• Quality Improvement in Health Care
• /
• v.7 no.2
• /
• pp.138-155
• /
• 2000

Background: Factors related to waiting and staying time for patient care in emergency care center (ECC) were examined during 1 month from Apr. 1 to Apr. 30, 1997 at an ECC of Yeungnam university hospital in Taegu metropolitan city, to obtain the baseline data on the strategy of effective management of emergency patients. Method: The study subjects consisted of the 1,742 patients who visited at ECC and the data were obtained from the medical records of ECC and direct surveys. Results: The mean interval between ECC admission time and initial care time by each ECC duty residents was 83.1 minutes for male patients and 84.9 minutes for female patients, and mean ECC staying time (time interval between admission and final disposition from ECC) was 718.0 minutes in men and 670.5 minutes in women. As the results, the mean staying time in ECC was higher in older age, and especially the both of initial care time and staying time were highest in patients of medical aid, and shortest in patients of worker's accident compensation insurance. The on admission or not, previously endotracheal-intubation state of patient. The ECC staying ti initial care time was much more delayed in patients of not having previous medical records and the ECC staying time was higher in referred patients from out-patient department, in transferred patients from the other hospitals and patients having previous records, and in patients partly used the order-communicating system. The factors associated with the initial care time were the numbers of ECC patients and the existence of any true emergent patients, being cardiopulmonary resuscitation (CPR) statusme was much more longer in patients of drug intoxication, in CPR patients, in medical department patients, in transfused patients and in patients related to 3 or more departments. And according to the numbers of duty internships, the ECC staying time for four internships was more longer than for five internships and after admission ordering was done, also-more longer in status being of no available beds. As above mentioned results, the factors for the ECC staying time were thought to be statistically significant (P<0.01) according to the patient's age and the laboratory orders and the X-ray films checked. And also the factor for the ECC staying time were thought to be statistically significant (P<0.01) according to the status being of no available beds, the laboratory orders and/or the special laboratory orders, the X-ray films checked, final disposing department, transferred to other hospital or not, home medication or not, admission or not, the grades of beds, the year grades of residents, the causes of ECC visit, the being CPR status on admission or not, the surgical operation or not, being known personells in our hospital. Conclution: Authors concluded that the relieving method of long-staying time in ECC was being establishing the legally proved apparatus which could differentiate the true emergency or non-emergency patients, and that the methods of shortening ECC staying time were doing definitely necessary laboratory orders and managing beds more flexibly to admit for ECC patients and finally this methods were thought to be a method of unloading for ECC personnels and improving the quality of care in emergency patients.

• Journal of Intelligence and Information Systems
• /
• v.24 no.2
• /
• pp.111-124
• /
• 2018

This study aims to develop a classification model for predicting the occurrence of hyperlipidemia, one of the chronic diseases. Prior studies applying data mining techniques for predicting disease can be classified into a model design study for predicting cardiovascular disease and a study comparing disease prediction research results. In the case of foreign literatures, studies predicting cardiovascular disease were predominant in predicting disease using data mining techniques. Although domestic studies were not much different from those of foreign countries, studies focusing on hypertension and diabetes were mainly conducted. Since hypertension and diabetes as well as chronic diseases, hyperlipidemia, are also of high importance, this study selected hyperlipidemia as the disease to be analyzed. We also developed a model for predicting hyperlipidemia using SVM and meta learning algorithms, which are already known to have excellent predictive power. In order to achieve the purpose of this study, we used data set from Korea Health Panel 2012. The Korean Health Panel produces basic data on the level of health expenditure, health level and health behavior, and has conducted an annual survey since 2008. In this study, 1,088 patients with hyperlipidemia were randomly selected from the hospitalized, outpatient, emergency, and chronic disease data of the Korean Health Panel in 2012, and 1,088 nonpatients were also randomly extracted. A total of 2,176 people were selected for the study. Three methods were used to select input variables for predicting hyperlipidemia. First, stepwise method was performed using logistic regression. Among the 17 variables, the categorical variables(except for length of smoking) are expressed as dummy variables, which are assumed to be separate variables on the basis of the reference group, and these variables were analyzed. Six variables (age, BMI, education level, marital status, smoking status, gender) excluding income level and smoking period were selected based on significance level 0.1. Second, C4.5 as a decision tree algorithm is used. The significant input variables were age, smoking status, and education level. Finally, C4.5 as a decision tree algorithm is used. In SVM, the input variables selected by genetic algorithms consisted of 6 variables such as age, marital status, education level, economic activity, smoking period, and physical activity status, and the input variables selected by genetic algorithms in artificial neural network consist of 3 variables such as age, marital status, and education level. Based on the selected parameters, we compared SVM, meta learning algorithm and other prediction models for hyperlipidemia patients, and compared the classification performances using TP rate and precision. The main results of the analysis are as follows. First, the accuracy of the SVM was 88.4% and the accuracy of the artificial neural network was 86.7%. Second, the accuracy of classification models using the selected input variables through stepwise method was slightly higher than that of classification models using the whole variables. Third, the precision of artificial neural network was higher than that of SVM when only three variables as input variables were selected by decision trees. As a result of classification models based on the input variables selected through the genetic algorithm, classification accuracy of SVM was 88.5% and that of artificial neural network was 87.9%. Finally, this study indicated that stacking as the meta learning algorithm proposed in this study, has the best performance when it uses the predicted outputs of SVM and MLP as input variables of SVM, which is a meta classifier. The purpose of this study was to predict hyperlipidemia, one of the representative chronic diseases. To do this, we used SVM and meta-learning algorithms, which is known to have high accuracy. As a result, the accuracy of classification of hyperlipidemia in the stacking as a meta learner was higher than other meta-learning algorithms. However, the predictive performance of the meta-learning algorithm proposed in this study is the same as that of SVM with the best performance (88.6%) among the single models. The limitations of this study are as follows. First, various variable selection methods were tried, but most variables used in the study were categorical dummy variables. In the case with a large number of categorical variables, the results may be different if continuous variables are used because the model can be better suited to categorical variables such as decision trees than general models such as neural networks. Despite these limitations, this study has significance in predicting hyperlipidemia with hybrid models such as met learning algorithms which have not been studied previously. It can be said that the result of improving the model accuracy by applying various variable selection techniques is meaningful. In addition, it is expected that our proposed model will be effective for the prevention and management of hyperlipidemia.

• Journal of Intelligence and Information Systems
• /
• v.24 no.2
• /
• pp.59-83
• /
• 2018

With the increasing importance of sentiment analysis to grasp the needs of customers and the public, various types of deep learning models have been actively applied to English texts. In the sentiment analysis of English texts by deep learning, natural language sentences included in training and test datasets are usually converted into sequences of word vectors before being entered into the deep learning models. In this case, word vectors generally refer to vector representations of words obtained through splitting a sentence by space characters. There are several ways to derive word vectors, one of which is Word2Vec used for producing the 300 dimensional Google word vectors from about 100 billion words of Google News data. They have been widely used in the studies of sentiment analysis of reviews from various fields such as restaurants, movies, laptops, cameras, etc. Unlike English, morpheme plays an essential role in sentiment analysis and sentence structure analysis in Korean, which is a typical agglutinative language with developed postpositions and endings. A morpheme can be defined as the smallest meaningful unit of a language, and a word consists of one or more morphemes. For example, for a word '예쁘고', the morphemes are '예쁘(= adjective)' and '고(=connective ending)'. Reflecting the significance of Korean morphemes, it seems reasonable to adopt the morphemes as a basic unit in Korean sentiment analysis. Therefore, in this study, we use 'morpheme vector' as an input to a deep learning model rather than 'word vector' which is mainly used in English text. The morpheme vector refers to a vector representation for the morpheme and can be derived by applying an existent word vector derivation mechanism to the sentences divided into constituent morphemes. By the way, here come some questions as follows. What is the desirable range of POS(Part-Of-Speech) tags when deriving morpheme vectors for improving the classification accuracy of a deep learning model? Is it proper to apply a typical word vector model which primarily relies on the form of words to Korean with a high homonym ratio? Will the text preprocessing such as correcting spelling or spacing errors affect the classification accuracy, especially when drawing morpheme vectors from Korean product reviews with a lot of grammatical mistakes and variations? We seek to find empirical answers to these fundamental issues, which may be encountered first when applying various deep learning models to Korean texts. As a starting point, we summarized these issues as three central research questions as follows. First, which is better effective, to use morpheme vectors from grammatically correct texts of other domain than the analysis target, or to use morpheme vectors from considerably ungrammatical texts of the same domain, as the initial input of a deep learning model? Second, what is an appropriate morpheme vector derivation method for Korean regarding the range of POS tags, homonym, text preprocessing, minimum frequency? Third, can we get a satisfactory level of classification accuracy when applying deep learning to Korean sentiment analysis? As an approach to these research questions, we generate various types of morpheme vectors reflecting the research questions and then compare the classification accuracy through a non-static CNN(Convolutional Neural Network) model taking in the morpheme vectors. As for training and test datasets, Naver Shopping's 17,260 cosmetics product reviews are used. To derive morpheme vectors, we use data from the same domain as the target one and data from other domain; Naver shopping's about 2 million cosmetics product reviews and 520,000 Naver News data arguably corresponding to Google's News data. The six primary sets of morpheme vectors constructed in this study differ in terms of the following three criteria. First, they come from two types of data source; Naver news of high grammatical correctness and Naver shopping's cosmetics product reviews of low grammatical correctness. Second, they are distinguished in the degree of data preprocessing, namely, only splitting sentences or up to additional spelling and spacing corrections after sentence separation. Third, they vary concerning the form of input fed into a word vector model; whether the morphemes themselves are entered into a word vector model or with their POS tags attached. The morpheme vectors further vary depending on the consideration range of POS tags, the minimum frequency of morphemes included, and the random initialization range. All morpheme vectors are derived through CBOW(Continuous Bag-Of-Words) model with the context window 5 and the vector dimension 300. It seems that utilizing the same domain text even with a lower degree of grammatical correctness, performing spelling and spacing corrections as well as sentence splitting, and incorporating morphemes of any POS tags including incomprehensible category lead to the better classification accuracy. The POS tag attachment, which is devised for the high proportion of homonyms in Korean, and the minimum frequency standard for the morpheme to be included seem not to have any definite influence on the classification accuracy.

• Information Systems Review
• /
• v.14 no.3
• /
• pp.75-97
• /
• 2012

Fostering trusting belief in financial transactions is a challenging task in Internet banking services. Authenticated Certificate had been regarded as an effective method to guarantee the trusting belief for online transactions. However, previous research claimed that this method has some loopholes for such abusers as hackers, who intend to attack the financial accounts of innocent transactors in Internet. Two types of methods have been suggested as alternatives for securing user identification and activity in online financial services. Control transparency uses information over the transaction process to verify and to control the transactions. Outcome feedback, which refers to the specific information about exchange outcomes, provides information over final transaction results. By using these two methods, financial service providers can send signals to involved parties about the robustness of their security mechanisms. These two methods-control transparency and outcome feedback-have been widely used in the IS field to enhance the quality of IS services. In this research, we intend to verify that these two methods can also be used to reduce risks and to increase the security protections in online banking services. The purpose of this paper is to empirically test the effects of the control transparency and the outcome feedback on the risk perceptions in Internet banking services. Our assumption is that these two methods-control transparency and outcome feedback-can reduce perceived risks involved with online financial transactions, while increasing perceived trust over financial service providers. These changes in user attitudes can increase the level of user satisfactions, which may lead to the increased user loyalty as well as users' willingness to pay for the financial transactions. Previous research in IS suggested that the increased level of transparency on the process and the result of transactions can enhance the information quality and decision quality of IS users. Transparency helps IS users to acquire the information needed to control the transaction counterpart and thus to complete transaction successfully. It is also argued that transparency can reduce the perceived transaction risks in IS usage. Many IS researchers also argued that the trust can be generated by the institutional mechanisms. Trusting belief refers to the truster's belief for the trustee to have attributes for being beneficial to the truster. Institution-based trust plays an important role to enhance the probability of achieving a successful outcome. When a transactor regards the conditions crucial for the transaction success, he or she considers the condition providers as trustful, and thus eventually trust the others involved with such condition providers. In this process, transparency helps the transactor complete the transaction successfully. Through the investigation of these studies, we expect that the control transparency and outcome feedback can reduce the risk perception on transaction and enhance the trust with the service provider. Based on a theoretical framework of transparency and institution-based trust, we propose and test a research model by evaluating research hypotheses. We have conducted a laboratory experiment in order to validate our research model. Since the transparency artifact(control transparency and outcome feedback) is not yet adopted in online banking services, the general survey method could not be employed to verify our research model. We collected data from 138 experiment subjects who had experiences with online banking services. PLS is used to analyze the experiment data. The measurement model confirms that our data set has appropriate convergent and discriminant validity. The results of testing the structural model indicate that control transparency significantly enhances the trust and significantly reduces the risk perception of online banking users. The result also suggested that the outcome feedback significantly enhances the trust of users. We have found that the reduced risk and the increased trust level significantly improve the level of service satisfaction. The increased satisfaction finally leads to the increased loyalty and willingness to pay for the financial services.

• The Korean Journal of Nuclear Medicine Technology
• /
• v.13 no.1
• /
• pp.51-56
• /
• 2009

Purpose: Recently, most hospitals are introducing the PACS system and use of the system continues to expand. But small-scaled PACS called MicroPACS has already been in use through open source programs. The aim of this study is to prove utility of operating a MicroPACS, as a substitute back-up device for conventional storage media like CDs and DVDs, in addition to the full-PACS already in use. This study contains the way of setting up a MicroPACS with open source programs and assessment of its storage capability, stability, compatibility and performance of operations such as "retrieve", "query". Materials and Methods: 1. To start with, we searched open source software to correspond with the following standards to establish MicroPACS, (1) It must be available in Windows Operating System. (2) It must be free ware. (3) It must be compatible with PET/CT scanner. (4) It must be easy to use. (5) It must not be limited of storage capacity. (6) It must have DICOM supporting. 2. (1) To evaluate availability of data storage, we compared the time spent to back up data in the open source software with the optical discs (CDs and DVD-RAMs), and we also compared the time needed to retrieve data with the system and with optical discs respectively. (2) To estimate work efficiency, we measured the time spent to find data in CDs, DVD-RAMs and MicroPACS. 7 technologists participated in this study. 3. In order to evaluate stability of the software, we examined whether there is a data loss during the system is maintained for a year. Comparison object; How many errors occurred in randomly selected data of 500 CDs. Result: 1. We chose the Conquest DICOM Server among 11 open source software used MySQL as a database management system. 2. (1) Comparison of back up and retrieval time (min) showed the result of the following: DVD-RAM (5.13,2.26)/Conquest DICOM Server (1.49,1.19) by GE DSTE (p<0.001), CD (6.12,3.61)/Conquest (0.82,2.23) by GE DLS (p<0.001), CD (5.88,3.25)/Conquest (1.05,2.06) by SIEMENS. (2) The wasted time (sec) to find some data is as follows: CD ($156{\pm}46$), DVD-RAM ($115{\pm}21$) and Conquest DICOM Server ($13{\pm}6$). 3. There was no data loss (0%) for a year and it was stored 12741 PET/CT studies in 1.81 TB memory. In case of CDs, On the other hand, 14 errors among 500 CDs (2.8%) is generated. Conclusions: We found that MicroPACS could be set up with the open source software and its performance was excellent. The system built with open source proved more efficient and more robust than back-up process using CDs or DVD-RAMs. We believe that the operation of the MicroPACS would be effective data storage device as long as its operators develop and systematize it.

• Journal of Intelligence and Information Systems
• /
• v.23 no.4
• /
• pp.147-168
• /
• 2017

There have been many studies on accurate stock market forecasting in academia for a long time, and now there are also various forecasting models using various techniques. Recently, many attempts have been made to predict the stock index using various machine learning methods including Deep Learning. Although the fundamental analysis and the technical analysis method are used for the analysis of the traditional stock investment transaction, the technical analysis method is more useful for the application of the short-term transaction prediction or statistical and mathematical techniques. Most of the studies that have been conducted using these technical indicators have studied the model of predicting stock prices by binary classification - rising or falling - of stock market fluctuations in the future market (usually next trading day). However, it is also true that this binary classification has many unfavorable aspects in predicting trends, identifying trading signals, or signaling portfolio rebalancing. In this study, we try to predict the stock index by expanding the stock index trend (upward trend, boxed, downward trend) to the multiple classification system in the existing binary index method. In order to solve this multi-classification problem, a technique such as Multinomial Logistic Regression Analysis (MLOGIT), Multiple Discriminant Analysis (MDA) or Artificial Neural Networks (ANN) we propose an optimization model using Genetic Algorithm as a wrapper for improving the performance of this model using Multi-classification Support Vector Machines (MSVM), which has proved to be superior in prediction performance. In particular, the proposed model named GA-MSVM is designed to maximize model performance by optimizing not only the kernel function parameters of MSVM, but also the optimal selection of input variables (feature selection) as well as instance selection. In order to verify the performance of the proposed model, we applied the proposed method to the real data. The results show that the proposed method is more effective than the conventional multivariate SVM, which has been known to show the best prediction performance up to now, as well as existing artificial intelligence / data mining techniques such as MDA, MLOGIT, CBR, and it is confirmed that the prediction performance is better than this. Especially, it has been confirmed that the 'instance selection' plays a very important role in predicting the stock index trend, and it is confirmed that the improvement effect of the model is more important than other factors. To verify the usefulness of GA-MSVM, we applied it to Korea's real KOSPI200 stock index trend forecast. Our research is primarily aimed at predicting trend segments to capture signal acquisition or short-term trend transition points. The experimental data set includes technical indicators such as the price and volatility index (2004 ~ 2017) and macroeconomic data (interest rate, exchange rate, S&P 500, etc.) of KOSPI200 stock index in Korea. Using a variety of statistical methods including one-way ANOVA and stepwise MDA, 15 indicators were selected as candidate independent variables. The dependent variable, trend classification, was classified into three states: 1 (upward trend), 0 (boxed), and -1 (downward trend). 70% of the total data for each class was used for training and the remaining 30% was used for verifying. To verify the performance of the proposed model, several comparative model experiments such as MDA, MLOGIT, CBR, ANN and MSVM were conducted. MSVM has adopted the One-Against-One (OAO) approach, which is known as the most accurate approach among the various MSVM approaches. Although there are some limitations, the final experimental results demonstrate that the proposed model, GA-MSVM, performs at a significantly higher level than all comparative models.

• Radiation Oncology Journal
• /
• v.13 no.4
• /
• pp.331-338
• /
• 1995

Purpose : To evaluate our clinical experience with the combination of teletherapy and intraluminal brachytherapy in patients with unresectable or inoperable esophageal cancers. Materials and Methods : From Nov 1989 to Mar 1993, twenty patients with esophageal cancer were treated with radical radiotherapy and intraluminal brachytherapy at Yonsei Cancer Center. All patients had squamous histolgy and stage distribution was as follows: stage II, 4($20{\%}$)patients; III, 15 ($75{\%}$)patients; IV, 1($5{\%}$)patients. A dose of S-12Gy/1-3weeks with intraluminal brachytherapy (3-5Gy/fraction) to 5mm from the outside of the esophageal tube using high dose rate Iridium-192 remotely afterloading brachytherapy machine was given 2 weeks after a total dose of 59-64Gy with external radiotherapy. Induction chemotherapy using cisplatin and 5-FU was performed in 13 patients with median 3 cycles(1-6 cycles), Response rate, local control rate, survival and complications were analysed retrospectively. Results : Two-year overall survival rate and median survival were $15.8{\%}$ and 13.5 months. Response rates were as follows complete remission(CR) 5($25{\%}$): partial remission a(PRa) 7($35{\%}$): partial remission b(PRb) 7($35{\%}$), no response(NR) 1($5{\%}$). Patterns of failure were as follows; local failure 13($65{\%}$), local and distant failure 3($15{\%}$), distant failure 0($0{\%}$). Ultimate local control rate was $20{\%}$. Treatment related complications included esophageal ulcer in two patients and esophageal stricture in one. Conclusion : Though poor local conrol rate, median survival was improved as compared with previous results of radiation therapy alone(8months) and chemoradiation combined treatment(11 months) in Yonsei Cancer Center High-dose-rate intraluminal brachytherapy following external irradiation is an effective treatment modality with acceptable toxicity in esophageal cancer.

• Korean Journal of Soil Science and Fertilizer
• /
• v.18 no.3
• /
• pp.265-275
• /
• 1985

Present studies were carried out to investigate the distribution and formation of organic tiers contained paddy soils in Honam area characteristics to give basic informations on the effective utilization, management and improvement of the soils. The results obtained were summarized as follows; 1. The extent of organic tiers contained paddy soils in Honam area were 6.538㏊ and the amount of peat deposits were presumed about 2.41 million M/T. 2. Out of the total extent of the organic tiers contained paddy soils, about 97.6% was distributed in Honam plains (water-sheds of Mangyeong-Dongjin river), while about 1.5% in the Naju plains (water-sheds of Yeongsan river), and 0.9% in the Wando and Yeocheon areas. 3. The period of peat formation was presumed to be about the early of Seung Moon period (B.C. 4,250), and the Gongdeog series and the Bongnam series were formed in the bog conditions close to the valley mouth of near rolling and hill with small steram channels, and the Gimje series was formed in the out-skirts plains of the Gongdeog and Bongnam soils. 4. In the casue of peat formation, it was presumed to be the Gimje series that accumulated the fibrous peat out of the autochthonous peat such as reeds and grasses etc, to be the Gongdeog and Bongnam series that accumulated the autochtonous peat and the xylem and fibrous peat out of first allochthonous peat. 5. In the Organic horizons of these soils, the range of muck and peat horizons were in 62-68cm and 68-137cm of soil profile in the Gongdeog series, 52-84cm and 84-113cm in the Bongnam series respectively, one of muck horizon was in 46-71cm in the Gimje series. 6. The marks of soil horizons of the soils were expressed that the lower soils than the horizon of muck and peat were formed Cg, Aag for the muck horizon, 0 for the peat horizon, 0 of peat horizon were distingushed with Oag and Oig according to Organic forms. 7. The depthe occurred the muck and peat horizons were positively correlated with the width of local in the Gongdeog series ($r=0.881^{**}$, $r=0.827^{**}$), but not in the Bongnam series and Gimje series.

• Journal of Chest Surgery
• /
• v.41 no.1
• /
• pp.1-11
• /
• 2008

Background: The Damus-Kaye-Stansel (DKS) procedure is a proximal MPA-ascending aorta anastomosis used to relieve systemic ventricular outflow tract obstructions (SVOTO) and pulmonary hypertension. The purpose of this study was to review the indications and outcomes of the DKS procedure, including the DKS pathway and semilunar valve function. Material and Method: A retrospective review of 28 patients who underwent a DKS procedure between May 1994 and April 2006 was performed. The median age at operation was 5.3 months ($13\;days{\sim}38.1\;months$) and body weight was 5.0 kg ($2.9{\sim}13.5\;kg$). Preoperative pressure gradients were $25.3{\pm}15.7\;mmHg$ ($10{\sim}60\;mmHg$). Eighteen patients underwent a preliminary pulmonary artery banding as an initial palliation. Preoperative main diagnoses were double outlet right ventricle in 9 patients, double inlet left ventricle with ventriculoarterial discordance in 6,. another functional univentricular heart in 5, Criss-cross heart in 4, complete atrioventricular septal defect in 3, and hypoplastic left heart variant in 1. DKS techniques included end-to-side anastomosis with patch augmentation in 14 patients, classical end-to-side anastomosis in 6, Lamberti method (double-barrel) in 3, and others in 5. The bidirectional cavopulmonary shunt and Fontan procedure were concomitantly performed in 6 and 2 patients, respectively. Result: There were 4 hospital deaths (14.3%), and 3 late deaths (12.5%) with a follow-up duration of $62.7{\pm}38.9$ months ($3.3{\sim}128.1$ months). Kaplan-Meier estimated actuarial survival was $71.9%{\pm}9.3%$ at 10 years. Multivariate analysis showed right ventricle type single ventricle (hazard ratio=13.960, p=0.004) and the DKS procedure as initial operation (hazard ratio=6.767, p=0.042) as significant mortality risk factors. Four patients underwent staged biventricular repair and 13 received Fontan completion. No SVOTO was detected after the procedure by either cardiac catheterization or echocardiography except in one patient. There was no semiulnar valve regurgitation (>Gr II) or semilunar valve-related reoperation, but one patient (3.6%) who underwent classical end-to-side anastomosis needed reoperation for pulmonary artery stenosis caused by compression of the enlarged DKS pathway. The freedom from reoperation for the DKS pathway and semilunar valve was 87.5% at 10 years after operation. Conclusion: The DKS procedure can improve the management of SVOTO, and facilitate the selected patients who are high risk for biventricular repair just after birth to undergo successful staged biventricular repair. Preliminary pulmonary artery banding is a safe and effective procedure that improves the likelihood of successful DKS by decreasing pulmonary vascular resistance. The long-term outcome of the DKS procedure for semilunar valve function, DKS pathway, and relief of SVOTO is satisfactory.

• Radiation Oncology Journal
• /
• v.22 no.2
• /
• pp.115-123
• /
• 2004

Purpose : This retrospective study was conducted to compare early preliminary results of breast conservation therapy (BCT) with mastectomy In early breast cancer. Materials and Methods : We evaluated 171 women with AJCC stage I and II breast cancer who had been treated at Kangnam St. Mary's Hospital from March 1989 to August 1996. Eighty-eight patients underwent mastectomy and 85 patients did conservative surgery with breast irradiation. in the BCT group, all patients received whole breast irradiation to a total dose of 45$\~$50 Gy/5$\~$6 wks, followed by a boost to the original tumor site at least 60 Gy. Chemotherapy was administered to 29 (34.1$\%$) patients in BCT and 40 (45.5$\%$) in mastectomy, with various sequencing of surgery and/or radiation. We compared survival rate, patterns of failure in each treatment group and the prognostic factors that had a significant effect on treatment failure. The median follow-up time was 63 months (19$\~$111 months). Log rank test was used to estimate the prognostic factors for treatment failure. Results : Overall survival, disease free survival, locoregional recurrence and distant metastasis rates were not significantly different between the two treatment groups. During the follow-up period, 11 patients (12.5$\%$)in the mastectomy group and 10 patients (11.8%$\%$ in the BCT group were failed. Six local recurrences occurred after mastectomy and 5 after BCT Five patients fatted at distant site in mastectomy and 4 in BCT. Of the local recurrence cases, five of 6 mastectomy patients and 3 of S BCT patients were alive with no evidence of disease after salvage surgery and/or chemoirradiation. Our results indicated that the major influence on survival was distant metastasis. Unfortunately, control of distant metastasisis was not frequently achieved. Even with salvage systemic therapy or radiotherapy, most of distant metastasis patients died or had uncontrolled disease in both treatment groups: only one of 4 BCT patients and none of mastectomy patients were alive without disease. There was no apparent difference in the incidence rate of contralateral breast cancer and non-breast 2$^{nd}$ primary tumor between the two treatment groups. Univariate Log-rank test identified the N stage and the involved axillary LN number as distinct prognostic factors that were highly predictive of treatment failure in both treatment groups. Additionally, marginal status in BCT and histologic nuclear grade In the mastectomy group were risk factors for treatment fallure (p < 0.05). Concousion : Although further careful follow-up is necessary to confirm the trends evident In this serles, it would appear that patterns of failure and survival rate following conservative surgery and radiotherapy in early breast cancer are similar to those following mastectomy. The great majority of patients with local recurrence had an exellent salvage rate in both treatment groups. Therefore, these preliminary short term results support BCT as an equally effective management for early breast cancer as an alternative to mastectomy.