• 한국노년학
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• v.41 no.3
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• pp.295-308
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• 2021

This study is a descriptive study conducted to find out the predictive factors according to the level of the frailty of the communitydwelling older adult in a rural area. Data were collected from 400 older adults aged 65 years or older living in rural areas of Gyeongsangnam-do from October 2019 to March 2020. Data were analyzed using logistic regression to examine the predictive factors according to the level of frailty. The results showed that 27.8% for robust older adults, 30.9% for pre-frailty older adults, and 41.3% for frailty older adults. As a result of analyzing the predictive factors according to the level of frailty, the predictors from the robust stage to the pre-frailty stage were grip strength, nutritional status, and depression. The predictive factors for entering the pre-frailty stage into the frailty stage were gender, nutritional status, physical performance ability, and depression. Also, it was found that the predictive factors for entering from the robust stage to the frailty stage were sex, occupation, nutritional status, physical performance ability, and depression. Through this study, it was possible to understand the level of the frailty of the older adults living in rural communities and the effects of multidimensional variables. These results can be used as basic data necessary to find a way to prevent and manage the progression of frailty among older adults in rural areas.

• Journal of Power Electronics
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• v.11 no.1
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• pp.64-73
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• 2011

The stability of PWM rectifiers with a deadbeat current controller is seriously influenced by computation time delays and low-pass filters inserted into the current-sampling circuit. Predictive current control is often adopted to solve this problem. However, grid current predictive precision is affected by many factors such as grid voltage estimated errors, plant model mismatches, dead time and so on. In addition, the predictive current error aggravates the grid current distortion. To improve the grid current predictive precision, an improved deadbeat current controller with a repetitive-control-based observer to predict the grid current is proposed in this paper. The design principle of the proposed observer is given and its stability is discussed. The predictive performance of the observer is also analyzed in the frequency domain. It is shown that the grid predictive error can be decreased with the proposed method in the related bode diagrams. Experimental results show that the proposed method can minimize the current predictive error, improve the current loop robustness and reduce the grid current THD of PWM rectifiers.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.9
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• pp.4503-4506
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• 2016

Background: Lymph node and distant metastases are known as the prognostic factor in renal cell carcinoma (RCC). Clinical parameters are needed to predict metastases preoperatively. The aim of this study was to assess clinical predictive factors for lymph node and distant metastases. Materials and Methods: We collected RCC data from January 1995 until December 2015 at Cipto Mangunkusumo hospital in Jakarta. We only reviewed data that had renal cell carcinoma histopathology by operation or biopsy. Clinical information such as patient age, gender, hemoglobin (Hb), erythrocyte sedimentation rate (ESR), and tumor size (clinical T stage) were reviewed and analyzed by Chi-squre and logistic regression to establish clinical predictive value. Results: A total of 102 patients were reviewed. There were 32 (31.4%) with lymph node metastases and 27 (26.5%) with distant metastases. Age, Hb and clinical T staging were associated with nodal metastases. However, only Hb and clinical T staging were found to be associated with distant metastases. By logistic regression, we found T3-4 in clinical T-stage to be the only predictor of nodal metastases (OR 5.14; 1.87 - 14.09) and distant metastases (OR 3.42; 1.27 - .9.23). Conclusions: Clinical T-stages of T3 and T4 according to The AJCC TNM classification could be used as independent clinical predictive factors for lymph node or distant metastases in patients with RCC.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.1
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• pp.159-163
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• 2013

Background: This study used Surveillance, Epidemiology and End Results (SEER) pancreatic cancer data to identify predictive models and potential socio-economic disparities in pancreatic cancer outcome. Materials and Methods: For risk modeling, Kaplan Meier method was used for cause specific survival analysis. The Kolmogorov-Smirnov's test was used to compare survival curves. The Cox proportional hazard method was applied for multivariate analysis. The area under the ROC curve was computed for predictors of absolute risk of death, optimized to improve efficiency. Results: This study included 58,747 patients. The mean follow up time (S.D.) was 7.6 (10.6) months. SEER stage and grade were strongly predictive univariates. Sex, race, and three socio-economic factors (county level family income, rural-urban residence status, and county level education attainment) were independent multivariate predictors. Racial and socio-economic factors were associated with about 2% difference in absolute cause specific survival. Conclusions: This study s found significant effects of socio-economic factors on pancreas cancer outcome. These data may generate hypotheses for trials to eliminate these outcome disparities.

• Korean Journal of Construction Engineering and Management
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• v.9 no.6
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• pp.268-276
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• 2008

In highway construction projects, concrete pavement productivity has been challenged with constructors and decision-makers; at present there are few methods available to accurately evaluate the factors impacting on it. Any inefficient method to analyze it leads to the excessive schedule, higher rehabilitation costs, shorter service life, and reduction of ride quality. To implement these negative outcomes, constructors or decision-makers need a systematic tool that can be used to categorize the factors related to construction productivity. This paper applies multiple regression technique for productivity analysis of the Jointed Plane Concrete Pavement (JPCP), identifies the significant factors, and provides a predictive model assisting in monitoring and managing the productivity of the JPCP construction process. The completed and progressive projects are employed to derive and assess the proposed model. The results are analyzed to illustrate its capabilities.

• Journal of Korean Academy of Nursing
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• v.40 no.2
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• pp.264-276
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• 2010

Purpose: The purpose of this study was to propose and to test a predictive model that could explain and predict the health promotion behavior of obese school-age children in Korea. Methods: Participants for this study were 365 students from 13 elementary schools located in Jeonbuk Province, Korea. The data were analyzed using SPSS 15.0 program and Amos 7.0 program. Results: The results verified the factors that influence health promotion behavior of the participants. Important direct factors were prior health-related behavior, perceived self-efficacy, and commitment to a plan of action and indirect factors were perceived barrier and activity-related effect. These factors explained 75.3% of variance in the participants' health promotion behavior. The proposed model was concise and extensive in predicting health promotion behavior of the participants. Conclusion: Findings may provide useful assistance in developing effective nursing interventions for maintaining and promoting health promotion behavior in obese school-age children.

• Research in Community and Public Health Nursing
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• v.17 no.2
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• pp.253-262
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• 2006

Purpose: This study was done to evaluate the predictive factors of smoking cessation intention of smoking adolescents at H. district in Chungchungnam-do. Method: A convenience sample was recruited from a public health center at H. district in Chungchungnam-do. A total of 100 smoking adolescents were enrolled in this study. A self-report survey method was used to identify the predictive factors related to smoking cessation. Result: A forward stepwise logistic regression analysis identified four factors associated with smoking cessation intention of smoking adolescents: accompanied friends during the smoking cessation program (OR=20.14), preparation for smoking cessation (OR=5.12), smoking cessation knowledge after the smoking cessation program (OR=1.41), and the number of cigarettes (OR=0.15). Conclusion: Based on this study results, the effective programs in reducing adolescent smoking rates should include components to accompany peers, increase the knowledge of smoking impact, and the benefit of smoking cessation.

• Toxicological Research
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• v.28 no.2
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• pp.81-91
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• 2012

Many risk factors exist for chemotherapy-induced nausea and vomiting (CINV). This study utilized a multivariate projection technique to identify which risk factors were predictive of CINV in clinical practice. A single-centre, prospective, observational study was conducted from January 2007~July 2010 in Singapore. Patients were on highly (HECs) and moderately emetogenic chemotherapies with/without radiotherapy. Patient demographics and CINV risk factors were documented. Daily recording of CINV events was done using a standardized diary. Principal component (PC) analysis was performed to identify which risk factors could differentiate patients with and without CINV. A total of 710 patients were recruited. Majority were females (67%) and Chinese (84%). Five risk factors were potential CINV predictors: histories of alcohol drinking, chemotherapy-induced nausea, chemotherapy-induced vomiting, fatigue and gender. Period (ex-/current drinkers) and frequency of drinking (social/chronic drinkers) differentiated the CINV endpoints in patients on HECs and anthracycline-based, and XELOX regimens, respectively. Fatigue interference and severity were predictive of CINV in anthracycline-based populations, while the former was predictive in HEC and XELOX populations. PC analysis is a potential technique in analyzing clinical population data, and can provide clinicians with an insight as to what predictors to look out for in the clinical assessment of CINV. We hope that our results will increase the awareness among clinician-scientists regarding the usefulness of this technique in the analysis of clinical data, so that appropriate preventive measures can be taken to improve patients' quality of life.

• Journal of Korean Biological Nursing Science
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• v.19 no.3
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• pp.123-130
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• 2017

Purpose: This study aimed to identify factors influencing intra-operative core body temperature (CBT), and to develop a predictive model for intra-operative CBT in laparoscopic abdominal surgery. Methods: The prospective observational study involved 161 subjects, whose age, weight, and height were collected. The basal pre-operative CBT, pre-operative blood pressure, and heartbeat were measured. CBT was measured 1 hour and 2 hours after pneumoperitoneum. Results: Explanatory factors of intra-operative hypothermia (< $36^{\circ}C$) were weight (${\beta}=.361$, p< .001) and pre-operative CBT (${\beta}=.280$, p= .001) 1 hour after pneumoperitoneum (Adjusted $R^2=.198$, F= 7.56, p< .001). Weight was (${\beta}=.423$, p< .001) and pre-operative CBT was (${\beta}=.206$, p= .011) 2 hours after pneumoperitoneum (Adjusted $R^2=.177$, F= 5.93, p< .001). The researchers developed a predictive model for intra-operative CBT ($^{\circ}C$) by observing intra-operative CBT, body weight, and pre-operative CBT. The predictive model revealed that intra-operative CBT was positively correlated with body weight and pre-operative CBT. Conclusion: Influence of weight on intra-operative hypothermia increased over time from 1 hour to 2 hours after pneumoperitoneum, whereas influence of pre-operative CBT on intraoperative hypothermia decreased over time from 1 hour to 2 hours after pneumoperitoneum. The research recommends pre-warming for laparoscopic surgical patients to guard against intra-operative hypothermia.

• Korean Journal of Adult Nursing
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• v.23 no.5
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• pp.460-471
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• 2011

Purpose: This study was designed to investigate the levels of anxiety, depression, physical symptoms, and supportive care needs in patients with hematologic malignancy and to identify predictive factors of supportive care needs. Methods: The data were collected from 100 subjects undergoing treatments during 2010 in Korea. The questionnaires included the Hospital Anxiety-Depression Scale, the M. D. Anderson Symptom Inventory, and the Supportive Care Needs Survey-Short Form 34. The data were analyzed using descriptive statistics, t-test, ANOVA, Pearson correlation, and stepwise multiple regression. Results: Forty percent of the subjects had anxiety and 58% had depression. Thirty-eight percent of the subjects reported to have moderate-to-severe levels of physical symptoms. The most severe physical symptom was lack of appetite, followed by fatigue and pain. In terms of supportive care needs, the health system and information domain showed the highest among all domains. Supportive care needs had a significant positive correlation with anxiety, depression, and physical symptoms. And its predictive factors were identified as anxiety, physical symptoms and marital status, with the explanatory power of 48.9%. Conclusion: These findings demonstrate that anxiety and physical symptoms should be assessed and treated to meet the supportive care needs of patients with hematologic malignancies.