Background: Despite the considerable disease burden due to trauma injury, sufficient effort has not been made for the assessment of nationwide trauma care status in Korea. We explored the feasibility of a diagnosis code-based injury severity measuring method in light of its realworld usage. Methods: We used datasets from the National Emergency Department Information System to calculate the survival risk ratios (SRRs) and the Korean Trauma Data Bank to predict models, respectively. The target cohort was split into training and validation datasets using stratified random sampling in an 8:2 ratio. We established six major mortality prediction models depending on the included parameters: 1) the Trauma and Injury Severity Score (TRISS) (age, sex, original Revised Trauma Score [RTS], Injury Severity Score [ISS]), 2) extended International Classification of Diseases-based Injury Severity Score (ICISS) 1 (age, sex, original RTS, ICISS using international SRRs), 3) extended ICISS 2 (age, sex, original RTS, ICISS using Korean SRRs based on 4-digit diagnosis codes), 4) extended ICISS 3 (age, sex, original RTS, ICISS using Korean SRRs based on full-digit diagnosis codes), 5) extended ICISS 4 (age, sex, modified RTS, and ICISS using Korean SRRs based on 4-digit diagnosis codes), 6) extended ICISS 5 (age, sex, modified RTS, and ICISS using Korean SRRs based on full-digit diagnosis codes). We estimated the model using training datasets and fitted it to the validation datasets. We measured the area under the receiver operating characteristic curve (AUC) for discriminative ability. Overall performance was also evaluated using the Brier score. Results: We observed the feasibility of the extended ICISS models, though their performance was slightly lower than the TRISS model (training cohort, AUC 0.936–0.938 vs. 0.949).Regarding SRR calculation methods, we did not find statistically significant differences.The alternative use of the Alert, Voice, Pain, Unresponsive Scale instead of the Glasgow Coma Scale in the RTS calculation did not degrade model performance. Conclusion The availability of the practical ICISS model was observed based on the model performance. We expect our ICISS model to contribute to strengthening the Korean Trauma Care System by utilizing mortality prediction and severity classification.

Kimura’s disease is a rare, chronic inflammatory disorder that typically presents as painless head and neck masses in young Asian males, often accompanied by peripheral eosinophilia and elevated IgE levels. We report a case of recurrent Kimura’s disease involving the right parotid gland in a 35-year-old man, previously treated surgically. Due to tumor size (6 cm) and high risk of surgical complications, the patient underwent radiotherapy (30 Gy/15 fractions). Post-treatment imaging showed significant tumor reduction with no adverse effects or recurrence during 12 months of follow-up. While surgery remains the mainstay of treatment, recent studies suggest that radiotherapy or immunosuppressive therapy may be effective, especially in cases at high risk of recurrence. A recent meta-analysis identified tumor size ≥3 cm, prolonged disease duration (5 years), high eosinophil percentage (20%), and elevated IgE (10,000 IU/ml) as significant recurrence predictors. This case supports that radiotherapy may sere as a valuable treatment option when surgery in contraindicated or in high-risk recurrent cases.

Kimura’s disease is a rare, chronic inflammatory disorder that typically presents as painless head and neck masses in young Asian males, often accompanied by peripheral eosinophilia and elevated IgE levels. We report a case of recurrent Kimura’s disease involving the right parotid gland in a 35-year-old man, previously treated surgically. Due to tumor size (6 cm) and high risk of surgical complications, the patient underwent radiotherapy (30 Gy/15 fractions). Post-treatment imaging showed significant tumor reduction with no adverse effects or recurrence during 12 months of follow-up. While surgery remains the mainstay of treatment, recent studies suggest that radiotherapy or immunosuppressive therapy may be effective, especially in cases at high risk of recurrence. A recent meta-analysis identified tumor size ≥3 cm, prolonged disease duration (5 years), high eosinophil percentage (20%), and elevated IgE (10,000 IU/ml) as significant recurrence predictors. This case supports that radiotherapy may sere as a valuable treatment option when surgery in contraindicated or in high-risk recurrent cases.

Kimura’s disease is a rare, chronic inflammatory disorder that typically presents as painless head and neck masses in young Asian males, often accompanied by peripheral eosinophilia and elevated IgE levels. We report a case of recurrent Kimura’s disease involving the right parotid gland in a 35-year-old man, previously treated surgically. Due to tumor size (6 cm) and high risk of surgical complications, the patient underwent radiotherapy (30 Gy/15 fractions). Post-treatment imaging showed significant tumor reduction with no adverse effects or recurrence during 12 months of follow-up. While surgery remains the mainstay of treatment, recent studies suggest that radiotherapy or immunosuppressive therapy may be effective, especially in cases at high risk of recurrence. A recent meta-analysis identified tumor size ≥3 cm, prolonged disease duration (5 years), high eosinophil percentage (20%), and elevated IgE (10,000 IU/ml) as significant recurrence predictors. This case supports that radiotherapy may sere as a valuable treatment option when surgery in contraindicated or in high-risk recurrent cases.

Background: Despite the considerable disease burden due to trauma injury, sufficient effort has not been made for the assessment of nationwide trauma care status in Korea. We explored the feasibility of a diagnosis code-based injury severity measuring method in light of its realworld usage. Methods: We used datasets from the National Emergency Department Information System to calculate the survival risk ratios (SRRs) and the Korean Trauma Data Bank to predict models, respectively. The target cohort was split into training and validation datasets using stratified random sampling in an 8:2 ratio. We established six major mortality prediction models depending on the included parameters: 1) the Trauma and Injury Severity Score (TRISS) (age, sex, original Revised Trauma Score [RTS], Injury Severity Score [ISS]), 2) extended International Classification of Diseases-based Injury Severity Score (ICISS) 1 (age, sex, original RTS, ICISS using international SRRs), 3) extended ICISS 2 (age, sex, original RTS, ICISS using Korean SRRs based on 4-digit diagnosis codes), 4) extended ICISS 3 (age, sex, original RTS, ICISS using Korean SRRs based on full-digit diagnosis codes), 5) extended ICISS 4 (age, sex, modified RTS, and ICISS using Korean SRRs based on 4-digit diagnosis codes), 6) extended ICISS 5 (age, sex, modified RTS, and ICISS using Korean SRRs based on full-digit diagnosis codes). We estimated the model using training datasets and fitted it to the validation datasets. We measured the area under the receiver operating characteristic curve (AUC) for discriminative ability. Overall performance was also evaluated using the Brier score. Results: We observed the feasibility of the extended ICISS models, though their performance was slightly lower than the TRISS model (training cohort, AUC 0.936–0.938 vs. 0.949).Regarding SRR calculation methods, we did not find statistically significant differences.The alternative use of the Alert, Voice, Pain, Unresponsive Scale instead of the Glasgow Coma Scale in the RTS calculation did not degrade model performance. Conclusion The availability of the practical ICISS model was observed based on the model performance. We expect our ICISS model to contribute to strengthening the Korean Trauma Care System by utilizing mortality prediction and severity classification.

Background: Despite the considerable disease burden due to trauma injury, sufficient effort has not been made for the assessment of nationwide trauma care status in Korea. We explored the feasibility of a diagnosis code-based injury severity measuring method in light of its realworld usage. Methods: We used datasets from the National Emergency Department Information System to calculate the survival risk ratios (SRRs) and the Korean Trauma Data Bank to predict models, respectively. The target cohort was split into training and validation datasets using stratified random sampling in an 8:2 ratio. We established six major mortality prediction models depending on the included parameters: 1) the Trauma and Injury Severity Score (TRISS) (age, sex, original Revised Trauma Score [RTS], Injury Severity Score [ISS]), 2) extended International Classification of Diseases-based Injury Severity Score (ICISS) 1 (age, sex, original RTS, ICISS using international SRRs), 3) extended ICISS 2 (age, sex, original RTS, ICISS using Korean SRRs based on 4-digit diagnosis codes), 4) extended ICISS 3 (age, sex, original RTS, ICISS using Korean SRRs based on full-digit diagnosis codes), 5) extended ICISS 4 (age, sex, modified RTS, and ICISS using Korean SRRs based on 4-digit diagnosis codes), 6) extended ICISS 5 (age, sex, modified RTS, and ICISS using Korean SRRs based on full-digit diagnosis codes). We estimated the model using training datasets and fitted it to the validation datasets. We measured the area under the receiver operating characteristic curve (AUC) for discriminative ability. Overall performance was also evaluated using the Brier score. Results: We observed the feasibility of the extended ICISS models, though their performance was slightly lower than the TRISS model (training cohort, AUC 0.936–0.938 vs. 0.949).Regarding SRR calculation methods, we did not find statistically significant differences.The alternative use of the Alert, Voice, Pain, Unresponsive Scale instead of the Glasgow Coma Scale in the RTS calculation did not degrade model performance. Conclusion The availability of the practical ICISS model was observed based on the model performance. We expect our ICISS model to contribute to strengthening the Korean Trauma Care System by utilizing mortality prediction and severity classification.

Background: Despite the considerable disease burden due to trauma injury, sufficient effort has not been made for the assessment of nationwide trauma care status in Korea. We explored the feasibility of a diagnosis code-based injury severity measuring method in light of its realworld usage. Methods: We used datasets from the National Emergency Department Information System to calculate the survival risk ratios (SRRs) and the Korean Trauma Data Bank to predict models, respectively. The target cohort was split into training and validation datasets using stratified random sampling in an 8:2 ratio. We established six major mortality prediction models depending on the included parameters: 1) the Trauma and Injury Severity Score (TRISS) (age, sex, original Revised Trauma Score [RTS], Injury Severity Score [ISS]), 2) extended International Classification of Diseases-based Injury Severity Score (ICISS) 1 (age, sex, original RTS, ICISS using international SRRs), 3) extended ICISS 2 (age, sex, original RTS, ICISS using Korean SRRs based on 4-digit diagnosis codes), 4) extended ICISS 3 (age, sex, original RTS, ICISS using Korean SRRs based on full-digit diagnosis codes), 5) extended ICISS 4 (age, sex, modified RTS, and ICISS using Korean SRRs based on 4-digit diagnosis codes), 6) extended ICISS 5 (age, sex, modified RTS, and ICISS using Korean SRRs based on full-digit diagnosis codes). We estimated the model using training datasets and fitted it to the validation datasets. We measured the area under the receiver operating characteristic curve (AUC) for discriminative ability. Overall performance was also evaluated using the Brier score. Results: We observed the feasibility of the extended ICISS models, though their performance was slightly lower than the TRISS model (training cohort, AUC 0.936–0.938 vs. 0.949).Regarding SRR calculation methods, we did not find statistically significant differences.The alternative use of the Alert, Voice, Pain, Unresponsive Scale instead of the Glasgow Coma Scale in the RTS calculation did not degrade model performance. Conclusion The availability of the practical ICISS model was observed based on the model performance. We expect our ICISS model to contribute to strengthening the Korean Trauma Care System by utilizing mortality prediction and severity classification.

Kimura’s disease is a rare, chronic inflammatory disorder that typically presents as painless head and neck masses in young Asian males, often accompanied by peripheral eosinophilia and elevated IgE levels. We report a case of recurrent Kimura’s disease involving the right parotid gland in a 35-year-old man, previously treated surgically. Due to tumor size (6 cm) and high risk of surgical complications, the patient underwent radiotherapy (30 Gy/15 fractions). Post-treatment imaging showed significant tumor reduction with no adverse effects or recurrence during 12 months of follow-up. While surgery remains the mainstay of treatment, recent studies suggest that radiotherapy or immunosuppressive therapy may be effective, especially in cases at high risk of recurrence. A recent meta-analysis identified tumor size ≥3 cm, prolonged disease duration (5 years), high eosinophil percentage (20%), and elevated IgE (10,000 IU/ml) as significant recurrence predictors. This case supports that radiotherapy may sere as a valuable treatment option when surgery in contraindicated or in high-risk recurrent cases.

Primary aldosteronism is a group of disorders in which the autonomous secretion of aldosterone is associated with hypertension and hypokalemia. It is crucial to determine the laterality of aldosterone hypersecretion because treatment options differ accordingly. Adrenal venous sampling (AVS) is considered the most reliable method for assessing the laterality of primary aldosteronism. This procedure is often technically challenging because of the small size and varied locations of the adrenal veins. A better understanding of anatomical variations and careful review of imaging studies would improve sampling success. This report presents three cases of anatomical variations encountered during AVS.

Purpose: Pregnant women with diabetes mellitus (DM) and their babies are affected by complications and congenital abnormalities during pregnancy. This study aimed to examine the risk factors for cardiac anomalies and the characteristics of pregestational DM and GDM in mothers and babies in Korea. Methods: This retrospective study used medical records from Bucheon St. Mary's Hospital between January 2013 and July 2021. We studied 1983 infants, with 335 neonates from mothers with DM. Results: Body weight and body mass index were high in mothers with pregestational DM at delivery (p<0.005). The rate of preterm births was lower in the pregestational DM group than in the GDM group. Furthermore, the cardiac anomaly rate was high in the pregestational DM group (p<0.001). The rate of hyperbilirubinemia in the DM group was higher than that in the control group (p<0.001). Multivariate logistic regression analysis revealed no significant risk factors for congenital heart disease. Conclusion DM in pregnant women is associated with congenital anomalies. Therefore, the appropriate management of mothers with DM is important for the prognosis of their neonates.