Objective: : Recently, robotic-assisted spine surgery (RASS) has been considered a minimally invasive and relatively accurate method. In total, 495 robotic-assisted pedicle screw fixation (RAPSF) procedures were attempted on 100 patients during a 14-month period. The current study aimed to analyze the accuracy, potential risk factors, and learning curve of RAPSF. Methods: : This retrospective study evaluated the position of RAPSF using the Gertzbein and Robbins scale (GRS). The accuracy was analyzed using the ratio of the clinically acceptable group (GRS grades A and B), the dissatisfying group (GRS grades C, D, and E), and the Surgical Evaluation Assistant program. The RAPSF was divided into the no-breached group (GRS grade A) and breached group (GRS grades B, C, D, and E), and the potential risk factors of RAPSF were evaluated. The learning curve was analyzed by changes in robot-used time per screw and the occurrence tendency of breached and failed screws according to case accumulation. Results: : The clinically acceptable group in RAPSF was 98.12%. In the analysis using the Surgical Evaluation Assistant program, the tip offset was 2.37±1.89 mm, the tail offset was 3.09±1.90 mm, and the angular offset was 3.72°±2.72°. In the analysis of potential risk factors, the difference in screw fixation level (p=0.009) and segmental distance between the tracker and the instrumented level (p=0.001) between the no-breached and breached group were statistically significant, but not for the other factors. The mean difference between the no-breach and breach groups was statistically significant in terms of pedicle width (p<0.001) and tail offset (p=0.042). In the learning curve analysis, the occurrence of breached and failed screws and the robot-used time per screw screws showed a significant decreasing trend. Conclusion : In the current study, RAPSF was highly accurate and the specific potential risk factors were not identified. However, pedicle width was presumed to be related to breached screw. Meanwhile, the robot-used time per screw and the incidence of breached and failed screws decreased with the learning curve.

Objective: This study aimed to assess the degree of interest in robot-assisted spine surgery (RASS) among residents and to investigate the learning curve for beginners performing robotic surgery. Methods: We conducted a survey to assess awareness and interest in RASS among young neurosurgery residents. Subsequently, we offered a hands-on training program using a dummy to educate one resident. After completing the program, the trained resident performed spinal fusion surgery with robotic assistance under the supervision of a mentor. The clinical outcomes and learning curve associated with robotic surgery were then analyzed. Results: Neurosurgical residents had limited opportunities to participate in spinal surgery during their training. Despite this, there was a significant interest in the emerging field of robotic surgery. A trained resident performed RASS under the supervision of a senior surgeon. A total of 166 screw insertions were attempted in 28 patients, with 2 screws failing due to skiving. According to the Gertzbein-Robbins classification, 85.54% of the screws were rated as grade A, 11.58% as grade B, 0.6% as grade C, and 1.2% as grade D. The clinical acceptance rate was approximately 96.99%, which is comparable to the results reported by senior experts and time per screw statistically significantly decreased as experience was gained. Conclusion RASS can be performed with high accuracy within a relatively short timeframe, if residents receive adequate training.

Objective: This study aimed to assess the degree of interest in robot-assisted spine surgery (RASS) among residents and to investigate the learning curve for beginners performing robotic surgery. Methods: We conducted a survey to assess awareness and interest in RASS among young neurosurgery residents. Subsequently, we offered a hands-on training program using a dummy to educate one resident. After completing the program, the trained resident performed spinal fusion surgery with robotic assistance under the supervision of a mentor. The clinical outcomes and learning curve associated with robotic surgery were then analyzed. Results: Neurosurgical residents had limited opportunities to participate in spinal surgery during their training. Despite this, there was a significant interest in the emerging field of robotic surgery. A trained resident performed RASS under the supervision of a senior surgeon. A total of 166 screw insertions were attempted in 28 patients, with 2 screws failing due to skiving. According to the Gertzbein-Robbins classification, 85.54% of the screws were rated as grade A, 11.58% as grade B, 0.6% as grade C, and 1.2% as grade D. The clinical acceptance rate was approximately 96.99%, which is comparable to the results reported by senior experts and time per screw statistically significantly decreased as experience was gained. Conclusion RASS can be performed with high accuracy within a relatively short timeframe, if residents receive adequate training.

Objective: This study aimed to assess the degree of interest in robot-assisted spine surgery (RASS) among residents and to investigate the learning curve for beginners performing robotic surgery. Methods: We conducted a survey to assess awareness and interest in RASS among young neurosurgery residents. Subsequently, we offered a hands-on training program using a dummy to educate one resident. After completing the program, the trained resident performed spinal fusion surgery with robotic assistance under the supervision of a mentor. The clinical outcomes and learning curve associated with robotic surgery were then analyzed. Results: Neurosurgical residents had limited opportunities to participate in spinal surgery during their training. Despite this, there was a significant interest in the emerging field of robotic surgery. A trained resident performed RASS under the supervision of a senior surgeon. A total of 166 screw insertions were attempted in 28 patients, with 2 screws failing due to skiving. According to the Gertzbein-Robbins classification, 85.54% of the screws were rated as grade A, 11.58% as grade B, 0.6% as grade C, and 1.2% as grade D. The clinical acceptance rate was approximately 96.99%, which is comparable to the results reported by senior experts and time per screw statistically significantly decreased as experience was gained. Conclusion RASS can be performed with high accuracy within a relatively short timeframe, if residents receive adequate training.

Objective: This study aimed to assess the degree of interest in robot-assisted spine surgery (RASS) among residents and to investigate the learning curve for beginners performing robotic surgery. Methods: We conducted a survey to assess awareness and interest in RASS among young neurosurgery residents. Subsequently, we offered a hands-on training program using a dummy to educate one resident. After completing the program, the trained resident performed spinal fusion surgery with robotic assistance under the supervision of a mentor. The clinical outcomes and learning curve associated with robotic surgery were then analyzed. Results: Neurosurgical residents had limited opportunities to participate in spinal surgery during their training. Despite this, there was a significant interest in the emerging field of robotic surgery. A trained resident performed RASS under the supervision of a senior surgeon. A total of 166 screw insertions were attempted in 28 patients, with 2 screws failing due to skiving. According to the Gertzbein-Robbins classification, 85.54% of the screws were rated as grade A, 11.58% as grade B, 0.6% as grade C, and 1.2% as grade D. The clinical acceptance rate was approximately 96.99%, which is comparable to the results reported by senior experts and time per screw statistically significantly decreased as experience was gained. Conclusion RASS can be performed with high accuracy within a relatively short timeframe, if residents receive adequate training.

Objective: This study aimed to assess the degree of interest in robot-assisted spine surgery (RASS) among residents and to investigate the learning curve for beginners performing robotic surgery. Methods: We conducted a survey to assess awareness and interest in RASS among young neurosurgery residents. Subsequently, we offered a hands-on training program using a dummy to educate one resident. After completing the program, the trained resident performed spinal fusion surgery with robotic assistance under the supervision of a mentor. The clinical outcomes and learning curve associated with robotic surgery were then analyzed. Results: Neurosurgical residents had limited opportunities to participate in spinal surgery during their training. Despite this, there was a significant interest in the emerging field of robotic surgery. A trained resident performed RASS under the supervision of a senior surgeon. A total of 166 screw insertions were attempted in 28 patients, with 2 screws failing due to skiving. According to the Gertzbein-Robbins classification, 85.54% of the screws were rated as grade A, 11.58% as grade B, 0.6% as grade C, and 1.2% as grade D. The clinical acceptance rate was approximately 96.99%, which is comparable to the results reported by senior experts and time per screw statistically significantly decreased as experience was gained. Conclusion RASS can be performed with high accuracy within a relatively short timeframe, if residents receive adequate training.

Objective: Fluoroscopy-guided percutaneous pedicle screw fixation (FGPSF) and its further development, robot-assisted percutaneous pedicle screw fixation (RAPSF), are minimally invasive spinal surgery (MISS) techniques. FGPSF is a standard technique at our hospital, and RAPSF incorporating artificial intelligence has been performed at our hospital since October 2021. This study compared these 2 techniques and analyzed their differences, accuracy, and clinical outcomes based on our experiences. Methods: This study conducted a detailed analysis of screw accuracy and the clinical outcomes of 2 MISS techniques, FGPSF, and RAPSF. Screw accuracy was evaluated using the Gertzbein and Robbins scale, categorizing placements into grades A–E, with grades A and B considered clinically acceptable. Accuracy was assessed using postoperative computed tomography images for FGPSF and intraoperative O-arm scan images for RAPSF. Clinical outcomes were compared by examining parameters, such as hospitalization duration, C-reactive protein (CRP) normalization period, estimated blood loss (EBL), and preoperative/postoperative visual analogue scale (VAS) scores. Screw-related complications were reviewed. Independent image evaluations by nonparticipating spine specialists ensured objective and reliable assessments. Results: Both FGPSF and RAPSF demonstrated high rates of clinically acceptable screw placement, with minimal breaches that required no repositioning. The clinically acceptable rates of FGPSF and RAPSF were similar (99.17% and 99.19%, respectively). Both groups also demonstrated similar clinical outcomes. The CRP normalization period, EBL, and ΔVAS (preoperative—postoperative) scores revealed no statistically significant differences between FGPSF and RAPSF. Neither group experienced screw-related complications; however, the RAPSF group exhibited a statistically significant shorter hospital stay than the FGPSF group. Conclusion This study compared the accuracy and clinical outcomes of FGPSF and RAPSF. Both methods demonstrated no significant differences in accuracy or clinical outcomes. Spine surgeons selected between the 2 methods based on individual patient needs, and additional research is required to fully understand the practical advantages of each technique in the clinical field.

Background: There has been no comparison of the determinants of admission route between acute ischemic stroke (AIS) and acute myocardial infarction (AMI). We examined whether factors associated with direct versus transferred-in admission to regional cardiocerebrovascular centers (RCVCs) differed between AIS and AMI. Methods: Using a nationwide RCVC registry, we identified consecutive patients presenting with AMI and AIS between July 2016 and December 2018. We explored factors associated with direct admission to RCVCs in patients with AIS and AMI and examined whether those associations differed between AIS and AMI, including interaction terms between each factor and disease type in multivariable models. To explore the influence of emergency medical service (EMS) paramedics on hospital selection, stratified analyses according to use of EMS were also performed. Results: Among the 17,897 and 8,927 AIS and AMI patients, 66.6% and 48.2% were directly admitted to RCVCs, respectively. Multivariable analysis showed that previous coronary heart disease, prehospital awareness, higher education level, and EMS use increased the odds of direct admission to RCVCs, but the odds ratio (OR) was different between AIS and AMI (for the first 3 factors, AMI > AIS; for EMS use, AMI < AIS). EMS use was the single most important factor for both AIS and AMI (OR, 4.72 vs. 3.90). Hypertension and hyperlipidemia increased, while living alone decreased the odds of direct admission only in AMI;additionally, age (65–74 years), previous stroke, and presentation during non-working hours increased the odds only in AIS. EMS use weakened the associations between direct admission and most factors in both AIS and AMI. Conclusions Various patient factors were differentially associated with direct admission to RCVCs between AIS and AMI. Public education for symptom awareness and use of EMS is essential in optimizing the transportation and hospitalization of patients with AMI and AIS.

Objective: This study evaluated the anxiety, work, and socioeconomic burden of emergency physicians (EP) during the coronavirus disease 2019 (COVID-19) pandemic in South Korea. Methods: A cross-sectional observational study was conducted using data from the 2020 Korean Emergency Physician Survey that included the following domains: hospital resources of suspected COVID-19 patients, availability of personal protective equipment, levels of home and workplace anxiety, the severity of work burnout, identification of stressors, changes in personal environments, and measures to decrease stress/anxiety. Results: Totally, 855 eligible participants were enrolled in the study. A statistically significant deterioration was observed in response to decreased working income or an unstable employment situation (0.46±0.88 points). The median number of patients with confirmed COVID-19 was 2.72. The risk of infection during emergency department (ED) work was found to be significantly increased (P<0.01). Of the 751 respondents (91.4%) who reported patient contact during their survey phase, 516 (62.8%) reported having taken the COVID-19 reverse transcription polymerase chain reaction test. The major factors that affected worsening of the work burden were determined to be unsuitable inter-hospital transfer arrangements for febrile patients (3.46±1.06 before vs. 1.99±1.16 after the pandemic, P<0.01) and delayed consultation for patients with fever or respiratory symptoms in the ED (3.20±1.06 before vs. 2.66±1.10 after the pandemic, P<0.01). Conclusion During the peak phase, the COVID-19 pandemic induced substantial workplace and socioeconomic burdens for Korean EPs. The sustained impact of the pandemic on the wellness of EPs deserves further investigation to guide targeted interventions.

Objective: Machine learning is emerging as a new alternative in various scientific fields and is potentially a new method of interpretation. Using the Light Gradient Boosting Machine (LightGBM), we analyzed the factors that influence the rechoice of emergency medicine responders. The survey is a cross-sectional study which provides an accurate understanding of a responder's current status. However, the results may vary depending on the composition, format, and question, and the relationship between the answers may be unclear. Methods: This study evaluated the modified 2020 Korean Emergency Physician Survey raw data. We applied the preferred model for random relationship check, random forest, support vector machine, and LightGBM models. The stacking ensemble model was used for the final decision process. Results: ‘It is fun working in an emergency room’was the most selected response factor for re-choice, followed by ‘interesting major’. The physical burden of age and lack of identity had a negative impact, whereas burnout and emotional stress factors had a lesser effect. Anxiety caused by the coronavirus disease 2019 (COVID-19) is thought to have a significant impact on this decision making. Conclusion Establishing the identity of emergency medicine and being faithful to its fundamental mission is a way to increase the rate of re-choice. Decreasing the burden of workload modified according to age is recommended to establish career longevity. The method of machine learning presents us with a new possibility of checking the relevance of survey results quickly and easily.