BACKGROUND AND OBJECTIVES: Heart rate variability has been known to be a prognostic factor of heart disease. However, determinants of heart rate variability in general korean population without clinical heart disease have not been studied. Objectives of this study were to measure heart rate variability in general population and to investigate clinical determinants of heart rate variability. METHODS:Heart rate variability measures were obtained by LRR-03TM and MemCalcTM software (GMS, Tokyo, Japan) from public officials in a district of Seoul and their families(n=69). Predictors of heart rate variability included age, gender, heart rate, smoking status, systolic blood pressure, diastolic blood pressure, serum total cholesterol, HDL-cholesterol. Univariate analysis and analysis of variance of low frequency power(0.04-0.15 Hz), high frequency power(0.15-0.30 Hz), and total power spectrum in relation to explanatory variables were done. In order to select determinants of heart rate variability, multiple linear regression model of each heart rate variability measure was created and stepwise selection method was applied. RESULTS: Analysis of variance showed that older age, higher heart rate, body mass index > or =27, systolic blood pressure > or =140 mmHg, diastolic blood pressure > or =90 mmHg, and serum total cholesterol > or =240 mg/dl were negatively associated with one or more heart rate variability measures. Serum HDL-cholesterol > or =35 mg/dl was positively associated with low and high frequency power. Multiple linear regression analyses showed that age and heart rate were the major determinants, gender and cardiovascular risk factors such as diastolic blood pressure, HDL-cholesterol, and smoking contributed to one or more heart rate variability measures. CONCLUSIONS: Age, heart rate, gender, and cardiovascular risk factors must be considered when evaluating heart rate variability.
Blood Pressure ; Body Mass Index ; Cholesterol ; Heart Diseases ; Heart Rate* ; Heart* ; Linear Models ; Risk Factors ; Seoul ; Smoke ; Smoking

PURPOSE: We wanted to further analyze the qualities that influence Korean medical students on their decision to choose each of the specialized areas of medicine. METHODS: We were able to obtain questionnaires from 394 students of Y University, School of Medicine. The students rated the various influential factors for specialty selection by using a five-point Likert scale. RESULTS: The factors found to influence the selection of popular specialties were gender, grades/scores, lifestyle attributes, and residency issues. Patient contact, lifestyle attributes, prospects, income prospects, and health care policies were significantly rated factors for choosing clinical-oriented specialties. For the selection of Medical specialties, gender, income, social responsibilities, income prospects, and malpractice insurance costs were the influential factors. Gender, 3rd year students, social responsibilities, prospects, income prospects, and society's views on medical profession affected the students' decisions to choose the major specialties. CONCLUSION: Based on the results of our study, we can conclude that gender and income prospects are some of the most significant factors affecting a student's selection of a specialty. These results suggest reform and improvement for a more stable health care policy and management strategies.
Delivery of Health Care ; Humans ; Insurance ; Internship and Residency ; Life Style ; Malpractice ; Social Responsibility ; Students, Medical* ; Surveys and Questionnaires

Effect of shift work on worker's health, family and social life was investigated at a automobile manufacturing plant in Inchon. In total, 2488 shift workers and 599 non-shift workers completed self administered questionnaire in their sleep pattern, subjective gastrointestinal symptoms, prevalent chronic disease status, general well-being schedule, family and social life. More shift workers complained of sleep disturbance, poor sleep quality, tiredness at awakening, and sleepiness in work than non-shift workers. More shift workers also complained of gastrointestinal disturbance than non-shift workers. Worker's mental health was assessed by General Well-Being Schedule(GWB) questionnaire developed for the U.S. Health and Nutrition Examination Surveys(HANES I). The percentage of severely distressed shift workers was significantly higher than that of non-shift workers(p<0.01). Among subscores in General Well-Being Schedule, anxiety, depression, positive well-being, vitality, and general health subscale of shift workers were lower than those of non-shift workers (p<0.05). In terms of family and social life, there was no significant difference between two groups. Multiple logistic regression analysis was done for discrete variables which showed statistically significant difference between shift and non-shift group. The variables included in analysis were sleep disturbance symptoms, gastrointestinal complaints, and distress level calculated from GWB score. Age, tenure, smoking, alcohol drinking, and exercise were adjusted as confounding factors and odds ratios for above symptoms due to shift work were calculated. Odds ratios (ORs) for sleep disturbance symptoms ranged from 0.52 to 3.59. ORs for gastrointestinal complaints ranged from 1.19 to 1.34. OR for distress level was 1.31. We concluded that shift workers are suffered from physical and psychological ailments due to shift work and interventional methods for preventing worker's health from adverse effects of shift work are needed.
Alcohol Drinking ; Anxiety ; Appointments and Schedules ; Automobiles* ; Chronic Disease ; Depression ; Family Health* ; Humans ; Incheon ; Logistic Models ; Mental Health ; Odds Ratio ; Plants* ; Questionnaires ; Smoke ; Smoking

Background: To propose fully automatic segmentation of left atrium using active learning with limited dataset in late gadolinium enhancement in cardiac magnetic resonance imaging (LGE-CMRI). Methods: An active learning framework was developed to segment the left atrium in cardiac LGE-CMRI. Patients (n = 98) with atrial fibrillation from the Korea University Anam Hospital were enrolled. First, 20 cases were delineated for ground truths by two experts and used for training a draft model. Second, the 20 cases from the first step and 50 new cases, corrected in a human-in-the-loop manner after predicting using the draft model, were used to train the next model; all 98 cases (70 cases from the second step and 28 new cases) were trained. An additional 20 LGE-CMRI were evaluated in each step. Results: The Dice coefficients for the three steps were 0.85 ± 0.06, 0.89 ± 0.02, and 0.90 ± 0.02, respectively. The biases (95% confidence interval) in the Bland-Altman plots of each step were 6.36% (−14.90–27.61), 6.21% (−9.62–22.03), and 2.68% (−8.57–13.93). Deep active learning-based annotation times were 218 ± 31 seconds, 36.70 ± 18 seconds, and 36.56 ± 15 seconds, respectively. Conclusion Deep active learning reduced annotation time and enabled efficient training on limited LGE-CMRI.

PURPOSE: A numerical method of designing a multiple quantum filter (MQF) is presented for the optimum detection of myo-inositol (mI), an important brain metabolite, by using in vivo proton nuclear magnetic resonance spectroscopy ((1)HMRS). MATERIALS AND METHODS: Starting from the characterization of the metabolite, the filter design includes the optimization of the sequence parameters such as the two echo times (TEs), the mixing time (TM), and the flip angle and offset frequency of the 3rd 90 degrees pulse which converts multiple quantum coherences (MQCs) back into single quantum coherences (SQCs). The optimized filter was then tested both in phantom and in human brains. RESULTS: The results demonstrate that the proposed MQF can improve the signal-tobackground ratio of the target metabolite by a factor of more than three by effectively suppressing the signal from the background metabolites. CONCLUSION: By incorporating a numerical method into the design of MQFs in 1HMRS the spectral integrity of a target metabolite, in particular, with a complicated spin system can be substantially enhanced.
Brain ; Humans ; Magnetic Resonance Spectroscopy ; Protons ; Spectrum Analysis

Objective: To assess the effect of left atrial appendage (LAA) isolation on LAA emptying and left atrial (LA) function using cardiac MRI in patients who underwent successful catheter ablation of atrial fibrillation (AF). Materials and Methods: This retrospective study included 84 patients (mean age, 59 ± 10 years; 67 males) who underwent cardiac MRI after successful catheter ablation of AF. According to the electrical activity of LAA after catheter ablation, patients showed either LAA isolation or LAA normal activity. The LAA emptying phase (LAA-EP, in the systolic phase [SP] or diastolic phase), LAA emptying flux (LAA-EF, mL/s), and LA ejection fraction (LAEF, %) were evaluated by cardiac MRI. Results: Of the 84 patients, 61 (73%) and 23 (27%) patients showed LAA normal activity and LAA isolation, respectively.Incidence of LAA emptying in SP was significantly higher in LAA isolation (91% vs. 0%, p < 0.001) than in LAA normal activation. LAA-EF was significantly lower in LAA isolation (40.1 ± 16.2 mL/s vs. 80.2 ± 25.1 mL/s, pp < 0.001) than in LAA normal activity. Furthermore, LAEF was significantly lower in LAA isolation (23.7% ± 11.2% vs. 31.1% ± 16.6%, p = 0.04) than in LAA normal activity. Multivariate analysis demonstrated that the LAA-EP was independent from LAEF (p = 0.01). Conclusion LAA emptying in SP may be a critical characteristic of LAA isolation, and it may adversely affect the LAEF after catheter ablation of AF.

Objective: To assess the effect of left atrial appendage (LAA) isolation on LAA emptying and left atrial (LA) function using cardiac MRI in patients who underwent successful catheter ablation of atrial fibrillation (AF). Materials and Methods: This retrospective study included 84 patients (mean age, 59 ± 10 years; 67 males) who underwent cardiac MRI after successful catheter ablation of AF. According to the electrical activity of LAA after catheter ablation, patients showed either LAA isolation or LAA normal activity. The LAA emptying phase (LAA-EP, in the systolic phase [SP] or diastolic phase), LAA emptying flux (LAA-EF, mL/s), and LA ejection fraction (LAEF, %) were evaluated by cardiac MRI. Results: Of the 84 patients, 61 (73%) and 23 (27%) patients showed LAA normal activity and LAA isolation, respectively.Incidence of LAA emptying in SP was significantly higher in LAA isolation (91% vs. 0%, p < 0.001) than in LAA normal activation. LAA-EF was significantly lower in LAA isolation (40.1 ± 16.2 mL/s vs. 80.2 ± 25.1 mL/s, pp < 0.001) than in LAA normal activity. Furthermore, LAEF was significantly lower in LAA isolation (23.7% ± 11.2% vs. 31.1% ± 16.6%, p = 0.04) than in LAA normal activity. Multivariate analysis demonstrated that the LAA-EP was independent from LAEF (p = 0.01). Conclusion LAA emptying in SP may be a critical characteristic of LAA isolation, and it may adversely affect the LAEF after catheter ablation of AF.

Purpose: The aim of this study is to demonstrate the association between recurrent atrial fibrillation (AF) and left ventricular (LV) adverse remodeling after catheter ablation and to evaluate the change of myocardial extracellular volume fraction (ECV) by catheter ablation outcomes. Materials and Methods: We retrospectively recruited 60 patients (44 men and 16 women) with a median age of 57 years (range, 32–78 years) who underwent cardiac MRI before and at 6–12 months after catheter ablation of AF. Cardiac MRI quantified myocardial ECV (%) in the left ventricle. Depending on myocardial ECV after catheter ablation, patients were divided into two groups: 1) LV adverse remodeling with ECV ≥ 28%; and 2) no adverse LV remodeling with ECV < 28%. Multivariable analysis was performed to assess the association between recurrent AF and LV remodeling. Results: Of 60 patients, 21 (35%) were in the LV adverse remodeling group (mean ECV ± standard deviation [SD]: 29.8% ± 1.4%) and 39 (65%) were in the no adverse LV remodeling group (mean ECV ± SD: 24.7% ± 1.5%). The incidence of recurrent AF was significantly greater in the LV adverse remodeling group than in the no adverse LV remodeling group (81% vs. 13%, p < 0.001). In patients with recurrent AF, mean myocardial ECV significantly increased from 27.7% ± 2.3% to 29.2% ± 2.3% (p = 0.004) after catheter ablation. In a multivariable analysis after adjusting sex, age, and myocardial ECV before catheter ablation, recurrent AF was independently associated with LV adverse remodeling after catheter ablation (odds ratio: 28.9, 95% confidence interval: 6.8–121.7, p < 0.001). Conclusion When monitoring with cardiac MRI, sustained AF was significantly associated with LV adverse remodeling through an increase in myocardial ECV after catheter ablation of AF.

Objectives: To evaluate the side effects and causes of discontinuation of either combined oral contraceptives or dienogest (DNG) used to prevent recurrence in patients with surgically confirmed endometriosis. Methods: We retrospectively analyzed the medical records of 213 women with endometriosis who had been treated with combined oral contraceptives (ethinyl estradiol 0.02 mg/drospirenone 3 mg [EE/DRSP]) or DNG 2 mg for 12 months or more. The side effects reported by the patients, laboratory parameters, causes of discontinuation of medication, and recurrence rates were evaluated one, two, three, four, and five years after starting medication (Y1, Y2, Y3, Y4, and Y5). Results: EE/DRSP were administered to 59 patients, while DNG was administered to 154 patients. The mean durations of postoperative use of EE/DRSP and DNG were 44.5 ± 22.6 months and 23.6 ± 13.5 months, respectively. The prevalence of side effects was 27.1%, 19.0%, 10.0%, 10.5%, and 7.4% in the EE/DRSP group and 29.2%, 15.7%, 14.0%, 23.1%, and 0.0% in the DNG group at Y1, Y2, Y3, Y4, and Y5, respectively. The discontinuation rates were 1.7%, 1.7%, 4.0%, 0.0%, and 7.4% at Y1, Y2, Y3, Y4, and Y5, respectively, in the EE/DRSP group and 10.4%, 3.3%, 4.0%, 3.8%, and 0.0% at the same times in the DNG group. The recurrence rates were less than 4% in both the groups. Conclusions The side effects of commonly prescribed postoperative hormone treatments were relatively mild, and the occurrence of side effects decreased with continuous administration. Further, the long-term use of postoperative hormone treatments is likely to prevent recurrence of endometriosis after surgery.

OBJECTIVE: To simulate the B₁-inhomogeneity-induced variation of pharmacokinetic parameters on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). MATERIALS AND METHODS: B₁-inhomogeneity-induced flip angle (FA) variation was estimated in a phantom study. Monte Carlo simulation was performed to assess the FA-deviation-induced measurement error of the pre-contrast R₁, contrast-enhancement ratio, Gd-concentration, and two-compartment pharmacokinetic parameters (K(trans), v(e), and v(p)). RESULTS: B₁-inhomogeneity resulted in −23–5% fluctuations (95% confidence interval [CI] of % error) of FA. The 95% CIs of FA-dependent % errors in the gray matter and blood were as follows: −16.7–61.8% and −16.7–61.8% for the pre-contrast R₁, −1.0–0.3% and −5.2–1.3% for the contrast-enhancement ratio, and −14.2–58.1% and −14.1–57.8% for the Gd-concentration, respectively. These resulted in −43.1–48.4% error for K(trans), −32.3–48.6% error for the v(e), and −43.2–48.6% error for v(p). The pre-contrast R₁ was more vulnerable to FA error than the contrast-enhancement ratio, and was therefore a significant cause of the Gd-concentration error. For example, a −10% FA error led to a 23.6% deviation in the pre-contrast R₁, −0.4% in the contrast-enhancement ratio, and 23.6% in the Gd-concentration. In a simulated condition with a 3% FA error in a target lesion and a −10% FA error in a feeding vessel, the % errors of the pharmacokinetic parameters were −23.7% for K(trans), −23.7% for v(e), and −23.7% for v(p). CONCLUSION: Even a small degree of B₁-inhomogeneity can cause a significant error in the measurement of pharmacokinetic parameters on DCE-MRI, while the vulnerability of the pre-contrast R₁ calculations to FA deviations is a significant cause of the miscalculation.
Brain ; Gray Matter ; Magnetic Resonance Imaging* ; Monte Carlo Method ; Phantoms, Imaging