OBJECTIVES: Heart failure (HF) is a progressive syndrome that marks the end-stage of heart diseases, and it has a high mortality rate and significant cost burden. In particular, non-adherence of medication in HF patients may result in serious consequences such as hospital readmission and death. This study aims to identify predictors of medication adherence in HF patients. In this work, we applied a Support Vector Machine (SVM), a machine-learning method useful for data classification. METHODS: Data about medication adherence were collected from patients at a university hospital through self-reported questionnaire. The data included 11 variables of 76 patients with HF. Mathematical simulations were conducted in order to develop a SVM model for the identification of variables that would best predict medication adherence. To evaluate the robustness of the estimates made with the SVM models, leave-one-out cross-validation (LOOCV) was conducted on the data set. RESULTS: The two models that best classified medication adherence in the HF patients were: one with five predictors (gender, daily frequency of medication, medication knowledge, New York Heart Association [NYHA] functional class, spouse) and the other with seven predictors (age, education, monthly income, ejection fraction, Mini-Mental Status Examination-Korean [MMSE-K], medication knowledge, NYHA functional class). The highest detection accuracy was 77.63%. CONCLUSIONS: SVM modeling is a promising classification approach for predicting medication adherence in HF patients. This predictive model helps stratify the patients so that evidence-based decisions can be made and patients managed appropriately. Further, this approach should be further explored in other complex diseases using other common variables.
Heart ; Heart Diseases ; Heart Failure ; Humans ; Medication Adherence ; New York ; Patient Compliance ; Patient Readmission ; Support Vector Machine ; Surveys and Questionnaires

PURPOSE: The purpose of this study was to investigate the influence of communication competence and burnout on nursing performance in intensive care units (ICU). METHOD: The participants were 209 nurses from four university hospitals. Measurements included a socio-demographic and job related survey, communication competence inventory, the Maslach burnout inventory and a nursing performance scale. Data were collected from February 6 to 24, 2012, with a self-report questionnaire. The statistical analyses were performed with SPSS 18.0 software. RESULTS: The mean scores for communication competence, burnout and nursing performance were 50.49, 84.72, and 62.18, respectively. Communication competence (r=.44, p<.001) and burn out (r=-.32, p<.001) were significantly correlated with nursing performance. In the multiple linear regression, factors influencing nursing performance were communication competence, age and burnout. These variables explained about 46% of the total variance of nursing performance. Communication competence (beta=.34, p%.001) was the most influential factor. CONCLUSION: Nurses' poor communication skills and burnout can influence the occurrences of medical errors in ICU nursing performance. The results suggest that good communication and burnout resolution skills programs should be implemented to improve nursing performance efficiency.
Burns ; Hospitals, University ; Critical Care ; Intensive Care Units ; Linear Models ; Medical Errors ; Mental Competency ; Surveys and Questionnaires

OBJECTIVES: The purposes of this study were to identify the factors that affect the health-related quality of life (HRQoL) of the elderly with chronic diseases and to subsequently develop from such factors a prediction model to help identify HRQoL risk groups that require intervention. METHODS: We analyzed a set of secondary data regarding 716 individuals extracted from the Korea National Health and Nutrition Examination Survey from 2008 to 2010. The statistical package of SPSS and MATLAB were used for data analysis and development of the prediction model. The algorithms used in the study were the following: stepwise logistic regression (SLR) analysis and machine learning (ML) techniques, such as decision tree, random forest, and support vector machine methods. RESULTS: Five factors with statistical significance were identified for HRQoL in the elderly with chronic diseases: 'monthly income', 'diagnosis of chronic disease', 'depression', 'discomfort', and 'perceived health status.' The SLR analysis showed the best performance with accuracy = 0.93 and F-score = 0.49. The results of this study provide essential materials that will help formulate personalized health management strategies and develop interventions programs towards the improvement of the HRQoL for elderly people with chronic diseases. CONCLUSIONS: Our study is, to our best knowledge, the first attempt to identify the influencing factors and to apply prediction models for the HRQoL of the elderly with chronic diseases by using ML techniques as an alternative and complement to the traditional statistical approaches.
Aged* ; Chronic Disease* ; Complement System Proteins ; Decision Trees ; Humans ; Korea ; Logistic Models ; Machine Learning* ; Nutrition Surveys ; Quality of Life* ; Statistics as Topic ; Support Vector Machine

OBJECTIVES: The aim of this study was to establish a prediction model of medication adherence in elderly patients with chronic diseases and to identify variables showing the highest classification accuracy of medication adherence in elderly patients with chronic diseases using support vector machine (SVM) and conventional statistical methods, such as logistic regression (LR). METHODS: We included 293 chronic disease patients older than 65 years treated at one tertiary hospital. For the medication adherence, Morisky's self-report was used. Data were collected through face-to-face interviews. The mean age of the patients was 73.8 years. The classification process was performed with LR (SPSS ver. 20.0) and SVM (MATLAB ver. 7.12) method. RESULTS: Taking into account 16 variables as predictors, the result of applying LR and SVM classification accuracy was 71.1% and 97.3%, respectively. We listed the top nine variables selected by SVM, and the accuracy using a single variable, self-efficacy, was 72.4%. The results suggest that self-efficacy is a key factor to medication adherence among a Korean elderly population both in LR and SVM. CONCLUSIONS: Medication non-adherence was strongly associated with self-efficacy. Also, modifiable factors such as depression, health literacy, and medication knowledge associated with medication non-adherence were identified. Since SVM builds an optimal classifier to minimize empirical classification errors in discriminating between patient samples, it could achieve a higher accuracy with the smaller number of variables than the number of variables used in LR. Further applications of our approach in areas of complex diseases, treatment will provide uncharted potentials to researchers in the domains.
Aged ; Chronic Disease ; Depression ; Health Literacy ; Humans ; Logistic Models ; Medication Adherence ; Regression Analysis ; Support Vector Machine ; Tertiary Care Centers

BACKGROUND: The aim of this study is to evaluate the effects of local anesthetic distribution on symptoms using ultrasound image after C6 stellate ganglion block (SGB). METHODS: Twenty-six patients underwent SGB via an anterior paratracheal approach at the sixth cervical level using 6 ml of 1% mepivacaine. We divided the patients into two groups by local anesthetic distribution using ultrasound image after SGB. In the group 'sub', injected local anesthetic was beneath the prevertebral fascia. In the group 'supra', some of injected local anesthetic was above the prevertebral fascia. The occurrence of Horner's syndrome, warm sensation on the face and hand, brachial plexus block, hoarseness, and foreign body sensation in the throat were evaluated. The skin temperature of the bilateral thumbs was measured pre and post SGB. RESULTS: The occurrence of hoarseness and the foreign body sensation in the throat was significantly reduced in the group 'sub' than the group 'supra' (P<0.05). The skin temperature of the ipsilateral thumb significantly increased in both groups compared to the pre SGB values, and the change of the skin temperature significantly increased in the group 'sub' than the group 'supra' (P<0.05). CONCLUSIONS: Subfascial distribution of local anesthetic under ultrasound image after SGB reduces the typical complications. It is more effective in the sympathetic block than suprafascial distribution.
Brachial Plexus ; Fascia ; Foreign Bodies ; Hand ; Hoarseness ; Horner Syndrome ; Humans ; Mepivacaine ; Pharynx ; Sensation ; Skin Temperature ; Stellate Ganglion ; Thumb

Endometriosis is the aberrant presence of endometrial tissue outside the uterine cavity. We report a case of cutaneous endometriosis which developed on the scar of a uterine myomectomy in a 35-year-old female. The patient presented with a bean-sized, oval-shaped, erythematous nodule, which was located where a drain tube had been inserted. During her first visit to our clinic, she felt slight pain upon light touch to the lesion. She was not menstruating at this time. The lesion had been getting bigger and she reported that the pain was aggravated during menstruation. Diagnosis was confirmed by histopathologic examination, which showed multiple endometrial glands with decidualized stroma, and hemosiderin pigment. Many dermatologists are not familiar with cutaneous endometriosis. Therefore, we present this case as a good example which shows pathognomonic symptoms and characteristic histopathologic findings of cutaneous endometriosis.
Adult ; Cicatrix ; Diagnosis ; Endometriosis* ; Female ; Hemosiderin ; Humans ; Menstruation ; Uterine Myomectomy

Epidemiologic studies have suggested the association between environmental exposure to volatile organic compounds (VOCs) and polycyclic aromatic hydrocarbons (PAHs) and the increased risk of incurring asthma. Yet there is little data regarding the relationship between personal exposure to air pollution and the incidence of asthma in children. This study was designed to evaluate the effect of exposure to air pollution on children with asthma by using exposure biomarkers. We assessed the exposure level to VOCs by measuring urinary concentrations of hippuric acid and muconic acid, and PAHs by 1-OH pyrene and 2-naphthol in 30 children with asthma and 30 children without asthma (control). The mean level of hippuric acid was 0.158+/-0.169micromol/mol creatinine in the asthma group and 0.148+/-0.249micromol/mol creatinine in the control group, with no statistical significance noted (p=0.30). The mean concentration of muconic acid was higher in the asthma group than in the control group (7.630+/-8.915micromol/mol creatinine vs. 3.390+/-4.526micromol/mol creatinine p=0.01). The mean level of urinary 1-OHP was higher in the asthma group (0.430+/-0.343micromol/mol creatinine) than the control group (0.239+/-0.175micromol/mol creatinine), which was statistically significant (p=0.03). There was no difference in the mean concentration of 2-NAP between the two groups (9.864+/-10.037micromol/mol in the asthma group vs. 9.157+/-9.640micromol/mol in the control group, p=0.96). In conclusion, this study suggests that VOCs and PAHs have some role in asthma.
Air Pollutants/*pharmacology ; Asthma/*physiopathology/urine ; Case-Control Studies ; Child, Preschool ; Creatinine/urine ; Female ; Hippurates/urine ; Humans ; Male ; Naphthols/urine ; Organic Chemicals/chemistry/*pharmacology ; Polycyclic Hydrocarbons, Aromatic/*pharmacology ; Pyrenes/metabolism ; Sorbic Acid/*analogs & derivatives/metabolism ; Volatilization

Although laryngomalacia is the most common cause of congenital stridor in infancy, it is a benign, self-limited disease which usually resolves by the age of 18 months with no long- term sequelae. Nevertheless, infants who suffered from recurrent stridor and respiratory distress should be evaluated for other causes of stridor such as cardiopulmonary anomalies. We report 3 cases of infants who had recurrent stridor and respiratory distress from their early infancy. Case 1 had a double aortic arch and a tracheomalacia, case 2 had a hypoplasia of the right lung, and case 3 had a horseshoe lung as well as scimitar syndrome. Physicians should be alert for the possibility of the congenital cardiopulmonary abnormalities in infants with recurrent stridor and/or respiratory distress.
Aorta, Thoracic ; Dyspnea ; Humans ; Infant ; Laryngomalacia ; Lung ; Respiratory Sounds ; Scimitar Syndrome ; Tracheomalacia

PURPOSE: Nurses' knowledge regarding advance directives may affect their administration of and confidence towards end of life care. This study aimed to describe the relationships of knowledge, confidence, and learning needs with advance directives among hospital nurses.METHOD: This cross-sectional study was performed at a tertiary university hospital in Seoul between September 25 and October 14, 2017. Convenience sampling was used to recruit nurses who provided bedside care and had at least 1 year of clinical experience. We used a validated self-report questionnaire.RESULTS: The mean score of knowledge, confidence and learning needs were 5.00±1.73, 29.81±7.52, and 64.54±8.48 respectively. Hospital nurses' knowledge, confidence and learning needs were significantly different according to age, job position, educational level and perceived advance directives. Knowledge regarding advance directives was significantly associated with confidence (r = .27, p < .001) and learning needs (r = .16, p = .005).CONCLUSION: Knowledge regarding advance directives was relatively low compared to the findings of previous studies. Therefore, nurses should be knowledgeable and encouraged to initiate advance directives. It is necessary to develop a standardized educational program regarding advance directives based on Korean cultures.
Advance Directives ; Cross-Sectional Studies ; Learning ; Methods ; Seoul ; Terminal Care

Human sparganosis is a zoonotic disease caused by infection and migration of the plerocercoid of Spirometra spp. Although sparganosis were reported from most parts of the body, the sparganum parasitizing inside cerebral artery is remarkably uncommon. We report a case of cerebral intravascular sparganosis in an elderly patient with acute ischemic stroke who was diagnosed by retrieving sparganum during mechanical thrombectomy. Finally, the parasites were identified as Spirometra erinaceieuropaei using multiplex PCR and cox1 gene sequencing.