• Journal of the Korean Data and Information Science Society
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• v.22 no.2
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• pp.217-225
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• 2011

It is important to find risk factors associated with mental disorder. Also the hazard ratio that represent the relationship of risk factors with illness is main interest in medicine. Thus we used odds ratio to explore the relationship between mental disorder and risk factors. On this paper, when we applied Bayesian network to delirium of mental disorder, we selected major risk factors and calculated odds ratio. Especially we identified odds ratio of single risk factors and multiple risk factors.

• The Korean Journal of Applied Statistics
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• v.24 no.2
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• pp.323-333
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• 2011

We analyzed using logistic to find factors with a mental disorder because logistic is the most efficient way assess risk factors. In this paper, we applied data mining techniques that are logistic, neural network, c5.0, cart and Bayesian network to delirium data. The Bayesian network method was chosen as the best model. When delirium data were applied to the Bayesian network, we determined the risk factors associated with delirium as well as identified the network between the risk factors.

• Journal of the Korean Data and Information Science Society
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• v.22 no.6
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• pp.1257-1264
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• 2011

Delirium is a neuropsychiatric disorder accompanying symptoms of hallucination, drowsiness, and tremors. It has high occurrence rates among elders, heart disease patients, and burn patients. It is a medical emergency associated with increased morbidity and mortality rates. That s why early detection and prevention of delirium ar significantly important. And This mental illness like delirium occurred by complex interaction between risk factors. In this paper, we identify risk factors and interactions between these factors for delirium using multi-factor dimensionality reduction (MDR) method.

• Journal of the Korean Data and Information Science Society
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• v.22 no.5
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• pp.911-919
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• 2011

In recent medical analysis, it becomes more important to looking for risk factors related to mental illness. If we find and identify their relevant characteristics of the risk factors, the disease can be prevented in advance. Moreover, the study can be helpful to medical development. These kinds of studies of risk factors for mental illness have mainly been discussed by using the logistic regression model. However in this paper, data mining techniques such as CART, C5.0, logistic, neural networks and Bayesian network were used to search for the risk factors. The Bayesian network of the above data mining methods was selected as most optimal model by applying delirium data. Then, Bayesian network analysis was used to find risk factors and the relationship between the risk factors are identified through a radial graph.

• Korean Journal of Psychosomatic Medicine
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• v.19 no.1
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• pp.28-33
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• 2011

Objective: This study aimed to investigate the pattern of psychiatric consultation-liaison in a new general hospital over a 5-year period. Method: Retrospective chart review was conducted for psychiatric consultations performed from May 2004 to December 2008 in a new general hospital in Hwasun, Korea. Results: A total of 1,852 patients who were referred to the Department of Psychiatry for consultation were included in the analysis. The main reasons for psychiatric consultation were changes in mental status(20.5%), depression(16.8%), insomnia(12.8%), and anxiety(7.9%). Psychiatric consultations were conducted with diagnoses of delirium(39.7%), depressive disorder(28.2%), adjustment disorder(7.9%), and anxiety disorder(4.1%). Patients with delirium were significantly older than were those with other psychiatric diagnoses(p<0.001). Delirium was more common in male patients than in female patients(47.1% vs. 29.9%, respectively), and depression was more common in female patients than in male patients(48.3% vs. 33.9%, respectively)(p<0.001). Delirium was more common in patients who underwent surgical operation than those who did not(p=0.010). Conclusion: Delirium was the most common diagnosis for psychiatric consultation followed by depression in a university hospital. Delirium was more prevalent in men than in women, while depression was more common in women.

• Journal of Korean Academy of Nursing
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• v.53 no.4
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• pp.371-384
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• 2023

Purpose: With an increase in the aging population, the number of patients with degenerative spinal diseases undergoing surgery has risen, as has the incidence of postoperative delirium. This study aimed to investigate the risk factors affecting postoperative delirium in older adults who had undergone spine surgery and to identify the associated biomarkers. Methods: This study is a prospective study. Data of 100 patients aged ≥ 70 years who underwent spinal surgery were analyzed. Demographic data, medical history, clinical characteristics, cognitive function, depression symptoms, functional status, frailty, and nutritional status were investigated to identify the risk factors for delirium. The Confusion Assessment Method, Delirium Rating Scale-R-98, and Nursing Delirium Scale were also used for diagnosing delirium. To discover the biomarkers, urine extracellular vesicles (EVs) were analyzed for tau, ubiquitin carboxy-terminal hydrolase L1 (UCH-L1), neurofilament light, and glial fibrillary acidic protein using digital immunoassay technology. Results: Nine patients were excluded, and data obtained from the remaining 91 were analyzed. Among them, 18 (19.8%) developed delirium. Differences were observed between participants with and without delirium in the contexts of a history of mental disorder and use of benzodiazepines (p = .005 and p = .026, respectively). Tau and UCH-L1-concentrations of urine EVs-were comparatively higher in participants with severe delirium than that in participants without delirium (p = .002 and p = .001, respectively). Conclusion: These findings can assist clinicians in accurately identifying the risk factors before surgery, classifying high-risk patients, and predicting and detecting delirium in older patients. Moreover, urine EV analysis revealed that postoperative delirium following spinal surgery is most likely associated with brain damage.

• Korean Journal of Biological Psychiatry
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• v.14 no.2
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• pp.99-105
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• 2007

Objectives : The purpose of present study was to investigate the effect, safety and tolerability of risperdal sachet(oral solution) with lorazepam tablet versus intramuscular haloperidol and lorazepam injection for management of acute psychotic symptom in the elderly with organic mental disorder. Methods : Total 37 patients who have dementia, medical or physical diseases, associated with acute psychotic symptom were randomly assigned to oral treatment with 1mg of risperdal sachet(oral solution) plus 1mg of lorazepam(N=17) or to intramuscular treatment with 2.5mg of haloperidol plus 2mg of lorazepam (N=20). The change of CGI scores was used for the evaluation of efficacy. Results : Mean score improvements at 15, 30, 60, and 120 minutes after treatment were statistically significant at each time point in both groups(p<0.001) and were similar in both groups(p=0.189). Conclusion : A single oral dose of risperdal sachet(oral solution) plus lorazepam was as effective and tolerable as parenterally administered haloperidol plus lorazepam for the rapid control of acute psychotic symptom in the elderly with organic mental disorder.

• Journal of Korean Critical Care Nursing
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• v.13 no.3
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• pp.62-74
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• 2020

Purpose : This study aimed to investigate the prevalence and risk factors of mental health problems in patients discharged from the intensive care unit (ICU). Methods : This was a secondary analysis study using data from a multicenter prospective cohort of post-ICU patients. We analyzed data of 311 patients enrolled in the primary cohort study who responded to the mental health questionnaire three months after the discharge. Anxiety and depression were measured on the Hospital Anxiety-Depression Scale, and post-traumatic stress disorder (PTSD) was measured on the Posttraumatic Diagnostic Scale. Results : The prevalence of anxiety, depression, and PTSD in patients at three months after ICU discharge were 25.7%, 17.4%, and 18.0%, respectively, and 7.7% of them experienced all three problems. Unemployment (OR=1.99, p=.033) and unplanned ICU admission (OR=2.28, p=.017) were risk factors for depression, while women gender (OR=2.34, p=.009), comorbid diseases (OR=2.88, p=.004), non-surgical ICUs (trauma ICU: OR=7.31, p=.002, medical ICU: OR=3.72, p=.007, neurological ICU: OR=2.95, p=.019) and delirium (OR=2.89, p=.009) were risk factors for PTSD. Conclusion : ICU nurses should proactively monitor risk factors for post-ICU mental health problems. In particular, guidelines on the detection and management of delirium in critically ill patients should be observed.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.4
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• pp.137-144
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• 2020

Delirium is among the most common mental disorders encountered in patients with a temporary cognitive impairment such as consciousness disorder, attention disorder, and poor speech, particularly among those who are older. Delirium is distressing for patients and families, can interfere with the management of symptoms such as pain, and is associated with increased elderly mortality. The purpose of this paper is to generate useful clinical knowledge that can be used to distinguish the outcomes of patients with delirium in long-term care facilities. For this purpose, we extracted the clinical classification knowledge associated with delirium using a local covering rule acquisition approach with the rough lower approximation region. The clinical applicability of the proposed method was verified using data collected from a prospective cohort study. From the results of this study, we found six useful clinical pieces of evidence that the duration of delirium could more than 12 days. Also, we confirmed eight factors such as BMI, Charlson Comorbidity Index, hospitalization path, nutrition deficiency, infection, sleep disturbance, bed scores, and diaper use are important in distinguishing the outcomes of delirium patients. The classification performance of the proposed method was verified by comparison with three benchmarking models, ANN, SVM with RBF kernel, and Random Forest, using a statistical five-fold cross-validation method. The proposed method showed an improved average performance of 0.6% and 2.7% in both accuracy and AUC criteria when compared with the SVM model with the highest classification performance of the three models respectively.

• Journal of Korean Critical Care Nursing
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• v.9 no.1
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• pp.1-14
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• 2016

Purpose: To investigate the post-intensive care syndrome (PICS) and to analyze the factors affecting the quality of life (QoL) of survivors of critical illness. Methods: Subjects were 114 outpatients who had been discharged from intensive care units of a university hospital in B city, Korea. From July 30 through September 30, 2015, PICS was assessed using the Korean Montreal Cognitive Assessment, Hospital Anxiety-Depression Scale, Korean Instrumental/Activities of Daily Living (K-I/ADL) index, and handwriting transformation, while physical and mental health-related QoL was measured using the SF-12. Results: Of the subjects, 39.5% were screened for mild cognitive disorder and 23.7% experienced handwriting transformation after discharge. Multiple regression analysis revealed that restraint application, current job, time of ${\geq}36$ months after discharge, depression, anxiety, and handwriting transformation accounted for 40.9% of the physical health-related QoL, and depression, anxiety and experience of delirium accounted for 62.4% of the mental health-related QoL. Conclusions: It is necessary to make efforts to reduce restraint application in intensive care units and prevent the occurrence of delirium, with the objective of reducing PICS and improving the QoL of critical illness survivors.