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.

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.

Purpose: NUT carcinoma (NC) is a solid tumor caused by the rearrangement of NUTM1 that usually develops in midline structures, such as the thorax. No standard treatment has been established despite high lethality. Thus, we investigated whether targeting the junction region of NUTM1 fusion breakpoints could serve as a potential treatment option for NC. Materials and Methods: We designed and evaluated a series of small interfering RNAs (siRNAs) targeting the junction region of BRD4-NUTM1 fusion (B4N), the most common form of NUTM1 fusion. Droplet digital polymerase chain reaction using the blood of patients was also tested to evaluate the treatment responses by the junction sequence of the B4N fusion transcripts. Results: As expected, the majority of NC fusion types were B4N (12 of 18, 67%). B4N fusion-specific siRNA treatment on NC cells showed specific inhibitory effects on the B4N fusion transcript and fusion protein without affecting the endogenous expression of the parent genes, resulting in decreased relative cell growth and attenuation of tumor size. In addition, the fusion transcript levels in platelet-rich-plasma samples of the NC patients with systemic metastasis showed a negative correlation with therapeutic effect, suggesting its potential as a measure of treatment responsiveness. Conclusion This study suggests that tumor-specific sequences could be used to treat patients with fusion genes as part of precision medicine for a rare but deadly disease.

Purpose: Despite enzyme replacement therapy (ERT) and/or allogeneic hematopoietic stem cell transplantation, individuals with mucopolysaccharidosis (MPS) I or II often experience significant growth deficiencies. This study aimed to assess the safety and efficacy of recombinant human growth hormone (hGH) treatment in children diagnosed with MPS I or II. Materials and Methods: A total of nine pediatric patients—four with MPS I and five with MPS II—underwent treatment with ERT and hGH at Samsung Medical Center. Results: The mean hGH dose administered was 0.26±0.03 mg/kg/week. In the MPS I group, three patients showed an increase in height Z-score from –4.09±0.83 to –3.68±0.43 after 1 year of hGH treatment, and to –3.10±0.72 by the end of the hGH regimen. In the MPS II group, while the height Z-score of four patients decreased according to standard growth charts, it improved from 1.61±1.79 to 2.71±1.68 based on the disease-specific growth chart through hGH treatment. Two patients discontinued hGH treatment due to lack of efficacy after 22 and 6 months each of treatment, respectively. No new-onset neurological symptoms or necessity for prosthetic or orthopedic surgery were reported during hGH treatment. Conclusion This study provides insights into the impact of hGH on MPS patients, demonstrating its potential to reverse growth deceleration in some cases. Further research is needed to explore the long-term effects of hGH on changes in body composition, muscle strength, and bone health in this population.

Background: There are many models for predicting diabetes mellitus (DM), but their clinical implication remains vague. Therefore, we aimed to create various DM prediction models using easily accessible health screening test parameters. Methods: Two sets of variables were used to develop eight DM prediction models. One set comprised 62 easily accessible examination results of commonly used variables from a tertiary university hospital. The second set comprised 27 of the 62 variables included in the national routine health checkups. Gradient boosting and random forest algorithms were used to develop the models. Internal validation was performed using the stratified 10-fold cross-validation method. Results: The area under the receiver operating characteristic curve (ROC-AUC) for the 62-variable DM model making 12-month predictions for subjects without diabetes was the largest (0.928) among those of the eight DM prediction models. The ROC-AUC dropped by more than 0.04 when training with the simplified 27-variable set but still showed fairly good performance with ROC-AUCs between 0.842 and 0.880. The accuracy was up to 11.5% higher (from 0.807 to 0.714) when fasting glucose was included. Conclusion We created easily applicable diabetes prediction models that deliver good performance using parameters commonly assessed during tertiary university hospital and national routine health checkups. We plan to perform prospective external validation, hoping that the developed DM prediction models will be widely used in clinical practice.

Background: Spinal cord injury (SCI) is a serious clinical condition that impacts a patient's physical, psychological, and socio-economic status. The aim of this pilot study was to evaluate the effects of training with a newly developed powered wearable exoskeleton (Hyundai Medical Exoskeleton [H-MEX]) on functional mobility, physiological health, and quality of life in non-ambulatory SCI patients. Methods: Participants received 60 minutes of walking training with a powered exoskeleton 3 times per week for 10 weeks (total 30 sessions). The 6-minute walking test (6MWT) and timedup-and-go test (TUGT) were performed to assess ambulatory function. The physiological outcomes of interest after exoskeleton-assisted walking training were spasticity, pulmonary function, bone mineral density, colon transit time, and serum inflammatory markers. Effects of walking training on subjective outcomes were estimated by the Korean version of the Falls Efficacy Scale—International and the 36-Item Short-Form Health Survey version 2. Results: Ten participants finished 30 sessions of training and could ambulate independently.No severe adverse events were reported during the study. After training, the mean distance walked in the 6MWT (49.13 m) was significantly enhanced compared with baseline (20.65 m). The results of the TUGT also indicated a statistically significant improvement in the times required to stand up, walk 3 m and sit down. Although not statistically significant, clinically meaningful changes in some secondary physiological outcomes and/or quality of life were reported in some participants. Conclusion In conclusion, this study demonstrated that the newly developed wearable exoskeleton, H-MEX is safe and feasible for non-ambulatory SCI patients, and may have potential to improve quality of life of patients by assisting bipedal ambulation. These results suggest that the H-MEX can be considered a beneficial device for chronic non-ambulatory SCI patients.

Background: Spinal cord injury (SCI) is a serious clinical condition that impacts a patient's physical, psychological, and socio-economic status. The aim of this pilot study was to evaluate the effects of training with a newly developed powered wearable exoskeleton (Hyundai Medical Exoskeleton [H-MEX]) on functional mobility, physiological health, and quality of life in non-ambulatory SCI patients. Methods: Participants received 60 minutes of walking training with a powered exoskeleton 3 times per week for 10 weeks (total 30 sessions). The 6-minute walking test (6MWT) and timedup-and-go test (TUGT) were performed to assess ambulatory function. The physiological outcomes of interest after exoskeleton-assisted walking training were spasticity, pulmonary function, bone mineral density, colon transit time, and serum inflammatory markers. Effects of walking training on subjective outcomes were estimated by the Korean version of the Falls Efficacy Scale—International and the 36-Item Short-Form Health Survey version 2. Results: Ten participants finished 30 sessions of training and could ambulate independently.No severe adverse events were reported during the study. After training, the mean distance walked in the 6MWT (49.13 m) was significantly enhanced compared with baseline (20.65 m). The results of the TUGT also indicated a statistically significant improvement in the times required to stand up, walk 3 m and sit down. Although not statistically significant, clinically meaningful changes in some secondary physiological outcomes and/or quality of life were reported in some participants. Conclusion In conclusion, this study demonstrated that the newly developed wearable exoskeleton, H-MEX is safe and feasible for non-ambulatory SCI patients, and may have potential to improve quality of life of patients by assisting bipedal ambulation. These results suggest that the H-MEX can be considered a beneficial device for chronic non-ambulatory SCI patients.