Objective: Technological developments have made it possible to create simulation models to educate clinicians on surgical techniques and patient preparation. In this study, we created an inexpensive lumbar spine phantom using patient data and analyzed its usefulness in clinical education. Methods: This randomized comparative study used computed tomography and magnetic resonance imaging data from a single patient to print a three-dimensional (3D) bone framework and create a mold. The printed bones and structures made from the mold were placed in a simulation model that was used to train residents. The residents were divided into two groups: Group L, which received only an audiovisual lecture, and Group P, which received an additional 1 hour of training using the 3D phantom. The performance of both groups was evaluated using pretest and post-test analyses. Results: Both the checklist and global rating scores increased after training in both groups. However, some variables improved significantly only in Group P. The overall satisfaction score was also higher in Group P than in Group L. Conclusions: We have described a method by which medical doctors can create a spine simulation phantom and have demonstrated its efficiency for procedural education.

This study uses machine learning and population data to analyze major determinants of blood transfusion among patients with hip arthroplasty. Retrospective cohort data came from Korea National Health Insurance Service claims data for 19,110 patients aged 65 years or more with hip arthroplasty in 2019. The dependent variable was blood transfusion (yes vs no) in 2019 and its 31 predictors were included. Random forest variable importance and Shapley Additive Explanations were used for identifying major predictors and the directions of their associations with blood transfusion. The random forest registered the area under the curve of 73.6%. Based on random forest variable importance, the top-10 predictors were anemia (0.25), tranexamic acid (0.17), age (0.16), socioeconomic status (0.05), spinal anesthesia (0.05), general anesthesia (0.04), sex (female) (0.04), dementia (0.03), iron (0.02), and congestive heart failure (0.02). These predictors were followed by their top-20 counterparts including cardiovascular disease, statin, chronic obstructive pulmonary disease, diabetes mellitus, chronic kidney disease, peripheral vascular disease, liver disease, solid tumor, myocardial infarction and hypertension. In terms of max Shapley Additive Explanations values, these associations were positive, e.g., anemia (0.09), tranexamic acid (0.07), age (0.09), socioeconomic status (0.05), spinal anesthesia (0.05), general anesthesia (0.04), sex (female) (0.02), dementia (0.03), iron (0.04), and congestive heart failure (0.03). For example, the inclusion of anemia, age, tranexamic acid or spinal anesthesia into the random forest will increase the probability of blood transfusion among patients with hip arthroplasty by 9%, 7%, 9% or 5%. Machine learning is an effective prediction model for blood transfusion among patients with hip arthroplasty. The high-risk group with anemia, age and comorbid conditions need to be treated with tranexamic acid, iron and/or other appropriate interventions.

Hyunyoung Seong, Daehun Yun, Kyung Seob Yoon, Ji Soo Kwak, and Jae Chul Koh. Korean J Pain 2022;35:403-12. https://doi.org/10.3344/kjp.2022.35.4.403

Preoperative red blood cell (RBC) transfusion can induce immune modulation and alloimmunization; however, few studies have investigated the effect of preoperative transfusion and hemoglobin levels that need to be corrected before surgery, especially in critically ill patients such as those with end-stage liver disease who undergo liver transplantation (LT). This study aimed to investigate the effects of preoperative RBC transfusion on long-term mortality in LT recipients. A total of 249 patients who underwent LT at a single center between January 2012 and December 2021 were included in this study. The patients were divided into 2 groups: preoperative transfusion and preoperative non-transfusion. Since the baseline characteristics were significantly different between the 2 groups, we performed propensity score matching, including factors such as the Model for End-Stage Liver Disease score and intraoperative RBC transfusion, to exclude possible biases that could affect prognosis. We analyzed the 5-year mortality rate as the primary outcome. The preoperative transfusion group showed a 4.84-fold higher hazard ratio than that in the preoperative non-transfusion group. There were no differences in 30-day mortality, duration of intensive care unit stay, or graft rejection rate between the 2 groups. Preoperative transfusion could influence long-term mortality in LT, and clinicians should pay attention to RBC transfusion before LT unless the patient is hemodynamically unstable. A large-scale randomized controlled trial is needed to determine the possible mechanisms related to preoperative RBC transfusion, long-term mortality, and the level of anemia that should be corrected before surgery.

Hyunyoung Seong, Raing Kyu Kim, Youngjae Shin, Hye Won Lee, and Jae Chul Koh. Korean J Pain 2020;33:395-9. https://doi.org/10.3344/kjp.2020.33.4.395

Background: Gastric insufflation can cause gastric regurgitation, which may be exacerbated in patients who are expected to have difficult airways. The purpose of this study was to investigate the difference in respiratory parameters and the frequency of gastric insufflation according to the ventilation mode during the anesthestic induction on patients who were predicted to have difficult facemask ventilation. Methods: A total of eighty patients with expected airway difficulties were included. Patient were allocated to 2 groups (n = 40 each). In the manual ventilation group, ventilation was performed by putting a mask on the patient’s face with 1-hand and adjusting the pressure limiting valve to 15 cm H₂O. In the pressure-controlled ventilation group, a mask was held in place using 2-handed jaw-thrust maneuver. The pressure-controlled ventilation was applied and peak inspiration pressure was adjusted to achieve a tidal volume of 6 to 8 mL/kg. The primary outcome was the difference of the peak airway pressure between 2 groups every 30 seconds for 120 seconds duration of mask ventilation. We also evaluated respiratory variables including peak airway pressure, End-tidal carbon dioxide and also gastric insufflation using ultrasonography. Results: The pressure-controlled ventilation group demonstrated lower peak airway pressure than the manual ventilation group (P = .005). End-tidal carbon dioxide was higher in the pressure-controlled ventilation group (P = .012). The incidence of gastric insufflation assessed by real-time ultrasonography of the gastric antrum was higher in the manual ventilation group than in the pressure-controlled ventilation group [3 (7.5%) vs 17 (42.5%), risk ratio (95% confidence interval): 0.06 to 0.56, P = .003]. Conclusions: Pressure-controlled ventilation during facemask ventilation in patients who were expected to have difficult airways showed a lower gastric insufflation rate with low peak airway pressure compared to manual ventilation.