In-depth study of the components of polymyxins is the key to controlling the quality of this class of antibiotics. Similarities and variations of components present significant analytical challenges. A two-dimensional (2D) liquid chromatography-mass spectrometr (LC-MS) method was established for screening and comprehensive profiling of compositions of the antibiotic colistimethate sodium (CMS). A high concentration of phosphate buffer mobile phase was used in the first-dimensional LC system to get the components well separated. For efficient and high-accuracy screening of CMS, a targeted method based on a self-constructed high resolution (HR) mass spectrum database of CMS components was established. The database was built based on the commercial MassHunter Personal Compound Database and Library (PCDL) software and its accuracy of the compound matching result was verified with six known components before being applied to genuine sample screening. On this basis, the unknown peaks in the CMS chromatograms were deduced and assigned. The molecular formula, group composition, and origins of a total of 99 compounds, of which the combined area percentage accounted for more than 95% of CMS components, were deduced by this 2D-LC-MS method combined with the MassHunter PCDL. This profiling method was highly efficient and could distinguish hundreds of components within 3 h, providing reliable results for quality control of this kind of complex drugs.

Accurate occupation classification is essential in various fields, including policy development and epidemiological studies. This study aims to develop an occupation classification model based on DistilKoBERT.

Purpose: This study aimed to compare cognitive, non-cognitive, and overall learning outcomes for sepsis and trauma resuscitation skills in novices with virtual patient simulation (VPS) versus in-person simulation (IPS). Methods: A randomized controlled trial was conducted on junior doctors in 1 emergency department from January to December 2022, comparing 70 minutes of VPS (n=19) versus IPS (n=21) in sepsis and trauma resuscitation. Using the nominal group technique, we created skills assessment checklists and determined Bloom’s taxonomy domains for each checklist item. Two blinded raters observed participants leading 1 sepsis and 1 trauma resuscitation simulation. Satisfaction was measured using the Student Satisfaction with Learning Scale (SSLS). The SSLS and checklist scores were analyzed using the Wilcoxon rank sum test and 2-tailed t-test respectively. Results: For sepsis, there was no significant difference between VPS and IPS in overall scores (2.0; 95% confidence interval [CI], -1.4 to 5.4; Cohen’s d=0.38), as well as in items that were cognitive (1.1; 95% CI, -1.5 to 3.7) and not only cognitive (0.9; 95% CI, -0.4 to 2.2). Likewise, for trauma, there was no significant difference in overall scores (-0.9; 95% CI, -4.1 to 2.3; Cohen’s d=0.19), as well as in items that were cognitive (-0.3; 95% CI, -2.8 to 2.1) and not only cognitive (-0.6; 95% CI, -2.4 to 1.3). The median SSLS scores were lower with VPS than with IPS (-3.0; 95% CI, -1.0 to -5.0). Conclusion For novices, there were no major differences in overall and non-cognitive learning outcomes for sepsis and trauma resuscitation between VPS and IPS. Learners were more satisfied with IPS than with VPS (clinicaltrials.gov identifier: NCT05201950).

Background and Objectives: Real-world clinical data, outside of clinical trials and expert centers, on adverse events related to the use of SyncCardia total artificial heart (TAH) remain limited. We aim to analyze adverse events related to the use of SynCardia TAH reported to the Food and Drug Administration (FDA)’s Manufacturers and User Defined Experience (MAUDE) database. Methods: We reviewed the FDA’s MAUDE database for any adverse events involving the use of SynCardia TAH from 1/01/2012 to 9/30/2020. All the events were independently reviewed by three physicians. Results: A total of 1,512 adverse events were identified in 453 “injury and death” reports in the MAUDE database. The most common adverse events reported were infection (20.2%) and device malfunction (20.1%). These were followed by bleeding events (16.5%), respiratory failure (10.1%), cerebrovascular accident (CVA)/other neurological dysfunction (8.7%), renal dysfunction (7.5%), hepatic dysfunction (2.2%), thromboembolic events (1.8%), pericardial effusion (1.8%), and hemolysis (1%). Death was reported in 49.4% of all the reported cases (n=224/453).The most common cause of death was multiorgan failure (n=73, 32.6%), followed by CVA/other non-specific neurological dysfunction (n=44, 19.7%), sepsis (n=24, 10.7%), withdrawal of support (n=20, 8.9%), device malfunction (n=11, 4.9%), bleeding (n=7, 3.1%), respiratory failure (n=7, 3.1%), gastrointestinal disorder (n=6, 2.7%), and cardiomyopathy (n=3, 1.3%). Conclusions Infection was the most common adverse event following the implantation of TAH. Most of the deaths reported were due to multiorgan failure. Early recognition and management of any possible adverse events after the TAH implantation are essential to improve the procedural outcome and patient survival.

Accurate occupation classification is essential in various fields, including policy development and epidemiological studies. This study aims to develop an occupation classification model based on DistilKoBERT.

Purpose: This study aimed to compare cognitive, non-cognitive, and overall learning outcomes for sepsis and trauma resuscitation skills in novices with virtual patient simulation (VPS) versus in-person simulation (IPS). Methods: A randomized controlled trial was conducted on junior doctors in 1 emergency department from January to December 2022, comparing 70 minutes of VPS (n=19) versus IPS (n=21) in sepsis and trauma resuscitation. Using the nominal group technique, we created skills assessment checklists and determined Bloom’s taxonomy domains for each checklist item. Two blinded raters observed participants leading 1 sepsis and 1 trauma resuscitation simulation. Satisfaction was measured using the Student Satisfaction with Learning Scale (SSLS). The SSLS and checklist scores were analyzed using the Wilcoxon rank sum test and 2-tailed t-test respectively. Results: For sepsis, there was no significant difference between VPS and IPS in overall scores (2.0; 95% confidence interval [CI], -1.4 to 5.4; Cohen’s d=0.38), as well as in items that were cognitive (1.1; 95% CI, -1.5 to 3.7) and not only cognitive (0.9; 95% CI, -0.4 to 2.2). Likewise, for trauma, there was no significant difference in overall scores (-0.9; 95% CI, -4.1 to 2.3; Cohen’s d=0.19), as well as in items that were cognitive (-0.3; 95% CI, -2.8 to 2.1) and not only cognitive (-0.6; 95% CI, -2.4 to 1.3). The median SSLS scores were lower with VPS than with IPS (-3.0; 95% CI, -1.0 to -5.0). Conclusion For novices, there were no major differences in overall and non-cognitive learning outcomes for sepsis and trauma resuscitation between VPS and IPS. Learners were more satisfied with IPS than with VPS (clinicaltrials.gov identifier: NCT05201950).

Accurate occupation classification is essential in various fields, including policy development and epidemiological studies. This study aims to develop an occupation classification model based on DistilKoBERT.

Purpose: This study aimed to compare cognitive, non-cognitive, and overall learning outcomes for sepsis and trauma resuscitation skills in novices with virtual patient simulation (VPS) versus in-person simulation (IPS). Methods: A randomized controlled trial was conducted on junior doctors in 1 emergency department from January to December 2022, comparing 70 minutes of VPS (n=19) versus IPS (n=21) in sepsis and trauma resuscitation. Using the nominal group technique, we created skills assessment checklists and determined Bloom’s taxonomy domains for each checklist item. Two blinded raters observed participants leading 1 sepsis and 1 trauma resuscitation simulation. Satisfaction was measured using the Student Satisfaction with Learning Scale (SSLS). The SSLS and checklist scores were analyzed using the Wilcoxon rank sum test and 2-tailed t-test respectively. Results: For sepsis, there was no significant difference between VPS and IPS in overall scores (2.0; 95% confidence interval [CI], -1.4 to 5.4; Cohen’s d=0.38), as well as in items that were cognitive (1.1; 95% CI, -1.5 to 3.7) and not only cognitive (0.9; 95% CI, -0.4 to 2.2). Likewise, for trauma, there was no significant difference in overall scores (-0.9; 95% CI, -4.1 to 2.3; Cohen’s d=0.19), as well as in items that were cognitive (-0.3; 95% CI, -2.8 to 2.1) and not only cognitive (-0.6; 95% CI, -2.4 to 1.3). The median SSLS scores were lower with VPS than with IPS (-3.0; 95% CI, -1.0 to -5.0). Conclusion For novices, there were no major differences in overall and non-cognitive learning outcomes for sepsis and trauma resuscitation between VPS and IPS. Learners were more satisfied with IPS than with VPS (clinicaltrials.gov identifier: NCT05201950).

Objectives: The sodium index is an index that converts the estimated sodium intake calculated using a verified and reliable sodium estimation formula. This study aimed to determine the relationship between the sodium index and obesity indicators and the potential impact of excessive sodium consumption on obesity. Methods: Obesity indicators, such as body mass index (BMI), body fat percentage, waist-tohip ratio (WHR), and visceral fat levels, were analyzed in 120 university students (60 men and 60 women). The sodium index was calculated by indexing the estimated sodium intake according to age, sex, BMI, salt-eating habits, and salt-eating behaviors. The relationship between sodium index and obesity indicators was analyzed using multiple logistic regression. Results: The estimated sodium intake was 3,907.1 mg, with 76.7% of the participants categorized under the “careful” level of sodium index and 10.8% under the “moderate” level. As the sodium index increased, the BMI, body fat percentage, WHR, and visceral fat levels significantly increased. All obesity indicators significantly increased in patients with a “severe” sodium index than in those with a “moderate” sodium index. In addition, a strong positive correlation was identified between obesity indicators and sodium index. When the “severe” sodium index was compared with the “moderate” sodium index, the risk of obesity based on body fat percentage increased by 2.181 times (95% confidence interval [CI], 1.526–3.118), while the risk of obesity based on visceral fat level increased by 4.073 times (95% CI, 2.097–7.911). Conclusions Our findings suggest a correlation between excessive sodium intake and obesity. Moreover, the sodium index can be used to determine sodium intake.