lab with use of laparoscopic box trainer. <h3>Patients or Participants</h3> Feedback on the simulation model was obtained from 2 fellowship trained minimally invasive gynecologic attending surgeons (MIGS) and 17 OB/GYN residents evenly distributed across post-graduate year. <h3>Interventions</h3> Using the described model, we assessed user experience and face validity via pre- and post-tests. <h3>Measurements and Main Results</h3> On post-test, 94% of post-graduate learners felt the tactile feedback on the fibroid to be realistic or very realistic. 100% felt starting the plane of enucleation to be realistic or very realistic. 88% felt as though the density of fibroid and number of tenaculum tear-offs was realistic or very realistic. Lastly, 94% of participants felt peeling fibers from the fibroid to be realistic or very realistic. Difficulties with the injection of vasopressin and excess mobility of the uterus during enucleation were cited as points for improvement. After the simulation, 76% felt comfortable or very comfortable with creating the hysterotomy and identifying the correct plane for enucleation as compared to 29% prior. Similarly, 82% of learners felt comfortable or very comfortable with enucleation via traction-counter traction approach as compared to only 35% prior. <h3>Conclusion</h3> This proposed low-fidelity model for laparoscopic myomectomy realistically simulated the fundamental steps of fibroid enucleation and served as a promising method to teach the nuances of haptic feedback on pilot testing. As no historical data is available, in future studies we aim to measure construct validity with predictive validation techniques in a cohort of attending surgeons, MIGS fellows, and OB/GYN residents across several sites.

A Low-fidelity Model for Office-based Hysteroscopy with a Vaginoscopic Approach

Hysteroscopy is an established method for the diagnosis and treatment of intrauterine pathology. A vaginoscopic approach for office-based hysteroscopy confers less pain; however, trainees report lack of confidence with this procedure. We sought to create a low-fidelity simulation model for office-based hysteroscopy with a vaginoscopic approach and to evaluate the validity and reliability of this model. Prospective cohort study. A single academic medical center. Eligible participants included obstetrics and gynecology residents and attendings who regularly perform hysteroscopy. The vaginoscopy model was created with an inanimate female pelvis simulator with an exam glove placed within the vagina. Following 2 instructional videos, participants performed a hysteroscopy simulation with a vaginoscopic approach. The primary outcome was total score on a modified Global Rating Scale and Objective Structured Assessment of Technical Skills. The Objective Structured Assessment of Technical Skills outlines a series of steps that must be performed and was created with assistance from experts in hysteroscopy for providing content-oriented evidence of validity. Time to complete each task and total time were tracked. Participants completed a postprocedure survey assessing the model and experience. A total of 30 physicians participated, with 20 residents (9 junior and 11 senior) and 10 attendings. Attending physicians completed the simulation faster than junior residents (197.2 ± 30.9 vs 289.8 ± 107.4 seconds, p=.022). On the Global Rating Scale, both attending physicians and senior residents scored significantly higher than junior residents (26.1 ± 2.4 vs 22.5 ± 3.7, p=.01). Postsurvey data demonstrated that 93.3% of all participants were satisfied with simulation, 96.6% found it useful, 80% found it realistic, and 93% indicated that they may use this technique in the future. This study shows our low-fidelity model to be effective and useful and to improve confidence for vaginoscopic approach to hysteroscopy. Further studies are needed to assess ability to predict or improve clinical and surgical skills.

Innovative use of a flipped-classroom approach to teach fundamental nursing skills

Prelicensure nursing students are required to master fundamental nursing skills. The COVID-19 pandemic created challenges in maintaining excellence while teaching skill acquisition. The purpose of this study was to evaluate skill validation scores and student satisfaction and self-confidence using a flipped classroom approach and a low-fidelity simulation model to innovatively teach skill acquisition. Researchers used a quasi-experimental method to compare skill validation scores of a control group and intervention group using independent samples t-test. Researchers also evaluated whether prelicensure nursing students had satisfaction and self-confidence with this teaching strategy. Findings suggested that skills validations scores were no different using a flipped-classroom approach than in-person instruction. Prelicensure nursing students were satisfied and self-confident following the implementation of this teaching strategy. This teaching strategy has the potential to decrease in-person clinical practice time, provide alternative opportunities for clinical make-up and remediation, and decrease cost.

Integrated optimization design for horizontal well spacing and fracture stage placement in shale gas reservoir

Horizontal well drilling and hydraulic fracturing technologies play an essential role in improving gas recovery from shale reservoirs. However, they are expensive technologies and resource intensive production strategies. Optimization design of horizontal well spacing and fracture stage placement helps in striking a balance between gas production and economic benefits. However, previous researches relied mainly on numerical simulation technique which is computationally expensive and time-consuming. To reduce the computational burden, a novel multi-fidelity support vector regression (MFSVR) surrogate model assisted horizontal well spacing and fracture stage placement integrated optimization method, namely WSF-MFSVR, is proposed in this study. In the WSF-MFSVR method, both low-fidelity (LF) and high-fidelity (HF) numerical simulation models were applied to establish the multi-fidelity (MF) surrogate model so as to lessen the computational burden and guarantee its quality. In order to enhance the evaluation accuracy, the particle swarm optimization (PSO) algorithm was adopted to find the optimal hyper-parameters of the MFSVR model. Two cases with different wells and fracture types based on the shale gas reservoir with Barnett shale properties were employed to verify the WSF-MFSVR method. The results indicated that a combination of 300 H F and 3500 LF samples was the most suitable for establishing the MFSVR model to approximate the numerical simulation model. In terms of computational efficiency, the WSF-MFSVR method was about 50 times faster than the HF numerical simulation model-based method. Furthermore, the relative hyper-area difference (RHD) and overall spread (OS) of the WSF-MFSVR method were similar to that of the HF numerical simulation model-based method. However, the RHD and OS of the WSF-MFSVR method were superior to that of the LF numerical simulation model-based and single-fidelity support vector regression model-assisted methods. The data of these indexes quantitatively showed the superior convergence and diversity of the final optimal solutions obtained by WSF-MFSVR method.

Development of a Novel, Low-Cost, Low-Fidelity Simulation Model for Pudendal Nerve Block Application.

Pudendal nerve block is an important alternative to neuraxial anesthesia, yet studies demonstrate that 3% to 50% of pudendal nerve blocks are ineffective. Lack of clinician training is the most common cause, and there are no simulation models currently described. To develop and test a novel, low-cost, low-fidelity simulation model for training residents in the placement of a pudendal nerve block. A pudendal nerve block model was developed using commonly found supplies, with a cost of $20.57. First-year to fourth-year obstetrics and gynecology (OB/GYN) and family medicine (FM) residents were invited to 1 of 4 pudendal nerve block 1-hour simulation sessions from December 2019 to March 2021 during their required teaching sessions. Expert faculty led a discussion of pudendal nerve blocks, then participants practiced with the described model. A survey about the model was created by the authors and administrated prior to and immediately after the session. Pre- and post-surveys were analyzed by Wilcoxon signed rank tests, and Bonferroni correction was performed. Thirty-four out of a total of 36 eligible residents participated (94%). Residents showed improvement in knowledge (median pre-simulation score 43.99 compared with 70.06 post-simulation, P<.00625) and self-assessed confidence (median pre-simulation score 1.7 compared with 3.2 post-simulation, P<.00625) of a pudendal block placement after simulation training. This new, low-cost, reusable, low-fidelity simulation model for pudendal nerve block placement improved knowledge and confidence in OB/GYN and FM residents after 1 hour of simulation training.

Efficient Surrogate Modeling and Design Optimization of Compact Integrated On-Chip Inductors Based on Multi-Fidelity EM Simulation Models

High-performance and small-size on-chip inductors play a critical role in contemporary radio-frequency integrated circuits. This work presents a reliable surrogate modeling technique combining low-fidelity EM simulation models, response surface approximations based on kriging interpolation, and space mapping technology. The reported method is useful for the development of broadband and highly accurate data-driven models of integrated inductors within a practical timeframe, especially in terms of the computational expense of training data acquisition. Application of the constructed surrogate model for rapid design optimization of a compact on-chip inductor is demonstrated. The optimized EM-validated design solution can be reached at a low computational cost, which is a considerable improvement over existing approaches. In addition, this work provides a description and illustrates the usefulness of a multi-fidelity design optimization method incorporating EM computational models of graduated complexity and local polynomial approximations managed by an output space mapping optimization framework. As shown by the application example, the final design solution is obtained at the cost of a few high-fidelity EM simulations of a small-size integrated coil. A supplementary description of variable-fidelity EM computational models and a trade-off between model accuracy and its processing time complements the work.

Validation of a Low-Fidelity Model for Office-Based Hysteroscopy with a Vaginoscopic Approach

<h3>Study Objective</h3> Hysteroscopy is an established method for the diagnosis and treatment of intrauterine pathology. A vaginoscopic approach for office-based hysteroscopy confers less pain; however, trainees report lack of confidence with this procedure. We sought to create a low-fidelity simulation model for office-based hysteroscopy with a vaginoscopic approach and to evaluate the validity and reliability of this model. <h3>Design</h3> Prospective cohort study. <h3>Setting</h3> A single site academic medical center. <h3>Patients or Participants</h3> Eligible participants included obstetrics and gynecology residents and attendings who regularly perform hysteroscopy. <h3>Interventions</h3> The vaginoscopy model was created with a female pelvis simulator and an exam glove placed within the vagina. Following two instructional videos, participants performed a hysteroscopy simulation with a vaginoscopic approach. The primary outcome was total score on a modified Global Rating Scale (GRS) and Objective Structured Assessment of Technical Skills (OSATS). The OSATS describes key procedural steps and was created with experts in hysteroscopy for content validity. Time to complete each task was recorded and summed. A post-procedure survey assessed the model and physician experience. <h3>Measurements and Main Results</h3> Ten attending and 20 resident physicians (9 junior and 11 senior) participated. Attending physicians completed the simulation significantly faster than junior residents (197(±31) vs. 290(±107) seconds, Cohen's <i>d</i>=1.2, p=0.022). On the GRS, both attending physicians (26.1(±2.4), <i>d</i>=2.5, p=0.001) and senior residents (22.5(±3.7), <i>d</i>=1.3, p=0.010) scored significantly higher than junior residents (17.4(±4.3)). Ninety-three percent of surveyed participants were satisfied with simulation, 97% found it useful, 80% found it realistic and 93% indicated that they may use this technique in the future. <h3>Conclusion</h3> This study shows our low-fidelity model to have construct, content, and face validity for vaginoscopic approach to hysteroscopy. A sufficiently powered, yet small sample of physician performance data yielded a large effect size in global mean score differences between attendings and junior residents. Physicians reported the technique to be satisfactory, realistic, and useful for future application.

Multifidelity modeling similarity conditions for airfoil dynamic stall prediction with manifold mapping

PurposeThe purpose of this work is to investigate the similarity requirements for the application of multifidelity modeling (MFM) for the prediction of airfoil dynamic stall using computational fluid dynamics (CFD) simulations.Design/methodology/approachDynamic stall is modeled using the unsteady Reynolds-averaged Navier–Stokes equations and Menter's shear stress transport turbulence model. Multifidelity models are created by varying the spatial and temporal discretizations. The effectiveness of the MFM method depends on the similarity between the high- (HF) and low-fidelity (LF) models. Their similarity is tested by computing the prediction error with respect to the HF model evaluations. The proposed approach is demonstrated on three airfoil shapes under deep dynamic stall at a Mach number 0.1 and Reynolds number 135,000.FindingsThe results show that varying the trust-region (TR) radius (λ) significantly affects the prediction accuracy of the MFM. The HF and LF simulation models hold similarity within small (λ ≤ 0.12) to medium (0.12 ≤ λ ≤ 0.23) TR radii producing a prediction error less than 5%, whereas for large TR radii (0.23 ≤ λ ≤ 0.41), the similarity is strongly affected by the time discretization and minimally by the spatial discretization.Originality/valueThe findings of this work present new knowledge for the construction of accurate MFMs for dynamic stall performance prediction using LF model spatial- and temporal discretization setup and the TR radius size. The approach used in this work is general and can be used for other unsteady applications involving CFD-based MFM and optimization.

Concept for a study on community responses to low sonic boom in Europe

In 2018, NASA was the first to assess noise annoyance by low-sonic booms among a population not used to hearing any of the acoustical phenomena associated with an aircraft flying at supersonic speeds (QSF18 study). Meanwhile, within the EU-project RUMBLE, data are collected, and literature reviewed used for research on community responses to low sonic boom demonstrator overflights. We present recommendations for such a field study, comprising NASA and RUMBLE studies' findings and other European efforts emphasizing items discussed by NASA and European researchers in the aftermaths of the first QSF18 results. We propose a study design for the CRLSB study in different European climate zones. A low-fidelity simulation model has been developed to pre-select test sites, supplemented by a more detailed impact model (NENA) for final site selection and preparation of the survey. We identified an approach of mixed survey modes, including experience-sampling procedures, as the most desirable modus operandi for community response assessment. Further, we propose a method for calculating desired sample sizes when applying linear mixed-effects modeling to data collected from a continental field study. [This project has received funding from the European Union's Horizon 2020 research and innovation program under Grant Agreement No. 769896.]

Validation of a low-cost simulation strategy for burn escharotomy training

BackgroundEscharotomy is the primary effective intervention to relieve constriction and impending vascular compromise in deep, circumferential or near-circumferential burns of the extremities and trunk. Training on escharotomy indications, technique and pitfalls is essential, as escharotomy is both an infrequent and high-risk procedure in civilian and military medical environments, including low-resource settings. Therefore, we aimed to validate an educational strategy that combines video-based instruction with a low-cost, low-fidelity simulation model for teaching burn escharotomy. MethodsPre-hospital and hospital-based medical personnel, with varying degrees of burn care-related experience, participated in a one-hour training session. The first part of the training consisted of video-based instruction that described the indications, preparation, steps, pitfalls and complications associated with escharotomy. The second part of the training consisted of a supervised, hands-on simulation with a previously described low-cost, low-fidelity escharotomy model. Participants were then offered two psychometrically validated instruments to assess their learning experience. Results40 participants were grouped according to prior burn care and surgical experience: attending surgeons (6), surgery and emergency medicine residents and fellows (26), medical students (5), and pre-hospital personnel (3). On two psychometrically validated questionnaires, participants at both the attending and trainee levels overwhelmingly confirmed that our educational strategy met best educational practices on the criteria of active learning, collaboration, diverse ways of learning, and high expectations; they also highly rated their satisfaction with and self-confidence under this learning strategy. DiscussionAn educational strategy that combines video-based instruction and a low-cost, low-fidelity escharotomy simulation model was successfully demonstrated with participants across a broad range of prior burn care experience levels. This strategy is easily reproducible and broadly applicable to increase the knowledge and confidence of medical personnel before they are called to perform escharotomy. Important applications include resource-limited environments and deployed military settings.

Making the Cut: Implementing a Low Cost, Low Fidelity Simulation Model for Teaching Emergency Thoracotomy Procedure.

Emergent thoracotomy is a rare but high-stakes procedure for trauma patients. Emergency medicine residents are expected to perform this procedure after graduation, but few get the opportunity to perform it, leading to suboptimal performance and patient morbidity and mortality. Previous low-cost thoracotomy trainers revolve around modifying an existing costly thoracotomy task trainer or bear limited resemblance to actual landmarks and anatomy. This study attempts to bridge this gap by creating a low-cost model with supplies found at most home improvement/craft stores that is more anatomically accurate. We constructed a low fidelity model, which residents ultimately found to be helpful in mastering this rare procedure, and after the training session, they reported a greater level of comfort and familiarization with the procedure.

A Randomized Cross-Over Trial Focused on Clinical Breast Exam Skill Acquisition Using High Fidelity versus Low Fidelity Simulation Models in Rwanda

Breast cancer incidence is rising for women in low and middle income country (LMIC)s. Growing the health care workforce trained in clinical breast exam (CBE) is critical to mitigating breast cancer globally. We developed a CBE simulation training course and determined whether training on a low-fidelity (LF) simulation model results in similar skill acquisition as training on high-fidelity (HF) models in Rwanda. A single-center randomized educational crossover trial was implemented. A preintervention baseline exam (exam 1), followed by a lecture series (exam 2), and training sessions with assigned simulation models was implemented (exam 3)-participants then crossed over to their unassigned model (exam 4). The primary outcome of this study determined mean difference in CBE exam scores between HF and LF groups. Secondary outcomes identified any provider level traits and changes in overall scores. The study was implemented at the University Teaching Hospital, Kigali (CHUK) in Rwanda, Africa from July 2014 to March 2015 PARTICIPANTS: Medical students, residents in surgery, obstetrics and gynecology, and internal medicine residents participated in a 1-day CBE simulation training course. A total of 107 individuals were analyzed in each arm of the study. Mean difference in exam scores between HF and LF models in exam 1 to 4 was not significantly different (exam 1 0.08 standard error (SE) = 0.47, p = 0.42; exam 2 0.86, SE = 0.69, p = 0.16; exam 3 0.03, SE = 0.38, p = 0.66; exam 4 0.10 SE = 0.37, p = 0.29). Overall exam scores improved from pre- to post-intervention. Mean difference in exams scores were not significantly different between participants trained with HF versus LF models. LF models can be utilized as cost effective teaching tools for CBE skill acquisition, in resource poor areas.

A generalized approximate control variate framework for multifidelity uncertainty quantification

We describe and analyze a variance reduction approach for Monte Carlo (MC) sampling that accelerates the estimation of statistics of computationally expensive simulation models using an ensemble of models with lower cost. These lower cost models — which are typically lower fidelity with unknown statistics — are used to reduce the variance in statistical estimators relative to a MC estimator with equivalent cost. We derive the conditions under which our proposed approximate control variate framework recovers existing multifidelity variance reduction schemes as special cases. We demonstrate that existing recursive/nested strategies are suboptimal because they use the additional low-fidelity models only to efficiently estimate the unknown mean of the first low-fidelity model. As a result, they cannot achieve variance reduction beyond that of a control variate estimator that uses a single low-fidelity model with known mean. However, there often exists about an order-of-magnitude gap between the maximum achievable variance reduction using all low-fidelity models and that achieved by a single low-fidelity model with known mean. We show that our proposed approach can exploit this gap to achieve greater variance reduction by using non-recursive sampling schemes. The proposed strategy reduces the total cost of accurately estimating statistics, especially in cases where only low-fidelity simulation models are accessible for additional evaluations. Several analytic examples and an example with a hyperbolic PDE describing elastic wave propagation in heterogeneous media are used to illustrate the main features of the methodology.

A Randomized Cross-Over Trial Focused on Breast Core Needle Biopsy Skill Acquisition and Safety Using High Fidelity Versus Low Fidelity Simulation Models in Rwanda

Breast cancer is the most common cancer diagnosed in low and middle-income countries. Growing the number of health care personnel trained in diagnostic procedures like breast core needle biopsy (BCNB) is critical. We developed a BCNB simulation-training course that evaluated skill acquisition, confidence, and safety, comparing low-cost low fidelity (LF) models to expensive high fidelity (HF) models. A single-center randomized education crossover trial was implemented. Participants were randomized to HF or LF groups. A preintervention baseline exam followed by lectures and training sessions with a HF or LF model was implemented. A postintervention simulation exam was conducted, and participants crossed over to the other simulation model. The study was implemented at the University Teaching Hospital, Kigali (CHUK) in Rwanda, Africa from October 2014 to March 2015. Residents training in surgery or obstetrics and gynecology participated in a 1-day BCNB training course. A total of 36 residents were analyzed, 19 in the HF arm and 17 in the LF arm. Mean difference in exam scores for HF and LF groups in the baseline exam (exam 1) (0.067, p = 0.94, standard error [SE] of 1.57) postintervention exam (exam 2) (1.85, SE 1.46, p = 0.33), and the crossover exam (exam 3) (4.39, SE = 1.90, p = 0.11) were not significantly different between HF and LF. Overall exam scores improved from pre- to postintervention. Our results indicate that mean difference in exams scores were not significantly different between residents trained with HF versus LF models. In resources poor areas-LF models can be utilized as effective teaching tools for skill acquisition for diagnostic surgical procedures.

Surgical cricothyroidostomy. Analysis and comparison between teaching and validation models of simulator models.

to compare the acquisition and retention of knowledge about surgical cricothyroidostomy by the rapid four-step technique (RFST), when taught by expository lecture, low fidelity and high-fidelity simulation models. ninety medical students at UFPR in the first years of training were randomized assigned into 3 groups, submitted to different teaching methods: 1) expository lectures, 2) low-fidelity simulator model, developed by the research team or 3) high-fidelity simulator model (commercial). The procedure chosen was surgical cricothyroidostomy using the RFST. Soon after lectures, the groups were submitted to a multiple-choice test with 20 questions (P1). Four months later, they underwent another test (P2) with similar content. Analysis of Variance was used to compare the grades of each group in P1 with their grades in P2, and the grades of the 3 groups 2 by 2 in P1 and P2. A multiple comparisons test (post-hoc) was used to check differences within each factor (test and group). Statistical significance was considered when p<0.05. Statistical analysis was performed in the statistical software R version 3.6.1. each group was composed of 30 medical students, without demographic differences between them. The mean scores of the groups of the expositive lecture, of the simulator of low fidelity model and of high-fidelity simulator model in P1 were, respectively, 75.00, 76.09, and 68.79, (p<0.05). In P2 the grades were 69.84, 75.32, 69.46, respectively, (p>0.05). the simulation of low fidelity model was more effective in learning and knowledge retention, being feasible for RFST cricothyroidostomy training in inexperienced students.