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Jin Bong Ye 6 Articles
Predicting 30-day mortality in severely injured elderly patients with trauma in Korea using machine learning algorithms: a retrospective study
Jonghee Han, Su Young Yoon, Junepill Seok, Jin Young Lee, Jin Suk Lee, Jin Bong Ye, Younghoon Sul, Se Heon Kim, Hong Rye Kim
J Trauma Inj. 2024;37(3):201-208.   Published online August 8, 2024
DOI: https://doi.org/10.20408/jti.2024.0024
  • 770 View
  • 24 Download
AbstractAbstract PDF
Purpose
The number of elderly patients with trauma is increasing; therefore, precise models are necessary to estimate the mortality risk of elderly patients with trauma for informed clinical decision-making. This study aimed to develop machine learning based predictive models that predict 30-day mortality in severely injured elderly patients with trauma and to compare the predictive performance of various machine learning models. Methods: This study targeted patients aged ≥65 years with an Injury Severity Score of ≥15 who visited the regional trauma center at Chungbuk National University Hospital between 2016 and 2022. Four machine learning models—logistic regression, decision tree, random forest, and eXtreme Gradient Boosting (XGBoost)—were developed to predict 30-day mortality. The models’ performance was compared using metrics such as area under the receiver operating characteristic curve (AUC), accuracy, precision, recall, specificity, F1 score, as well as Shapley Additive Explanations (SHAP) values and learning curves. Results: The performance evaluation of the machine learning models for predicting mortality in severely injured elderly patients with trauma showed AUC values for logistic regression, decision tree, random forest, and XGBoost of 0.938, 0.863, 0.919, and 0.934, respectively. Among the four models, XGBoost demonstrated superior accuracy, precision, recall, specificity, and F1 score of 0.91, 0.72, 0.86, 0.92, and 0.78, respectively. Analysis of important features of XGBoost using SHAP revealed associations such as a high Glasgow Coma Scale negatively impacting mortality probability, while higher counts of transfused red blood cells were positively correlated with mortality probability. The learning curves indicated increased generalization and robustness as training examples increased. Conclusions: We showed that machine learning models, especially XGBoost, can be used to predict 30-day mortality in severely injured elderly patients with trauma. Prognostic tools utilizing these models are helpful for physicians to evaluate the risk of mortality in elderly patients with severe trauma.
Summary
Clinical characteristics and mortality risk factors among trauma patients by age groups at a single center in Korea over 7 years: a retrospective study
Jonghee Han, Su Young Yoon, Junepill Seok, Jin Young Lee, Jin Suk Lee, Jin Bong Ye, Younghoon Sul, Seheon Kim, Hong Rye Kim
J Trauma Inj. 2023;36(4):329-336.   Published online November 7, 2023
DOI: https://doi.org/10.20408/jti.2023.0035
  • 1,546 View
  • 63 Download
AbstractAbstract PDF
Purpose
In this study, we aimed to compare the characteristics of patients with trauma by age group in a single center in Korea to identify the clinical characteristics and analyze the risk factors affecting mortality.
Methods
Patients aged ≥18 years who visited the Chungbuk National University Hospital Regional Trauma Center between January 2016 and December 2022 were included. The accident mechanism, severity of the injury, and outcomes were compared by classifying the patients into group A (18–64 years), group B (65–79 years), and group C (≥80 years). In addition, logistic regression analysis was performed to identify factors affecting death.
Results
The most common injury mechanism was traffic accidents in group A (40.9%) and slipping in group B (37.0%) and group C (56.2%). Although group A had the highest intensive care unit admission rate (38.0%), group C had the highest mortality rate (9.5%). In the regression analysis, 3 to 8 points on the Glasgow Coma Scale had the highest odds ratio for mortality, and red blood cell transfusion within 24 hours, intensive care unit admission, age, and Injury Severity Score were the predictors of death.
Conclusions
For patients with trauma, the mechanism, injured body region, and severity of injury differed among the age groups. The high mortality rate of elderly patients suggests the need for different treatment approaches for trauma patients according to age. Identifying factors affecting clinical patterns and mortality according to age groups can help improve the prognosis of trauma patients in the future.
Summary
Visual Disturbance Caused by a Nail Gun-Induced Penetrating Brain Injury
Jin Bong Ye, Young Hoon Sul, Se Heon Kim, Jin Young Lee, Jin Suk Lee, Hong Rye Kim, Soo Young Yoon, Jung Hee Choi
J Trauma Inj. 2021;34(3):203-207.   Published online September 30, 2021
DOI: https://doi.org/10.20408/jti.2021.0030
  • 2,801 View
  • 74 Download
AbstractAbstract PDF

Penetrating brain injury caused by a nail gun is an uncommon clinical scenario reported in the literature. A 36-year-old male presented with a nail that had penetrated through the occipital bone. He was alert and neurologically intact except for visual disturbance. Computed tomography (CT) of the brain showed the nail lodged at the occipital lobe and the parietal lobe, with minimal intracerebral hemorrhage. The nail was placed in the occipital lobe close to the superior sagittal sinus. We removed the nail with craniotomy since the entrance of the nail was close to the superior sagittal sinus. There were no newly developed neurological deficits postoperatively. Immediate postoperative CT showed no newly developed lesions. The patient recovered well without any significant complications. Two weeks postoperatively, magnetic resonance imaging showed no remarkable lesions. The visual disturbance was followed up at the outpatient department. To summarize, we report a rare case of penetrating head injury by a nail gun and discuss relevant aspects of the clinical management.

Summary
Cerebral Fat Embolism That Was Initially Negative on DiffusionWeighted Magnetic Resonance Imaging
Seung Je Go, Yun Su Mun, Seung Ho Bang, Yong Han Cha, Young Hoon Sul, Jin Bong Ye, Jae Guk Kim
J Trauma Inj. 2021;34(2):126-129.   Published online March 22, 2021
DOI: https://doi.org/10.20408/jti.2020.0007
  • 3,602 View
  • 90 Download
AbstractAbstract PDF

Fat embolism syndrome is a rare, but serious condition that occurs in patients with fractures of the long bones or who undergo orthopedic surgery. The main clinical features of fat embolism syndrome are an altered mental status, hypoxia, and petechial rash. Cerebral fat embolism is the most severe manifestation of fat embolism syndrome because it can lead to an altered mental status. The diagnosis of cerebral fat embolism is clinical, but brain magnetic resonance image (MRI) is helpful. There is usually an interval until symptoms, such as an altered mental status, develop after trauma. We report a case of cerebral fat embolism in which the patient’s mental status deteriorated several hours after trauma and the initial findings were negative on diffusion-weighted MRI.

Summary
Chronic Traumatic Glass Foreign Body Removal from the Lung through a Direct Parenchymal Incision
Su Young Yoon, Si Wook Kim, Jin Suk Lee, Jin Young Lee, Jin Bong Ye, Se Heon Kim, Young Hoon Sul
J Trauma Inj. 2019;32(4):248-251.   Published online December 30, 2019
DOI: https://doi.org/10.20408/jti.2019.031
  • 4,571 View
  • 63 Download
  • 1 Citations
AbstractAbstract PDF

Traumatic intrapulmonary glass foreign bodies that are missed on an initial examination can migrate and lead to severe complications. Here, we present a rare case of a traumatic intrapulmonary glass foreign body surgically removed by a direct pulmonary incision, which preserved the pulmonary parenchyma and avoided severe complications caused by migration.

Summary

Citations

Citations to this article as recorded by  
  • Thoracoscopic retrieval of an intrapulmonary sewing needle: A case report
    Houssem Messaoudi, Imen Ben Ismail, Wafa Ragmoun, Hatem Lahdhili, Saber Hachicha, Slim Chenik
    Clinical Case Reports.2020; 8(12): 2494.     CrossRef
Experience of Penetrating Gunshot Wound on Head in Korea
Hong Rye Kim, Seung Je Go, Young Hoon Sul, Jin Bong Ye, Jin Young Lee, Jung Hee Choi, Seoung Myoung Choi, Yook Kim, Su Young Yoon
J Trauma Inj. 2018;31(2):82-86.   Published online August 31, 2018
DOI: https://doi.org/10.20408/jti.2018.31.2.82
  • 8,011 View
  • 73 Download
  • 1 Citations
AbstractAbstract PDF

Craniocerebral gunshot injuries (CGIs) are extremely seldom happened in Korea because possession of individual firearm is illegal. So, CGIs are rarely encountered by Korean neurosurgeons or Korean trauma surgeons, though in other developing countries or Unites states of America their cases are indefatigably increasing. Management goal should focus on early aggressive, vigorous resuscitation. The treatments consist of immediate life salvage through correction of coagulopathy, intracranial decompression, prevention of infection and preservation of nervous tissue. There have been few studies involving penetrating CGIs in Korea. Here we present a case of penetrating gunshot wound in Korea. We present a 58-year-old man who was unintentionally shot by his colleague with a shotgun. The patients underwent computed tomography (CT) for assessment of intracranial injury. The bullet passed through the left parietal bone and right lateral ventricle and exited through the posterior auricular right temporal bone. After CT scan, he arrested and the cardiopulmonary resuscitation was conducted immediately. But we were unable to resuscitate him. This case report underscores the importance of the initial clinical exam and CT studies along with adequate resuscitation to make the appropriate management decision. Physicians should be familiar with the various injury patterns and imaging findings which are poor prognostic indicators.

Summary

Citations

Citations to this article as recorded by  
  • Civilian penetrating traumatic brain injury: A 5-year single-center experience
    Omid Yousefi, Pouria Azami, Roham Borazjani, Amin Niakan, Mahnaz Yadollahi, Hosseinali Khalili
    Surgical Neurology International.2023; 14: 28.     CrossRef

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