Purpose: Cancer patients need ongoing care from healthcare providers to maintain continuity of treatment. Much research has been conducted on digital health services for providing continuous management of discharged cancer patients. This review aimed to identify nurse-led digital health interventions for discharged cancer patients. Methods: This scoping review was conducted using JBI methodology. The population was post-discharge adult cancer patients, the concept was nurse-led digital health intervention, and the context was open. Databases including PubMed, Embase, CINAHL, Cochrane Library, KoreaMed, and RISS were searched.Data were summarized about the general characteristics of the article, participants, interventions, and outcomes. Results: Fifty-seven studies were included, with ten studies that focused on the elderly. One third of the participants included in this review had colorectal cancer (32.7%). Telephone was the most frequently used format, while the others were applications, the internet, and telemonitoring. The nurses’ main roles consisted of counseling, symptom monitoring, and education. Conclusion The development of nurseled digital health intervention for the elderly will be necessary, and studies using more diverse technologies will need to be conducted. Digital health interventions for post-discharge colorectal cancer patients could be applied in practice. Nurses should provide emotional support while providing digital health interventions.

Purpose: This study sought to translate the Stressors in Nursing Students Scale (SINS) into Korean (SINS-K) and verify its validity and reliability for identifying stressors of Korean nursing students. Methods: A methodological design was used. The SINS scale was translated into Korean and administered to 428 nursing students. The results of 213 students were used for exploratory factor analysis, and 215 responses were used for confirmatory factor analysis. Results: The SINS-K showed good internal consistency. The measurement items were consistent, and the independence between factors was maintained. After confirming convergent validity and discriminant validity, the final scale was completed with 33 items. The four factors extracted from the SINS-K were named “clinical practice”, “finance”, “education”, and “conflict”. Conclusion Despite differences in culture and language between countries, the results of this study are similar to those of the original tool. The findings provide information for developing strategies to reduce stressors among nursing students in a global context.

Background: Cumulative evidence consistently shows that anthropometric and body composition measurements are strongly linked to the risk of incident diabetes, typically based on baseline measurements. This study aims to assess whether repeated measurements enhance the prediction of diabetes risk beyond baseline assessments alone. Methods: We utilized data from a 16-year population-based follow-up cohort within the Korean Genome and Epidemiology Study, comprising 6,030 individuals aged 40 to 69 years at baseline. We included eight indices: a body shape index (ABSI), body adiposity index (BAI), waist circumference (WC), body mass index (BMI), waist-to-hip ratio (WHR), weight-adjusted skeletal muscle index (SMI), percent body fat, and fat-to-muscle ratio. The effect of these measurements for incident diabetes was estimated using Harrell’s C-indexes and hazard ratios with 95% confidence intervals, employing time-dependent Cox proportional hazard models. Results: Over the 16-year follow-up, 939 new diabetes cases were identified (cumulative incidence, 15.6%). The median number of indicator measurements per participant was eight. The basic model, including 10 features (sex, age, education levels, physical activity, alcohol intake, current smoking, total energy intake, dietary diversity score, and log-transformed C-reactive protein levels, and quartiles of unweighted genetic risk score at baseline), yielded a Harrell’s C-index of 0.610. The highest C-index in repeated measurements was for WC (0.668) across the general population, weight-adjusted SMI in men, and WHR in women. However, except for ABSI and BAI, the diabetes predictive power of the other indicators was comparable. Additionally, repeated measurements of WC, BMI, and WHR in women were found to contribute to improved discrimination compared to baseline measurements, but not in men. Conclusion Utilizing repeated measurements of general and central adiposity to predict diabetes may be helpful in predicting hidden risks, especially in women.

Background: Cumulative evidence consistently shows that anthropometric and body composition measurements are strongly linked to the risk of incident diabetes, typically based on baseline measurements. This study aims to assess whether repeated measurements enhance the prediction of diabetes risk beyond baseline assessments alone. Methods: We utilized data from a 16-year population-based follow-up cohort within the Korean Genome and Epidemiology Study, comprising 6,030 individuals aged 40 to 69 years at baseline. We included eight indices: a body shape index (ABSI), body adiposity index (BAI), waist circumference (WC), body mass index (BMI), waist-to-hip ratio (WHR), weight-adjusted skeletal muscle index (SMI), percent body fat, and fat-to-muscle ratio. The effect of these measurements for incident diabetes was estimated using Harrell’s C-indexes and hazard ratios with 95% confidence intervals, employing time-dependent Cox proportional hazard models. Results: Over the 16-year follow-up, 939 new diabetes cases were identified (cumulative incidence, 15.6%). The median number of indicator measurements per participant was eight. The basic model, including 10 features (sex, age, education levels, physical activity, alcohol intake, current smoking, total energy intake, dietary diversity score, and log-transformed C-reactive protein levels, and quartiles of unweighted genetic risk score at baseline), yielded a Harrell’s C-index of 0.610. The highest C-index in repeated measurements was for WC (0.668) across the general population, weight-adjusted SMI in men, and WHR in women. However, except for ABSI and BAI, the diabetes predictive power of the other indicators was comparable. Additionally, repeated measurements of WC, BMI, and WHR in women were found to contribute to improved discrimination compared to baseline measurements, but not in men. Conclusion Utilizing repeated measurements of general and central adiposity to predict diabetes may be helpful in predicting hidden risks, especially in women.

Background: Cumulative evidence consistently shows that anthropometric and body composition measurements are strongly linked to the risk of incident diabetes, typically based on baseline measurements. This study aims to assess whether repeated measurements enhance the prediction of diabetes risk beyond baseline assessments alone. Methods: We utilized data from a 16-year population-based follow-up cohort within the Korean Genome and Epidemiology Study, comprising 6,030 individuals aged 40 to 69 years at baseline. We included eight indices: a body shape index (ABSI), body adiposity index (BAI), waist circumference (WC), body mass index (BMI), waist-to-hip ratio (WHR), weight-adjusted skeletal muscle index (SMI), percent body fat, and fat-to-muscle ratio. The effect of these measurements for incident diabetes was estimated using Harrell’s C-indexes and hazard ratios with 95% confidence intervals, employing time-dependent Cox proportional hazard models. Results: Over the 16-year follow-up, 939 new diabetes cases were identified (cumulative incidence, 15.6%). The median number of indicator measurements per participant was eight. The basic model, including 10 features (sex, age, education levels, physical activity, alcohol intake, current smoking, total energy intake, dietary diversity score, and log-transformed C-reactive protein levels, and quartiles of unweighted genetic risk score at baseline), yielded a Harrell’s C-index of 0.610. The highest C-index in repeated measurements was for WC (0.668) across the general population, weight-adjusted SMI in men, and WHR in women. However, except for ABSI and BAI, the diabetes predictive power of the other indicators was comparable. Additionally, repeated measurements of WC, BMI, and WHR in women were found to contribute to improved discrimination compared to baseline measurements, but not in men. Conclusion Utilizing repeated measurements of general and central adiposity to predict diabetes may be helpful in predicting hidden risks, especially in women.

Background: Cumulative evidence consistently shows that anthropometric and body composition measurements are strongly linked to the risk of incident diabetes, typically based on baseline measurements. This study aims to assess whether repeated measurements enhance the prediction of diabetes risk beyond baseline assessments alone. Methods: We utilized data from a 16-year population-based follow-up cohort within the Korean Genome and Epidemiology Study, comprising 6,030 individuals aged 40 to 69 years at baseline. We included eight indices: a body shape index (ABSI), body adiposity index (BAI), waist circumference (WC), body mass index (BMI), waist-to-hip ratio (WHR), weight-adjusted skeletal muscle index (SMI), percent body fat, and fat-to-muscle ratio. The effect of these measurements for incident diabetes was estimated using Harrell’s C-indexes and hazard ratios with 95% confidence intervals, employing time-dependent Cox proportional hazard models. Results: Over the 16-year follow-up, 939 new diabetes cases were identified (cumulative incidence, 15.6%). The median number of indicator measurements per participant was eight. The basic model, including 10 features (sex, age, education levels, physical activity, alcohol intake, current smoking, total energy intake, dietary diversity score, and log-transformed C-reactive protein levels, and quartiles of unweighted genetic risk score at baseline), yielded a Harrell’s C-index of 0.610. The highest C-index in repeated measurements was for WC (0.668) across the general population, weight-adjusted SMI in men, and WHR in women. However, except for ABSI and BAI, the diabetes predictive power of the other indicators was comparable. Additionally, repeated measurements of WC, BMI, and WHR in women were found to contribute to improved discrimination compared to baseline measurements, but not in men. Conclusion Utilizing repeated measurements of general and central adiposity to predict diabetes may be helpful in predicting hidden risks, especially in women.

OBJECTIVE: 3-Methylcrotonyl CoA carboxylase deficiency (3MCCD) is classified as organic acid disease due to leucine catabolism. It is among the most common inborn errors of metabolism identified on newborn screening test using tandem mass spectrometry. There is a broad spectrum of clinical presentations. 3-Methylcrotonyl CoA carboxylase converts 3-methylcrotonyl-CoA to 3-methylglutaconyl-CoA using biotin as a coenzyme in mitochondria. Restricting protein diets and supplementing carnitine, glycine, and biotin are known treatments. We reported this study to find out clinical symptoms, type of gene mutation, and effect of treatment. METHODS: This study was based on retrospective data of patients with 3MCCD in Soonchunhyang University Seoul Hospital and Soonchunhyang University Bucheon Hospital between April 2009 to August 2016. RESULTS: All 10 infants were born term infants and had no symptoms. During the neonatal period, abnormalities were detected in the new born screening test using tandem mass spectrometry, 3-hydroxyisovalerylcarnitine was increased. 3-Methylcrotonylglycine (3MCG) and 3-hydroxyisovalreric acid (3HIVA) were examined in urine organic acid assay. The results showed that 3MCG was increased in all 10 children. Except for three of the 10 children, 3HIVA was increased. Genetic tests were performed on all 10 children. MCCC1 gene mutations were detected in four patients and MCCC2 mutations were detected in six patients. After diagnosis, all children were recommended leucine-restricted diets, and seven of the 10 patients started to feed on leucine free formula for the treatment of 3MCCD. CONCLUSION: According to our data, all patients has no symptoms and are shown normal development. There were no clinical symptoms or changes in prognosis according to gene mutation type.
Biotin ; Carnitine ; Child ; Diagnosis ; Diet ; Glycine ; Gyeonggi-do ; Humans ; Infant ; Infant, Newborn ; Leucine ; Mass Screening ; Metabolism ; Metabolism, Inborn Errors ; Mitochondria ; Neonatal Screening ; Prognosis ; Retrospective Studies ; Seoul ; Tandem Mass Spectrometry

PURPOSE: The aim of this study was to determine the diagnostic value of three screening questionnaires in identifying Korean patients at high risk for obstructive sleep apnea (OSA) in a sleep clinic setting in Korea. MATERIALS AND METHODS: Data were collected from 592 adult patients with suspected OSA who visited a sleep center. All patients completed the Sleep Apnea of Sleep Disorder Questionnaire (SA-SDQ), the Berlin questionnaire, and the STOP-Bang questionnaire. Estimated OSA risk was compared to a diagnosis of OSA. The sensitivity, specificity, positive predictive value, and negative predictive value were calculated for each questionnaire. RESULTS: The prevalence of OSA was 83.6% using an apnea-hypopnea index (AHI) > or =5/h and 58.4% for an AHI > or =15/h. The STOP-Bang questionnaire had a high sensitivity (97% for AHI > or =5/h, 98% for AHI > or =15/h), but the specificity was low (19% and 11%, respectively). In contrast, the sensitivity of the SA-SDQ was not high enough (68% for AHI > or =5/h, 74% for AHI > or =15/h) to be useful in a clinical setting, whereas the specificity was relatively good (66% and 61%, respectively). The sensitivity and specificity values of the Berlin questionnaire fell between those of the STOP-Bang questionnaire and the SA-SDQ. CONCLUSION: The STOP-Bang questionnaire may be useful for screening OSA in a sleep clinic setting, but its specificity is lower than the acceptable level for this purpose. A new screening questionnaire with a high sensitivity and acceptable specificity is therefore needed in a sleep clinic setting.
Adult ; Asian Continental Ancestry Group/*statistics & numerical data ; Female ; Humans ; Male ; Mass Screening/*methods ; Middle Aged ; Polysomnography/methods ; Predictive Value of Tests ; Prevalence ; *Questionnaires ; ROC Curve ; Reproducibility of Results ; Republic of Korea/epidemiology ; Sensitivity and Specificity ; Severity of Illness Index ; Sleep Apnea, Obstructive/*diagnosis/ethnology

BACKGROUND: Pregnancy may influence the skin in various ways from physiologic changes to pathologic dermatoses. OBJECTIVE: To analyze and quantify the distribution and clinical features of dermatoses in pregnant patients. METHODS: We retrospectively reviewed medical records of 634 pregnant patients who visited the department of dermatology between May, 2006 and November, 2012. The patients' epidemiologic status and clinical characteristics were analyzed. RESULTS: The mean age of patients was 30.6 and the mean gestational age was 22.3 weeks. They were classified into 3 groups: general dermatoses, pregnancy-specific dermatoses, and physiologic skin change. General dermatoses were observed in 434 patients (68.5%) and infectious disease accounted for 50.0% of them. The most frequent infectious disease was viral infection with herpes zoster (29.5%) and varicella (16.1%). Pregnancy-specific dermatoses were recognized in 177 patients (28.0%). Among them, 96 (54.2%) were diagnosed as atopic eruption of pregnancy and 66 (37.3%) were pruritic urticarial papules and plaques of pregnancy. Primigravida, late onset and abdominal involvement were more frequent in patients with pruritic urticarial papules and plaques of pregnancy. The prognosis of patients with pregnancy specific dermatoses was good without major fetal problems. Pyogenic granuloma was recorded as the most common physiologic changes encountered. We performed examinations and procedures in only 36.3% of pregnant patients. CONCLUSION: We analyzed the distribution and clinical characteristics observed in pregnant patients with dermatological problems. Dermatologists should be aware of the differences to improve the quality of patient care.
Chickenpox ; Communicable Diseases ; Dermatology ; Gestational Age ; Granuloma, Pyogenic ; Herpes Zoster ; Humans ; Medical Records ; Patient Care ; Pregnancy ; Pregnancy Complications ; Prognosis ; Pruritus ; Retrospective Studies ; Skin ; Skin Diseases

Anti-LGI1 (leucine-rich glioma inactivated-1) antibody encephalitis is one of autoimmune encephalitis. We report a 66-year-old man who presented with frequent, brief dystonic seizures which involve predominantly ipsilateral face and arm without cognitive impairment. Brain MRI showed normal finding. Serum and CSF tests revealed anti-LGI1 antibody. His symptom was not relieved by antiepileptic drugs, but completely controlled after immunotherapy. This case indicates that recognition of the brief, dystonic seizures should do tests for anti-LGI1 antibodies.
Aged ; Antibodies ; Anticonvulsants ; Arm ; Brain ; Encephalitis* ; Glioma ; Humans ; Immunotherapy ; Magnetic Resonance Imaging ; Potassium Channels, Voltage-Gated ; Seizures*