• Proceedings of the Korea Contents Association Conference
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• 2012.05a
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• pp.343-344
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• 2012

본 연구는 중증도가 높은 신경계중환자를 대상으로 중환자 중증도 분류도구와 Glasgow coma scale 적용의 유용성을 검정하고자 하는데 있다. 본 연구에서 대상자의 일반적 특성 및 임상 관련 특성에 따른 사망률 확인, 중환자 중증도 분류도구(CPSCS)의 일반적 특성, 임상관련 특성에 따른 중증도 차이, GCS의 일반적 특성과 임상관련 특성에 따른 중증도 차이를 파악하고, 임상적 유용성을 검정하고자 한다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.626-634
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• 2018

This retrospective study investigates the accuracy of triage procedures for pediatric patients in emergency departments (EDs) using the Korean Triage and Acuity Scale (KTAS). The study includes 250 randomly selected initial nursing records and clinical outcomes of pediatric patients who visited one regional ED or a local ED from October 2016 to September 2017. The collected data were analyzed by a qualified expert to determine the true triage score. The accuracy of triage was defined as the agreement between the triage score of the emergency nurses (ENs) and the true triage score as determined by the expert. Based on expert comments, the cause of the triage error was analyzed and the KTAS score was compared with the discharge, length of stay (LOS), and medical cost. The results showed that the degree of agreement in the triage score between the experts and the ENs was excellent (weighted kappa=0.77). Among the causes of triage discordance, the most frequent was the incorrect application of vital signs to the KTAS algorithm criteria (n=13). Patients with high severity KTAS levels 1 and 2 were discharged less often (${\chi}=43.25$, p<0.001). There were significant differences in the length of stay (F=12.39, p<0.001) and cost (F=11.78, p<0.001) between KTAS scores when adjusting for age. The results of this study indicate that KTAS is highly accurate in EDs. Hence, the newly developed triage tool is becoming well established in Korea.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.317-320
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• 2021

본 연구는 주기적인 알츠하이머 병의 중증도 모니터링을 위해 스마트 인솔을 통한 보행 특징 추출과 머신러닝 기반 중증도 분류의 성능에 대해 살펴보았다. 최근 고령화가 가속화되는 추세에 있어 치매 환자가 급증하고 있으며, 중증도가 심해질수록 필요한 치료 비용 및 노력이 급증하기 때문에 조기 진단이 최선의 치료 전략으로 보여진다. 환자 친화적이고 저비용의 관성 측정 장치가 내장된 스마트 인솔만을 사용하여 다양한 보행 실험 패러다임에서 환자의 보행 특징을 추출하고, 이를 알츠하이머 병의 중증도 진단을 위한 머신러닝 기반 분류기를 훈련시켜 성능을 평가한 결과, 숫자세기와 같이 뇌에 부하를 주는 하위 작업이 포함된 복합 보행을 측정한 데이터셋을 사용하여 훈련된 분류 모델이 일반 걷기 데이터셋을 사용한 모델보다 성능이 높게 나타나는 것이 관찰되었다. 본 연구는 안전하고 환경적 제약이 적은 방법을 사용하여 시기 적절한 진단뿐만 아니라 주기적인 중증도 모니터링 시스템의 일환으로 활용될 수 있을 것이다.

• Fire Science and Engineering
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• v.33 no.2
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• pp.139-144
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• 2019

The increase in the elderly population also increased the damage and deaths of the elderly drivers. However, studies on the severity and severity of the elderly driver are not actively conducted and the factors are unknown. In this study, I tried to find out the factors affecting the damage and severity of the elderly driver in the frontal collision and to utilize them additionally in the severity classification. Collision Deformation Classification (CDC) Code was used to check the extent of damage to the vehicle. Abbreviated Injury Scale (AIS) was used to determine the injury parts and severity of injury, and the Injury Severity Score (ISS) to confirm the severity of the patient. The odds ratios of severe injury patients were found to be 7.381 in the subjects with 5 or more deformation extent and the ${\beta}$ value of the deformation extent was 0.453 in the analysis of the severity by linear regression analysis. Therefore, the degree of deformation extent of 5 or more can be suggested as a criterion that can be used additionally to the severity classification in the elderly driver.

• Proceedings of the Korea Contents Association Conference
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• 2013.05a
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• pp.209-210
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• 2013

본 연구에서는 보건복지부에서 중증 응급환자를 위한 '중증질환별 특성화 센터'로 지정된 안양의 H병원에서 오토바이 사고로 인해 응급실을 내원하여 중증외상 환자로 분류된 환자를 대상으로 보건복지부 중앙응급의료센터에서 정한 중증외상 등록체계를 바탕으로 중증도를 분석하여 손상기전과 생존의 영향을 미치는 인자에 대하여 알아보고자 한다.

• Journal of Convergence for Information Technology
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• v.10 no.4
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• pp.98-103
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• 2020

The purpose of this study was to determine whether the results of KTAS(Korean Triage and Acuity Scale) triage classifier differ according to the occupations. We analyzed a total of 10,960,359 cases of data sent to the NEDIS from January 1st, 2016 to December 31th, 2017. The triage classifier were MD(Medical Doctor), R(Resident), INT(Intern), GP(General Practitioner), RN(Registered Nurses) and EMT(Emergency Medical Technician). The consistency between the initial triage and final triage results was the highest GP(98.9%) and the lowest INT(80.2%). The results of over-triage classification was the lowest by GP(0.6%) and the highest for INT(16.0%). Also, the results of under-triage classification was the lowest by MD, EMT(0.4%) and the highest for INT(3.8%). The results of KTAS triage classifier significantly differ from according to the occupations(p<0.001). Triage classification should not differ from according to occupations and skill. It is necessary to strengthen the classifier's capacity for accurate triage classifications.

• Tuberculosis and Respiratory Diseases
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• v.49 no.5
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• pp.585-593
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• 2000

Background : International consensus guidelines have recently been developed to improve the assessment and management of asthma. One of the major recommendation of these guidelines is that asthma severity should be assessed through the recognition of key symptoms, such as nocturnal waking, medication requirements, and objective measurements of lung function. Differential classification of asthma severity would lead to major differences in both long term pharmacological management and the treatment of severe exacerbation. Methods : This study examined the relationship between the symptom score and measurements of $FEV_1$ and PEF when expressed as a percentage of predicted values in asthmatics (n=107). Results : The correlation of $FEV_1$ % with PEFR% was highly significant (r=0.83, p<0.01). However, there was agreement in terms of the classification of asthma severity in 76.6% of the paired measurements of $FEV_1$ % and PEFR%. Agreement in the classification of asthma severity was also found in 57.1% of the paired analysis of $FEV_1$ % and symptom score. 39% of the patients classified as having moderate asthma on the basis of $FEV_1$ % recording would be considered to have severe asthma if symptom score alone were used. Low baseline $FEV_1$ and high bronchial responsiveness were associated with a low degree of perception of airway obstruction. Conclusion : The relationships between the symptom score, PEFR and $FEV_1$ were generally poor. When assessing asthma severity, age, duration, $PC_{20}$, and baseline $FEV_1$ should be considered.

• Journal of Korean Biological Nursing Science
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• v.24 no.2
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• pp.122-130
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• 2022

Purpose: This study was conducted to identify the professional competency of nurses working in emergency medical institutions that use the Korean Triage Acuity Scale (KTAS), and to identify factors that affect them. Methods: This study collected data from 105 nurses working in emergency medical institutions from June to August 2020. For data analysis, descriptive analysis, t-test, ANOVA, Pearson's correlation coefficient, and multiple regression were performed using the SPSS 25.0 program. Results: As for the professional competency in triage, the higher the self-efficacy (β= 0.58, p< .001), the more experience they have in triage-related education (β= 0.30, p< .001), 2-4 years of clinical experience in emergency department (β= 0.19, p= .002), in case of triage alone (β= 0.24, p< .001), the higher the level of education a nurse has (β= 0.19, p= .003), the higher the professional competency in triage. These variables explained professional competency in a total of 64.2% of the participants (F = 38.30, p< .001). Conclusion: To improve nurses' professional competence in triage, introducing manpower expansion, financial support, and the provision of appropriate places is suggested. In addition, it is necessary to repeatedly provide educational opportunities in an environment similar to actual clinical practice by developing various scenarios and introducing simulations and web-based formats.

• Journal of the Korea Convergence Society
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• v.12 no.1
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• pp.283-292
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• 2021

The purpose of this study was to identify the factors influencing the disaster nursing preparedness of nursing students. A descriptive survey study was carried out from June 12 to October 16, 2017, the subjects were junior and senior grade nursing students. Data were analyzed by t-test, ANOVA, Pearson's correlation coefficients and multiple regression analysis using the SPSS program. The influencing factors on the disaster nursing preparedness were lower confidence of disaster nursing (β =-.21, p<.001) and disaster nursing knowledge (β=.15, p=002). 10.2% of the variance in disaster nursing preparedness was explained by these two factors on multiple regression analysis. In order to improve the preparedness of nursing students for disaster nursing, nursing students' confidence in disaster nursing should be improved, and a systematic and practical disaster nursing curriculum should be developed.

• Phonetics and Speech Sciences
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• v.13 no.2
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• pp.57-66
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• 2021

This study focuses on the issue of automatic severity classification of dysarthric speakers based on speech intelligibility. Speech intelligibility is a complex measure that is affected by the features of multiple speech dimensions. However, most previous studies are restricted to using features from a single speech dimension. To effectively capture the characteristics of the speech disorder, we extracted features of multiple speech dimensions: voice quality, prosody, and pronunciation. Voice quality consists of jitter, shimmer, Harmonic to Noise Ratio (HNR), number of voice breaks, and degree of voice breaks. Prosody includes speech rate (total duration, speech duration, speaking rate, articulation rate), pitch (F0 mean/std/min/max/med/25quartile/75 quartile), and rhythm (%V, deltas, Varcos, rPVIs, nPVIs). Pronunciation contains Percentage of Correct Phonemes (Percentage of Correct Consonants/Vowels/Total phonemes) and degree of vowel distortion (Vowel Space Area, Formant Centralized Ratio, Vowel Articulatory Index, F2-Ratio). Experiments were conducted using various feature combinations. The experimental results indicate that using features from all three speech dimensions gives the best result, with a 80.15 F1-score, compared to using features from just one or two speech dimensions. The result implies voice quality, prosody, and pronunciation features should all be considered in automatic severity classification of dysarthria.