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A Study on the Historical Development of Research Community in Korea: Focused on the Government Supported Institutes (연구자 집단의 성장과 변천: 정부 출연 연구 기관을 중심으로)

  • Park Jin-Hee
    • Journal of Science and Technology Studies
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    • v.6 no.1 s.11
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    • pp.119-152
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    • 2006
  • This paper deals with the historical development of research community in Korea. As the former studies of the korean scientific community show, the government supported institutes played an important role in the formation of research community. Therefore the theme of this study is concerned with the historical development of the government supported institutes and the features of their researcher group. In this paper following questions will be answered: How the social status of these researcher group is changed, what kind of response on social problems or national politics they had, and which characteristic they showed with regards to the identity problem. After the korean liberation the government institutes, such as the Chungang Kongop Yonguso(industrial research center)and the Korean Atomic Energy Research Institute, contributed to the development of the first generation of research group. However this research group could hardly identify themselves as researcher, because they spent much time on testing, evaluation or education. The identity problem is also resulted from the deficiency of authority as research institute. The status of researcher had no difference from that of civil servant. With the establishment of KIST the korean research community came into blossom. The government supported institutes, which were founded after the model of KIST, allowed quantitative and qualitative growth of research community. Thanks to the guarantee of institutional authority and the new reward system, the researcher could get respect and improve its social status. During this period the researcher volunteered to help the government policies. We can find often the nationalistic statements in the research community. During 1990s the research group demonstrated different behaviors and attitude toward the government. The nationalistic ideology disappeared. Instead of that, the research group criticized the government policies and took actions against the government. Those changes are related with the lowered position of government supported institutes.

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A Study on the Buyer's Decision Making Models for Introducing Intelligent Online Handmade Services (지능형 온라인 핸드메이드 서비스 도입을 위한 구매자 의사결정모형에 관한 연구)

  • Park, Jong-Won;Yang, Sung-Byung
    • Journal of Intelligence and Information Systems
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    • v.22 no.1
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    • pp.119-138
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    • 2016
  • Since the Industrial Revolution, which made the mass production and mass distribution of standardized goods possible, machine-made (manufactured) products have accounted for the majority of the market. However, in recent years, the phenomenon of purchasing even more expensive handmade products has become a noticeable trend as consumers have started to acknowledge the value of handmade products, such as the craftsman's commitment, belief in their quality and scarcity, and the sense of self-esteem from having them,. Consumer interest in these handmade products has shown explosive growth and has been coupled with the recent development of three-dimensional (3D) printing technologies. Etsy.com is the world's largest online handmade platform. It is no different from any other online platform; it provides an online market where buyers and sellers virtually meet to share information and transact business. However, Etsy.com is different in that shops within this platform only deal with handmade products in a variety of categories, ranging from jewelry to toys. Since its establishment in 2005, despite being limited to handmade products, Etsy.com has enjoyed rapid growth in membership, transaction volume, and revenue. Most recently in April 2015, it raised funds through an initial public offering (IPO) of more than 1.8 billion USD, which demonstrates the huge potential of online handmade platforms. After the success of Etsy.com, various types of online handmade platforms such as Handmade at Amazon, ArtFire, DaWanda, and Craft is ART have emerged and are now competing with each other, at the same time, which has increased the size of the market. According to Deloitte's 2015 holiday survey on which types of gifts the respondents plan to buy during the holiday season, about 16% of U.S. consumers chose "homemade or craft items (e.g., Etsy purchase)," which was the same rate as those for the computer game and shoes categories. This indicates that consumer interests in online handmade platforms will continue to rise in the future. However, this high interest in the market for handmade products and their platforms has not yet led to academic research. Most extant studies have only focused on machine-made products and intelligent services for them. This indicates a lack of studies on handmade products and their intelligent services on virtual platforms. Therefore, this study used signaling theory and prior research on the effects of sellers' characteristics on their performance (e.g., total sales and price premiums) in the buyer-seller relationship to identify the key influencing e-Image factors (e.g., reputation, size, information sharing, and length of relationship). Then, their impacts on the performance of shops within the online handmade platform were empirically examined; the dataset was collected from Etsy.com through the application of web harvesting technology. The results from the structural equation modeling revealed that the reputation, size, and information sharing have significant effects on the total sales, while the reputation and length of relationship influence price premiums. This study extended the online platform research into online handmade platform research by identifying key influencing e-Image factors on within-platform shop's total sales and price premiums based on signaling theory and then performed a statistical investigation. These findings are expected to be a stepping stone for future studies on intelligent online handmade services as well as handmade products themselves. Furthermore, the findings of the study provide online handmade platform operators with practical guidelines on how to implement intelligent online handmade services. They should also help shop managers build their marketing strategies in a more specific and effective manner by suggesting key influencing e-Image factors. The results of this study should contribute to the vitalization of intelligent online handmade services by providing clues on how to maximize within-platform shops' total sales and price premiums.

Applying an IPA(Importance-Performance Analysis) Model to Comparative Study on the Elementary School Students' Parents' Crime Prevention Design Element(CPTED) Awareness for Crime Prevention (범죄예방을 위한 초등학교 학부모의 범죄예방설계(CPTED)요소 인식에 관한 비교 연구: IPA(중요도-실행도 분석)기법을 중심으로)

  • Choi, Hyun-Sick
    • Korean Security Journal
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    • no.40
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    • pp.209-242
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    • 2014
  • This study is to understand sure the primary crime prevention has been incidence as a social problem intended for parents through the analysis of the Crime Prevention Design (CPTED) CPTED element of recognize elements that target crime prevention strategy to effectively help students be and an object of the present invention is to provide a policy suggestion haryeoneunde proposed basic data required for orientation. To achieve the study objectives such as the core framework in this study IPA: Importance-Performance Analysis) also was selected. Subjects of study in 2010 Gyeongju Elementary parents name and were 203 first research group investigating the secondary school population of the region in 2014 to nomadic parents of 297 people sampled selection. Questionnaire that use by this study applies "Important-Performance Analysis : IPA" technique that Martilla & James(1977) presented and analyzed awareness for CPTED elements of strategy for student's crime prevention to elementary school pupil students' parentse. It was the first group, 0.886, 0.920, 0.895 and 2nd group 0.880, 0.906, 0.878 that reliability of (Cronbach' s ${\alpha}$) the importance, and believability of run chart was the first group, 0.880, 0.917, 0.878 and 2nd group, 0.735, 0.840, 0.830. Analysis of the data carried out frequency analysis, reliability analysis, Frequency analysis was performed, paired sample t-Test for the reliability analysis, and the technical statistical analysis of the data is. The analysis of lattice bars execution through the IPA, the importance of the primary parents elements of CPTED strategies are generally very high, but found that the variation depending on the components that Performance. This study, an important element of the strategy to eliminate the school building for students from inside and outside the criminal fears CPTED is a mechanical surveillance in the first group, organizational surveillance, and the second group is the region intensified I'll showed mechanically and organizational factors in the investigation, and request that the investment is urgently important element is also execution low, crime prevention personnel security higher importance than expanding the front door. The analysis result of this study expects that basic data can be used in policy direction presentation that examines closely CPTED elements of strategy for crime prevention of students and applies CPTED's component effectively at elementary school hereafter.

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Spatiotemporal Assessment of the Late Marginal Heading Date of Rice using Climate Normal Data in Korea (평년 기후자료를 활용한 국내 벼 안전출수 한계기의 시공간적 변화 평가)

  • Lee, Dongjun;Kim, Junhwan;Kim, Kwang Soo
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.16 no.4
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    • pp.316-326
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    • 2014
  • Determination of the late marginal heading date (LMHD), which would allow estimation of the late marginal seeding date and the late marginal transplanting date, would help identification of potential double cropping areas and, as a result, establishment of cropping systems. The objective of this study was to determine the LMHD at 51 sites in Korea. For these sites, weather data were obtained from 1971 to 2000 and from 1981 to 2010, which represent past and current normal climate conditions, respectively. To examine crop productivity on the LMHD, climatic yield potential (CYP) was determined to represent the potential yield under a given climate condition. The LMHD was calculated using accumulated temperature for 40 days with threshold values of $760^{\circ}C$, $800^{\circ}C$, $840^{\circ}C$ and $880^{\circ}C$. The value of CYP on a given LMHD was determined using mean temperature and sunshine duration for 40 days from the LMHD. The value of CYP on the LMHD was divided by the maximum value of CYP (CYPmax) in a season to represent the relative yield on the LMHD compared with the potential yield in the season. Our results indicated that the LMHD was delayed at most sites under current normal conditions compared with past conditions. Spatial variation of the LMHD differed by the threshold temperature. Overall, the minimum value of CYP/CYPmax was 81.8% under all of given conditions. In most cases, the value of CYP/CYPmax was >90%, which suggested that yield could be comparable to the potential yield even though heading would have occurred on the LMHD. When the LMHD could be scheduled later without considerable reduction in yield, the late marginal transplanting date could also be delayed accordingly, which would facilitate doublecropping in many areas in Korea. Yield could be affected by sudden change of temperature during a grain filling period. Yet, CYP was calculated using mean temperature and sunshine duration for 40 days after heading. Thus, the value of CYP/CYPmax may not represent actual yield potential due to change of the LMHD, which suggested that further study would be merited to take into account the effect of weather events during grain filling periods on yield using crop growth model and field experiments.

Comparison of Association Rule Learning and Subgroup Discovery for Mining Traffic Accident Data (교통사고 데이터의 마이닝을 위한 연관규칙 학습기법과 서브그룹 발견기법의 비교)

  • Kim, Jeongmin;Ryu, Kwang Ryel
    • Journal of Intelligence and Information Systems
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    • v.21 no.4
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    • pp.1-16
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    • 2015
  • Traffic accident is one of the major cause of death worldwide for the last several decades. According to the statistics of world health organization, approximately 1.24 million deaths occurred on the world's roads in 2010. In order to reduce future traffic accident, multipronged approaches have been adopted including traffic regulations, injury-reducing technologies, driving training program and so on. Records on traffic accidents are generated and maintained for this purpose. To make these records meaningful and effective, it is necessary to analyze relationship between traffic accident and related factors including vehicle design, road design, weather, driver behavior etc. Insight derived from these analysis can be used for accident prevention approaches. Traffic accident data mining is an activity to find useful knowledges about such relationship that is not well-known and user may interested in it. Many studies about mining accident data have been reported over the past two decades. Most of studies mainly focused on predict risk of accident using accident related factors. Supervised learning methods like decision tree, logistic regression, k-nearest neighbor, neural network are used for these prediction. However, derived prediction model from these algorithms are too complex to understand for human itself because the main purpose of these algorithms are prediction, not explanation of the data. Some of studies use unsupervised clustering algorithm to dividing the data into several groups, but derived group itself is still not easy to understand for human, so it is necessary to do some additional analytic works. Rule based learning methods are adequate when we want to derive comprehensive form of knowledge about the target domain. It derives a set of if-then rules that represent relationship between the target feature with other features. Rules are fairly easy for human to understand its meaning therefore it can help provide insight and comprehensible results for human. Association rule learning methods and subgroup discovery methods are representing rule based learning methods for descriptive task. These two algorithms have been used in a wide range of area from transaction analysis, accident data analysis, detection of statistically significant patient risk groups, discovering key person in social communities and so on. We use both the association rule learning method and the subgroup discovery method to discover useful patterns from a traffic accident dataset consisting of many features including profile of driver, location of accident, types of accident, information of vehicle, violation of regulation and so on. The association rule learning method, which is one of the unsupervised learning methods, searches for frequent item sets from the data and translates them into rules. In contrast, the subgroup discovery method is a kind of supervised learning method that discovers rules of user specified concepts satisfying certain degree of generality and unusualness. Depending on what aspect of the data we are focusing our attention to, we may combine different multiple relevant features of interest to make a synthetic target feature, and give it to the rule learning algorithms. After a set of rules is derived, some postprocessing steps are taken to make the ruleset more compact and easier to understand by removing some uninteresting or redundant rules. We conducted a set of experiments of mining our traffic accident data in both unsupervised mode and supervised mode for comparison of these rule based learning algorithms. Experiments with the traffic accident data reveals that the association rule learning, in its pure unsupervised mode, can discover some hidden relationship among the features. Under supervised learning setting with combinatorial target feature, however, the subgroup discovery method finds good rules much more easily than the association rule learning method that requires a lot of efforts to tune the parameters.

Development of cardiopulmonary resuscitation nursing education program of web-based instruction (웹 기반의 심폐소생술 간호교육 프로그램 개발)

  • Sin, Hae-Won;Hong, Hae-Sook
    • Journal of Korean Biological Nursing Science
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    • v.4 no.1
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    • pp.25-39
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    • 2002
  • The purpose of this study is to develop and evaluate a web-based instruction Program(WBI) to help nurses improving their knowledge and skill of cardiopulmonary resuscitation. Using the model of web-based instruction(WBI) program designed by Rhu(1999), this study was carried out during February-April 2002 in five different steps; analysis, design, data collection and reconstruction, programming and publishing, and evaluation. The results of the study were as follows; 1) The goal of this program was focused on improving accuracy of knowledge and skills of cardiopulmonary resuscitation. The program texts consists of the concepts and importances of cardiopulmonary resuscitation(CPR), basic life support(BLS), advanced cardiac life support(ACLS), treatment of CPR, nursing care after CPR treatment. And in the file making step, photographs, drawings and image files were collected and edited by web-editor(Namo), scanner and Adobe photoshop program. Then, the files were modified and posted on the web by file transfer protocol(FTP). Finally, the program was demonstrated and once again revised by the result, and then completed. 2) For the evaluation of the program, 36 nurses who in K university hospital located in D city, and related questionnaire were distributed to them as well. Higher scores were given by the nurses in its learning contents with $4.2{\pm}.67$, and in its structuring and interaction of the program with $4.0{\pm}.79$, and also in its satisfactory of the program with $4.2{\pm}.58$ respectively. In conclusion, if the contents of this WBI educational program upgrade further based upon analysis and applying of the results the program evaluation, it is considered as an effective tool to implement for continuing education as life-long educational system for nurse.

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Modeling of Sensorineural Hearing Loss for the Evaluation of Digital Hearing Aid Algorithms (디지털 보청기 알고리즘 평가를 위한 감음신경성 난청의 모델링)

  • 김동욱;박영철
    • Journal of Biomedical Engineering Research
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    • v.19 no.1
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    • pp.59-68
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    • 1998
  • Digital hearing aids offer many advantages over conventional analog hearing aids. With the advent of high speed digital signal processing chips, new digital techniques have been introduced to digital hearing aids. In addition, the evaluation of new ideas in hearing aids is necessarily accompanied by intensive subject-based clinical tests which requires much time and cost. In this paper, we present an objective method to evaluate and predict the performance of hearing aid systems without the help of such subject-based tests. In the hearing impairment simulation(HIS) algorithm, a sensorineural hearing impairment medel is established from auditory test data of the impaired subject being simulated. Also, the nonlinear behavior of the loudness recruitment is defined using hearing loss functions generated from the measurements. To transform the natural input sound into the impaired one, a frequency sampling filter is designed. The filter is continuously refreshed with the level-dependent frequency response function provided by the impairment model. To assess the performance, the HIS algorithm was implemented in real-time using a floating-point DSP. Signals processed with the real-time system were presented to normal subjects and their auditory data modified by the system was measured. The sensorineural hearing impairment was simulated and tested. The threshold of hearing and the speech discrimination tests exhibited the efficiency of the system in its use for the hearing impairment simulation. Using the HIS system we evaluated three typical hearing aid algorithms.

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Identification and Measurement of Hospital-Related Fears in Hospitalized School-Aged Children (학령기 입원아동의 병원관련 공포에 관한 탐색연구)

  • 문영임
    • Journal of Korean Academy of Nursing
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    • v.25 no.1
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    • pp.61-79
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    • 1995
  • When children are admitted to hospital, they have to adapt to new and unfamiliar stimuli. Children may respond with fear to stimuli such as pain or unfamiliar experiences. One goal of nursing is to help hospitalized children to adapt effectively to their hospital experience. Accordingly, nurses need to assess childrens' fears of their hospital experience to contribute to the planning of care to alleviate these fears. The problem addressed by this study was to identify and measure hospital-related fears(hereafter called HRF) in hospitalized school-aged children. The study was conceptualized with Roy's model. A descriptive qualitative approach was used first, followed by a quantitative approach. This study was conducted from November 30, 1989 to January 12, 1991. The sample consisted of 395 hospitalized school-aged children selected through an allocated sampling technique in nine general hospitals. The HRF questionnaire (three point likert scale ) was developed by a delphi technique. The data were analyzed by an SAS program. Factor analysis was used for the examination of component factors. Differences in the HRF related to demographic variables were examined by t-test, analysis of variance and the Scheffe test. The crude scores of the HRF scale were transformed into T- scores to calculate the standard scores. The results included the following : 1. Forty-four items were derived from 188 statements identifying the childrens' hospital-re-lated fears. These items clustered into 14 factors, fear of injections, operations, bodily harm others' pain, medical rounds, physical examinations, medical staff, disease process, blood and X-rays, drugs and cockroaches, tests, harsh discipline from parents or staff, being absent from school, and separation from family. The 14 factors was classified into four categories,'pain','the unfamiliar','the un-known' and 'separation'. 2. The reliability of the HRF instruments was .92(Cronbach's alpha). In the factor analysis, Cronbach's alpha coefficients for the 14 factors ranged from .84 to .86 and Cronbach's alpha coefficients for the four categories ranged from .70 to .84. Pearson correlation coefficient scores for relationships among the 14 factors ranged from ,11 to .50, and among the four categories, from ,44 to ,63, indicating their relative independence. 3. The total group HRF score ranged from 45 to 130 in a possible range of H to 132, with a mean of 74.51. The fears identified by the children were, in order, injections, harsh discipline by parents or staff, bodily harm, operations, medical staff, disease process, and medical rounds ; the least feared was others' pain. The fear item with the highest mean score was surgery and the lowest was examination by a doctor. HRF scores were higher for girls than for boys, and for grade 1 students than for grade 6 students. HRF scores were lower for children whose fathers were over 40 than for those whose fathers were in the 30 to 39 age group, and whose mothers were over 35 than for those whose mothers were in the 20 to 34 age group. HRF scores were lower when the mother rather than any other person stayed with the child. The expressed fear of pain, the unfamiliar, the un-known and of separation directs nurses' concern to the threat felt by hospitalized children to their concept of self. This study contributes to the assessment of fears of hospitalized children and of stimuli impinging on those fears. Accordingly, nursing practice will be directed to the alleviation of pain, pre-admission orientation to the hospital setting and routines, initiation of information about procedures and experiences and arrangments for mothers to stay with their children. Recommendations were made for further research in different settings and for development and testing of the instrument.

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Visualization and Localization of Fusion Image Using VRML for Three-dimensional Modeling of Epileptic Seizure Focus (VRML을 이용한 융합 영상에서 간질환자 발작 진원지의 3차원적 가시화와 위치 측정 구현)

  • 이상호;김동현;유선국;정해조;윤미진;손혜경;강원석;이종두;김희중
    • Progress in Medical Physics
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    • v.14 no.1
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    • pp.34-42
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    • 2003
  • In medical imaging, three-dimensional (3D) display using Virtual Reality Modeling Language (VRML) as a portable file format can give intuitive information more efficiently on the World Wide Web (WWW). The web-based 3D visualization of functional images combined with anatomical images has not studied much in systematic ways. The goal of this study was to achieve a simultaneous observation of 3D anatomic and functional models with planar images on the WWW, providing their locational information in 3D space with a measuring implement using VRML. MRI and ictal-interictal SPECT images were obtained from one epileptic patient. Subtraction ictal SPECT co-registered to MRI (SISCOM) was performed to improve identification of a seizure focus. SISCOM image volumes were held by thresholds above one standard deviation (1-SD) and two standard deviations (2-SD). SISCOM foci and boundaries of gray matter, white matter, and cerebrospinal fluid (CSF) in the MRI volume were segmented and rendered to VRML polygonal surfaces by marching cube algorithm. Line profiles of x and y-axis that represent real lengths on an image were acquired and their maximum lengths were the same as 211.67 mm. The real size vs. the rendered VRML surface size was approximately the ratio of 1 to 605.9. A VRML measuring tool was made and merged with previous VRML surfaces. User interface tools were embedded with Java Script routines to display MRI planar images as cross sections of 3D surface models and to set transparencies of 3D surface models. When transparencies of 3D surface models were properly controlled, a fused display of the brain geometry with 3D distributions of focal activated regions provided intuitively spatial correlations among three 3D surface models. The epileptic seizure focus was in the right temporal lobe of the brain. The real position of the seizure focus could be verified by the VRML measuring tool and the anatomy corresponding to the seizure focus could be confirmed by MRI planar images crossing 3D surface models. The VRML application developed in this study may have several advantages. Firstly, 3D fused display and control of anatomic and functional image were achieved on the m. Secondly, the vector analysis of a 3D surface model was defined by the VRML measuring tool based on the real size. Finally, the anatomy corresponding to the seizure focus was intuitively detected by correlations with MRI images. Our web based visualization of 3-D fusion image and its localization will be a help to online research and education in diagnostic radiology, therapeutic radiology, and surgery applications.

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Multivariate Analysis of Predictive Factors for the Severity in Stable Patients with Severe Injury Mechanism (중증 손상 기전의 안정된 환자에서 중증도 예측 인자들에 대한 다변량 분석)

  • Lee, Jae Young;Lee, Chang Jae;Lee, Hyoung Ju;Chung, Tae Nyoung;Kim, Eui Chung;Choi, Sung Wook;Kim, Ok Jun;Cho, Yun Kyung
    • Journal of Trauma and Injury
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    • v.25 no.2
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    • pp.49-56
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    • 2012
  • Purpose: For determining the prognosis of critically injured patients, transporting patients to medical facilities capable of providing proper assessment and management, running rapid assessment and making rapid decisions, and providing aggressive resuscitation is vital. Considering the high mortality and morbidity rates in critically injured patients, various studies have been conducted in efforts to reduce those rates. However, studies related to diagnostic factors for predicting severity in critically injured patients are still lacking. Furthermore, patients showing stable vital signs and alert mental status, who are injured via a severe trauma mechanism, may be at a risk of not receiving rapid assessment and management. Thus, this study investigates diagnostic factors, including physical examination and laboratory results, that may help predict severity in trauma patients injured via a severe trauma mechanism, but showing stable vital signs. Methods: From March 2010 to December 2011, all trauma patients who fit into a diagnostic category that activated a major trauma team in CHA Bundang Medical Center were analyzed retrospectively. The retrospective analysis was based on prospective medical records completed at the time of arrival in the emergency department and on sequential laboratory test results. PASW statistics 18(SPSS Inc., Chicago, IL, USA) was used for the statistical analysis. Patients with relatively stable vital signs and alert mental status were selected based on a revised trauma score of more than 7 points. The final diagnosis of major trauma was made based on an injury severity score of greater than 16 points. Diagnostic variables include systolic blood pressure and respiratory rate, glasgow coma scale, initial result from focused abdominal sonography for trauma, and laboratory results from blood tests and urine analyses. To confirm the true significance of the measured values, we applied the Kolmogorov-Smirnov one sample test and the Shapiro-Wilk test. When significance was confirmed, the Student's t-test was used for comparison; when significance was not confirmed, the Mann-Whitney u-test was used. The results of focused abdominal sonography for trauma (FAST) and factors of urine analysis were analyzed using the Chi-square test or Fisher's exact test. Variables with statistical significance were selected as prognostics factors, and they were analyzed using a multivariate logistics regression model. Results: A total of 269 patients activated the major trauma team. Excluding 91 patients who scored a revised trauma score of less than 7 points, 178 patients were subdivided by injury severity score to determine the final major trauma patients. Twenty-one(21) patients from 106 major trauma patients and 9 patients from 72 minor trauma patients were also excluded due to missing medical records or untested blood and urine analysis. The investigated variables with p-values less than 0.05 include the glasgow coma scale, respiratory rate, white blood cell count (WBC), serum AST and ALT, serum creatinine, blood in spot urine, and protein in spot urine. These variables could, thus, be prognostic factors in major trauma patients. A multivariate logistics regression analysis on those 8 variables showed the respiratory rate (p=0.034), WBC (p=0.005) and blood in spot urine (p=0.041) to be independent prognostic factors for predicting the clinical course of major trauma patients. Conclusion: In trauma patients injured via a severe trauma mechanism, but showing stable vital signs and alert mental status, the respiratory rate, WBC count and blood in the urine can be used as predictable factors for severity. Using those laboratory results, rapid assessment of major trauma patients may shorten the time to diagnosis and the time for management.