Vertebral arteriovenous fistula (VAVF) is a rare lesion characterized by an abnormal connection between the extracranial vertebral artery and the surrounding venous plexus. It typically arises due to penetrating injury, although it can occasionally result from blunt trauma. Brachial plexus injury (BPI) is also infrequently associated with VAVF. We present a rare case of VAVF caused by blunt trauma, which resulted in BPI. The patient, who had previously sustained a C2 fracture and C2–3 myelopathy from a bicycle accident, presented with new-onset weakness in the right upper extremity. His previous clinical history led to an initial suspicion of either an exacerbation of a pre-existing lesion or a shoulder injury. However, electromyography indicated that the weakness was due to BPI. Further evaluations later revealed VAVF to be the primary cause of the BPI. VAVF must be recognized as a rare potential reason for BPI, as timely intervention is essential for improving patient recovery and prognosis.

Background: Occupational contact dermatitis (OCD) is prevalent among hairdressers due to frequent exposure to chemicals like hair dyes and bleaching agents. Despite the risks, awareness among hairdressers remains low, leading to underreporting and inadequate preventive measures. Objective: This study evaluated hairdressers’ awareness of harmful hair dye ingredients, their experiences with OCD, and the association with product usage patterns. Methods: A cross-sectional study involving 100 hairdressers in Korea examined the relationship between work experience, product usage, and OCD. Chi-square tests and multivariate regression identified significant correlations. Results: Among the participants, 51% reported experiencing adverse skin reactions, with the hands being the most commonly affected area. Longer work experience as a hairdresser was significantly associated with the occurrence of adverse effects ( p=0.046). Notably, shampoo was identified as a suspected causative material significantly more often by the severe group compared to the non-severe group (28.0% vs. 3.8%, p=0.04). Conclusion Chemical exposure and frequent wet work contribute to high rates of OCD among hairdressers. Poor glove usage, especially during shampooing due to inconvenience, is a major risk factor. Raising awareness, promoting proper glove use, and improving workplace safety training are essential for reducing these skin conditions.

Background: Carbapenem resistance in Pseudomonas aeruginosa is a serious global health problem. We investigated the clonal distribution and its association with the carbapenem resistance mechanisms of carbapenem-non-susceptible P. aeruginosa isolates from three Korean hospitals. Methods: A total of 155 carbapenem-non-susceptible P. aeruginosa isolates collected between 2011 and 2019 were analyzed for sequence types (STs), antimicrobial susceptibility, and carbapenem resistance mechanisms, including carbapenemase production, the presence of resistance genes, OprD mutations, and the hyperproduction of AmpC β-lactamase. Results: Sixty STs were identified in carbapenem-non-susceptible P. aeruginosa isolates.Two high-risk clones, ST235 (N = 41) and ST111 (N = 20), were predominant; however, sporadic STs were more prevalent than high-risk clones. The resistance rate to amikacin was the lowest (49.7%), whereas that to piperacillin was the highest (92.3%). Of the 155 carbapenem-non-susceptible isolates, 43 (27.7%) produced carbapenemases. Three metalloβ-lactamase (MBL) genes, blaIMP-6 (N = 38), blaVIM-2 (N = 3), and blaNDM-1 (N = 2), were detected. blaIMP-6 was detected in clonal complex 235 isolates. Two ST773 isolates carried blaNDM-1 and rmtB. Frameshift mutations in oprD were identified in all isolates tested, regardless of the presence of MBL genes. Hyperproduction of AmpC was detected in MBL gene–negative isolates. Conclusions Frameshift mutations in oprD combined with MBL production or hyperproduction of AmpC are responsible for carbapenem resistance in P. aeruginosa. Further attention is required to curb the emergence and spread of new carbapenem-resistant P. aeruginosa clones.

Background: Carbapenem resistance in Pseudomonas aeruginosa is a serious global health problem. We investigated the clonal distribution and its association with the carbapenem resistance mechanisms of carbapenem-non-susceptible P. aeruginosa isolates from three Korean hospitals. Methods: A total of 155 carbapenem-non-susceptible P. aeruginosa isolates collected between 2011 and 2019 were analyzed for sequence types (STs), antimicrobial susceptibility, and carbapenem resistance mechanisms, including carbapenemase production, the presence of resistance genes, OprD mutations, and the hyperproduction of AmpC β-lactamase. Results: Sixty STs were identified in carbapenem-non-susceptible P. aeruginosa isolates.Two high-risk clones, ST235 (N = 41) and ST111 (N = 20), were predominant; however, sporadic STs were more prevalent than high-risk clones. The resistance rate to amikacin was the lowest (49.7%), whereas that to piperacillin was the highest (92.3%). Of the 155 carbapenem-non-susceptible isolates, 43 (27.7%) produced carbapenemases. Three metalloβ-lactamase (MBL) genes, blaIMP-6 (N = 38), blaVIM-2 (N = 3), and blaNDM-1 (N = 2), were detected. blaIMP-6 was detected in clonal complex 235 isolates. Two ST773 isolates carried blaNDM-1 and rmtB. Frameshift mutations in oprD were identified in all isolates tested, regardless of the presence of MBL genes. Hyperproduction of AmpC was detected in MBL gene–negative isolates. Conclusions Frameshift mutations in oprD combined with MBL production or hyperproduction of AmpC are responsible for carbapenem resistance in P. aeruginosa. Further attention is required to curb the emergence and spread of new carbapenem-resistant P. aeruginosa clones.

Background: Carbapenem resistance in Pseudomonas aeruginosa is a serious global health problem. We investigated the clonal distribution and its association with the carbapenem resistance mechanisms of carbapenem-non-susceptible P. aeruginosa isolates from three Korean hospitals. Methods: A total of 155 carbapenem-non-susceptible P. aeruginosa isolates collected between 2011 and 2019 were analyzed for sequence types (STs), antimicrobial susceptibility, and carbapenem resistance mechanisms, including carbapenemase production, the presence of resistance genes, OprD mutations, and the hyperproduction of AmpC β-lactamase. Results: Sixty STs were identified in carbapenem-non-susceptible P. aeruginosa isolates.Two high-risk clones, ST235 (N = 41) and ST111 (N = 20), were predominant; however, sporadic STs were more prevalent than high-risk clones. The resistance rate to amikacin was the lowest (49.7%), whereas that to piperacillin was the highest (92.3%). Of the 155 carbapenem-non-susceptible isolates, 43 (27.7%) produced carbapenemases. Three metalloβ-lactamase (MBL) genes, blaIMP-6 (N = 38), blaVIM-2 (N = 3), and blaNDM-1 (N = 2), were detected. blaIMP-6 was detected in clonal complex 235 isolates. Two ST773 isolates carried blaNDM-1 and rmtB. Frameshift mutations in oprD were identified in all isolates tested, regardless of the presence of MBL genes. Hyperproduction of AmpC was detected in MBL gene–negative isolates. Conclusions Frameshift mutations in oprD combined with MBL production or hyperproduction of AmpC are responsible for carbapenem resistance in P. aeruginosa. Further attention is required to curb the emergence and spread of new carbapenem-resistant P. aeruginosa clones.

Background: Carbapenem resistance in Pseudomonas aeruginosa is a serious global health problem. We investigated the clonal distribution and its association with the carbapenem resistance mechanisms of carbapenem-non-susceptible P. aeruginosa isolates from three Korean hospitals. Methods: A total of 155 carbapenem-non-susceptible P. aeruginosa isolates collected between 2011 and 2019 were analyzed for sequence types (STs), antimicrobial susceptibility, and carbapenem resistance mechanisms, including carbapenemase production, the presence of resistance genes, OprD mutations, and the hyperproduction of AmpC β-lactamase. Results: Sixty STs were identified in carbapenem-non-susceptible P. aeruginosa isolates.Two high-risk clones, ST235 (N = 41) and ST111 (N = 20), were predominant; however, sporadic STs were more prevalent than high-risk clones. The resistance rate to amikacin was the lowest (49.7%), whereas that to piperacillin was the highest (92.3%). Of the 155 carbapenem-non-susceptible isolates, 43 (27.7%) produced carbapenemases. Three metalloβ-lactamase (MBL) genes, blaIMP-6 (N = 38), blaVIM-2 (N = 3), and blaNDM-1 (N = 2), were detected. blaIMP-6 was detected in clonal complex 235 isolates. Two ST773 isolates carried blaNDM-1 and rmtB. Frameshift mutations in oprD were identified in all isolates tested, regardless of the presence of MBL genes. Hyperproduction of AmpC was detected in MBL gene–negative isolates. Conclusions Frameshift mutations in oprD combined with MBL production or hyperproduction of AmpC are responsible for carbapenem resistance in P. aeruginosa. Further attention is required to curb the emergence and spread of new carbapenem-resistant P. aeruginosa clones.

Tuberculous pericarditis is an extrapulmonary manifestation of tuberculosis that is most commonly associated with pericardial thickening, effusion, and calcification. We present a case of tuberculous pericarditis mimicking a malignant pericardial tumor in a 77-year-old male. CT revealed an irregular and nodular pericardial thickening. MRI revealed high signal intensity on T1-weighted fat-suppressed images and peripheral rim enhancement after gadolinium administration. MRI can be helpful in determining the differential diagnoses in cases of tuberculous pericarditis with nonspecific imaging findings.

Tuberculous pericarditis is an extrapulmonary manifestation of tuberculosis that is most commonly associated with pericardial thickening, effusion, and calcification. We present a case of tuberculous pericarditis mimicking a malignant pericardial tumor in a 77-year-old male. CT revealed an irregular and nodular pericardial thickening. MRI revealed high signal intensity on T1-weighted fat-suppressed images and peripheral rim enhancement after gadolinium administration. MRI can be helpful in determining the differential diagnoses in cases of tuberculous pericarditis with nonspecific imaging findings.

Tuberculous pericarditis is an extrapulmonary manifestation of tuberculosis that is most commonly associated with pericardial thickening, effusion, and calcification. We present a case of tuberculous pericarditis mimicking a malignant pericardial tumor in a 77-year-old male. CT revealed an irregular and nodular pericardial thickening. MRI revealed high signal intensity on T1-weighted fat-suppressed images and peripheral rim enhancement after gadolinium administration. MRI can be helpful in determining the differential diagnoses in cases of tuberculous pericarditis with nonspecific imaging findings.

Background: Worldwide, sepsis is the leading cause of death in hospitals. If mortality rates in patients with sepsis can be predicted early, medical resources can be allocated efficiently. We constructed machine learning (ML) models to predict the mortality of patients with sepsis in a hospital emergency department. Methods: This study prospectively collected nationwide data from an ongoing multicenter cohort of patients with sepsis identified in the emergency department. Patients were enrolled from 19 hospitals between September 2019 and December 2020. For acquired data from 3,657 survivors and 1,455 deaths, six ML models (logistic regression, support vector machine, random forest, extreme gradient boosting [XGBoost], light gradient boosting machine, and categorical boosting [CatBoost]) were constructed using fivefold cross-validation to predict mortality. Through these models, 44 clinical variables measured on the day of admission were compared with six sequential organ failure assessment (SOFA) components (PaO 2 /FIO 2 [PF], platelets (PLT), bilirubin, cardiovascular, Glasgow Coma Scale score, and creatinine).The confidence interval (CI) was obtained by performing 10,000 repeated measurements via random sampling of the test dataset. All results were explained and interpreted using Shapley’s additive explanations (SHAP). Results: Of the 5,112 participants, CatBoost exhibited the highest area under the curve (AUC) of 0.800 (95% CI, 0.756–0.840) using clinical variables. Using the SOFA components for the same patient, XGBoost exhibited the highest AUC of 0.678 (95% CI, 0.626–0.730). As interpreted by SHAP, albumin, lactate, blood urea nitrogen, and international normalization ratio were determined to significantly affect the results. Additionally, PF and PLTs in the SOFA component significantly influenced the prediction results. Conclusion Newly established ML-based models achieved good prediction of mortality in patients with sepsis. Using several clinical variables acquired at the baseline can provide more accurate results for early predictions than using SOFA components. Additionally, the impact of each variable was identified.