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의식이 명료한 일산화탄소 중독환자를 대상으로 응급실에서 시행한 간이정신상태검사의 임상적 의의
육현 ( Hyun Youk ),차용성 ( Yong Sung Cha ),김현 ( Hyun Kim ),김성훈 ( Sung Hoon Kim ),김지현 ( Ji Hyun Kim ),김오현 ( Oh Hyun Kim ),김형일 ( Hyung Il Kim ),차경철 ( Kyoung Chul Cha ),이강현 ( Kang Hyun Lee ),황성오 ( Sung Oh Hw 대한임상독성학회 2016 대한임상독성학회지 Vol.14 No.2
Purpose: Because carbon monoxide (CO)-intoxicated patients with an alert mental status and only mild cognitive dysfunction may be inadequately assessed by traditional bedside neurologic examination in the emergency department (ED), they may not receive appropriate treatment. Methods: We retrospectively investigated the incidence and features of cognitive dysfunction using the Korean version of the Mini-Mental State Examination (MMSE-K) in ED patients with CO poisoning with alert mental status. We conducted a retrospective review of 43 consecutive mild CO poisoned patients with a Glasgow Coma Scale score of 15 based on documentation by the treating emergency physician in the ED between July 2014 and August 2015. Results: Cognitive dysfunction, defined as a score of less than 24 in the MMSE-K, was diagnosed in six patients (14%) in the ED. In the MMSE-K, orientation to time, memory recall, and concentration/calculation showed greater impairments. The mean age was significantly older in the cognitive dysfunction group than the non-cognitive dysfunction group (45.3 yrs vs. 66.5 yrs, p<0.001). Among the initial symptoms, experience of a transient change in mental status before ED arrival was significantly more common in the cognitive dysfunction group (32.4% vs. 100%, p=0.003). Conclusion: Patients with CO poisoning and an alert mental status may experience cognitive dysfunction as assessed using the MMSE-K during the early stages of evaluation in the ED. In the MMSE-K, orientation to time, memory recall, and concentration/calculation showed the greatest impairment.
이동건,육현,김현,김오현,고진,김태훈,차경철,이강현,황성오,차용성 연세대학교의과대학 2016 Yonsei medical journal Vol.57 No.1
Purpose: Glufosinate poisoning can cause neurologic complications that may be difficult to treat due to delayed manifestation. Studies assessing possible predictors of complications are lacking. Although serum ammonia level is a potential predictor of severeneurotoxicity, it has only been assessed via case reports. Therefore, we investigated factors that predict neurologic complicationsin acute glufosinate-poisoned patients. Materials and Methods: We conducted a retrospective review of 45 consecutive glufosinate-poisoning cases that were diagnosed in the emergency department (ED) of Wonju Severance Christian Hospital between May 2007 and July 2014. Patients with a Glasgow Coma Scale (GCS) score of <8, seizure, and/or amnesia were defined to a neurologic complication group. Results: The neurologic complication group (29 patients, 64.4%) comprised patients with GCS<8 (27 patients, 60.0%), seizure (23 patients, 51.1%), and amnesia (5 patients, 11.1%). Non-neurologic complications included respiratory failure (14 patients, 31.1%), intubation and ventilator care (23 patients, 51.1%), shock (2 patients, 4.4%), pneumonia (16 patients, 35.6%), acute kidney injury (10 patients, 22.2%), and death (4 patients, 8.9%). Complications of GCS<8, seizure, respiratory failure, and intubation and ventilatorcare appeared during latent periods within 11 hrs, 34 hrs, 14 hrs, and 48 hrs, respectively. Initial serum ammonia was a predictorof neurologic complications [odds ratio 1.039, 95% confidence interval (1.001–1.078), p=0.046 and area under the curve 0.742]. Conclusion: Neurologic complications developed in 64.4% of patients with acute glufosinate poisoning. The most common complicationwas GCS<8. Initial serum ammonia level, which can be readily assessed in the ED, was a predictor of neurologic complications.
탑승자 교통사고에서 경추손상 판단을 위한 중증도 요인 분석
이희영,육현,공준석,강찬영,성실,이정훈,김호중,김상철,추연일,전혁진,박종찬,최지훈,이강현,Lee, Hee Young,Youk, Hyun,Kong, Joon Seok,Kang, Chan Young,Sung, Sil,Lee, Jung Hun,Kim, Ho Jung,Kim, Sang Chul,Choo, Yeon Il,Jeon, Hyeok Jin,Park, Jon 한국자동차안전학회 2018 자동차안전학회지 Vol.10 No.3
It was a pilot study for developing an algorithm to determine the presence or absence of cervical spine injury by analyzing the severity factor of the patients in motor vehicle occupant accidents. From August 2012 to October 2016, we used the KIDAS database, called as Korean In-Depth Accident Study database, collected from three regional emergency centers. We analyzed the general characteristics with several factors. Moreover, cervical spine injury patients were divided into two groups: Group 1 for from Quebec Task Force (hereinafter 'QTF') grade 0 to 1, and group 2 for from QTF grade 2 to 4. The score was assigned according to the distribution ratio of cervical spine injured patients compared to the total injured patients, and the cut-off value was derived from the total score by summation of the assigned score of each factors. 987 patients (53.0%) had no cervical spine injuries and 874 patients (47.0%) had cervical spine injuries. QTF grade 2 was found in 171 patients (9.2%) with musculoskeletal pain, QTF grade 3 was found in 38 patients (2.0%) with spinal cord injuries, and QTF grade 4 was found in 119 patients (6.4%) with dislocation or fracture, respectively. We selected the statistically significant factors, which could be affected the cervical spine injury, like the collision direction, the seating position, the deformation extent, the vehicle type and the frontal airbag deployment. Total score, summation of the assigned each factors, 10 was presented as a cut-off value to determine the cervical spine injury. In this study, it was meaningful as a pilot study to develop algorithms by selecting limited influence factors and proposing cut-off value to determine cervical spine injury. However, since the number of data samples was too small, additional data collection and influencing factor analysis should be performed to develop a more delicate algorithm.
고칼륨혈증 모니터링을 위한 딥러닝 기반 혈청 칼륨 수치에 따른 심전도 변화 스크리닝
문병진,변준,박영철,육현,이희영,추연일 대한전자공학회 2022 전자공학회논문지 Vol.59 No.2
고칼륨혈증(hyperkalemia)은 혈청 칼륨 수치(Serum Potassium Level : SPL)가 이상일 때 진단되며, 심장리듬에 영향을 미쳐 심부전을 일으킬 수 있으므로 빠른 경고가 중요하다. 혈청 칼륨 수치의 증가는 일반적으로 심전도(Electrocardiogram : ECG)의 변형을 일으킨다. 따라서 본 논문에서는 혈청 칼륨 수치에 따른 심전도 변화를 분석하여 고칼륨혈증의 위험이 있는 환자에게 고칼륨혈증의 위험성을 경고할 수 있는 딥러닝 모델을 제안한다. 본 논문에서는 장단기메모리(Long Short Term Memory : LSTM)와 함께 깊이별 분리 가능한 합성곱 커널을 기반으로 하는 합성곱 순환신경망(Convolutional Recurrent Neural Network : CRNN) 모델을 사용하였다. 실제 1,879명 환자의 심전도 데이터들을 대상으로 수행된 실험은 제안된 딥러닝 모델이 심전도의 변화를 분석하여 혈청 칼륨 수치를 비교적 정확하게 예측하고, 깊이분리 합성곱 커널을 사용함으로 인해 작은 네트워크 매개 변수로도 정확도를 유지할 수 있음을 보여준다.
이희영,이강현,김오현,육현,안교진,공준석,강찬영,추연일,김호중,김상철 사단법인 한국자동차안전학회 2019 자동차안전학회지 Vol.11 No.3
Developed countries are operating an in-depth database in motor vehicle crashes nationwide. They do not rely solely on the police investigation reports that are responsible for motor vehicle crashes in each country but are developing into a useful database by expanding the categories of data through more indicators addition. In Korea, after implementing comprehensive measures to reduce traffic accident deaths in 2013, the medical centers participated in establishing the actual accident investigation system, which was called as the Korean In-Depth Accident Study (hereinafter KIDAS). This KIDAS database included more in-depth indicators as the types of accidents, types of vehicles, the injury severity, adequacy of safety devices, seating position of passengers. Although there are difficulties in establishing an actual accident investigation system including data collection due to various restrictions, if the system can cooperate with each other such as medical centers, insurance companies, police, fire and rescue services, towing companies, and car repair shops in the future, It would be expected to contribute to the development of safer vehicle, treatment system and traffic safety policy that lower the injury severity of occupant in the event of a motor vehicle crashes.
이규희,URTNASAN ERDENEBAYAR,황상원,이희영,이정훈,고상백,육현 연세대학교의과대학 2022 Yonsei medical journal Vol.63 No.-
Purpose: We propose the Lifelog Bigdata Platform as a sustainable digital healthcare system based on individual-centric lifelog datasets and describe the standardization of lifelog and clinical data in its full-cycle management system. Materials and Methods: The Lifelog Bigdata Platform was developed by Yonsei Wonju Health System on the cloud to support digital healthcare and precision medicine. It consists of five core components: data acquisition system, de-identification of individual information, lifelog integration, analyzer, and service. We designed a gathering system into a dedicated virtual machine to save lifelog or clinical outcomes and established standard guidelines for maintaining the quality of gathering procedures. We used standard integration keys to integrate the lifelog and clinical data. Metadata were generated from the data warehouse after loading combined or fragmented data on it. We analyzed the de-identified lifelog and clinical data using the lifelog analyzer to prevent and manage acute and chronic diseases through providing results of statistics on analysis. Results: The big data centers were built in four hospitals and seven companies for integrating lifelog and clinical data to develop the Lifelog Bigdata Platform. We integrated and loaded lifelog big data and clinical data for 3 years. In the first year, we uploaded 94 types of data on the platform with a total capacity of 221 GB. Conclusion: The Lifelog Bigdata Platform is the first to combine lifelog and clinical data. The proposed standardization guidelines can be used for future platforms to achieve a virtuous cycle structure of lifelogging big data and an industrial ecosystem.