Updating Korean Disability Weights for Causes of Disease: Adopting an Add-on Study Method / 예방의학회지

Objectives@#Disability weights require regular updates, as they are influenced by both diseases and societal perceptions. Consequently, it is necessary to develop an up-to-date list of the causes of diseases and establish a survey panel for estimating disability weights. Accordingly, this study was conducted to calculate, assess, modify, and validate disability weights suitable for Korea, accounting for its cultural and social characteristics. @*Methods@#The 380 causes of disease used in the survey were derived from the 2019 Global Burden of Disease Collaborative Network and from 2019 and 2020 Korean studies on disability weights for causes of disease. Disability weights were reanalyzed by integrating the findings of an earlier survey on disability weights in Korea with those of the additional survey conducted in this study. The responses were transformed into paired comparisons and analyzed using probit regression analysis. Coefficients for the causes of disease were converted into predicted probabilities, and disability weights in 2 models (model 1 and 2) were rescaled using a normal distribution and the natural logarithm, respectively. @*Results@#The mean values for the 380 causes of disease in models 1 and 2 were 0.488 and 0.369, respectively. Both models exhibited the same order of disability weights. The disability weights for the 300 causes of disease present in both the current and 2019 studies demonstrated a Pearson correlation coefficient of 0.994 (p=0.001 for both models). This study presents a detailed add-on approach for calculating disability weights. @*Conclusions@#This method can be employed in other countries to obtain timely disability weight estimations.

Trends and Patterns of Cancer Burdens by Region and Income Level in Korea: A National Representative Big Data Analysis / Journal of the Korean Cancer Association, 대한암학회지

Purpose@#This study aimed to elucidate the trends and characteristics of the cancer burden in Korea by cancer site, region, and income level. @*Materials and Methods@#Korean National Burden of Disease research methodology was applied to measure the cancer burden in Korea from 2008 to 2018. The cause of death and national health insurance claims data were obtained from Statistics Korea and the National Health Insurance Service, respectively. An incidence-based approach was applied to calculate the disability-adjusted life-years, which is a summary measure of population health. @*Results@#In the past decade, the cancer burden in Korea increased from 2,088 to 2,457 person-years per 100,000 population. Among the cancer burden, the years of life lost decreased, and the years lived with disabilities increased. Cancers of the trachea, bronchus, and lung had the highest disease burden, followed by those of the stomach, colon and rectum, liver, and breast. @*Conclusion@#The findings of this study can provide valuable quantitative data for prioritizing and evaluating cancer prevention strategies and implementing cancer policies. Estimating the difference in cancer burden according to region and income level within a country can yield useful data to understand the nature of the cancer burden and scale of the problem. In addition, the results of this study provide a better understanding of the causes of cancer patterns, thereby generating new hypotheses regarding its pathogenesis.

A Review of the Types and Characteristics of Healthy Life Expectancy and Methodological Issues / 예방의학회지

An index that evaluates the health level of a population group considering both death and loss of function due to disease is called a summary measure of population health (SMPH). SMPHs are broadly divided into life year indices and life expectancy indices, the latter of which comprise healthy life expectancy (HLE). HLE is included as a policy target in various national and regional level healthcare plans, and the term “HLE” is commonly used in academia and by the public. However, the overall level of understanding of HLE—such as the precise definition of HLE and methods of calculating HLE—still seems to be low. As discussed in this study, the types of HLE are classified into disability-free life expectancy, disease-free life expectancy, quality-adjusted life expectancy, self-rated HLE, and disability-adjusted life expectancy. Their characteristics are examined to facilitate a correct understanding and appropriate utilization of HLE. In addition, the Sullivan method, as a representative method for calculating HLE, is presented in detail, and major issues in the process of calculating HLE, such as selection of the population group and age group, estimation of death probability, calculation of life years, and incorporation of health weights, are reviewed. This study will help researchers to select an appropriate HLE type and evaluate the validity of HLE research results, and it is expected to contribute to the vitalization of HLE research.

DALY Estimation Approaches: Understanding and Using the Incidence-based Approach and the Prevalence-based Approach / 예방의학회지

Disability-adjusted life-year (DALY) estimates may vary according to factors such as the standard life expectancy, age weighting, time preference and discount rate, calculation of disability weights, and selection of the estimation method. DALY estimation methods are divided into the following 3 approaches: the incidence-based approach, the pure prevalence-based approach, and the hybrid approach. These 3 DALY estimation approaches each reflect different perspectives on the burden of disease using unique characteristics, based on which the selection of a suitable approach may vary by the purpose of the study. The Global Burden of Disease studies, which previously estimated DALYs using the incidence-based approach, switched to using the hybrid approach in 2010, while the National Burden of Disease studies in Korea still mainly apply the incidence-based approach. In order to increase comparability with other international burden of disease studies, more DALY studies using the prevalence-based approach need to be conducted in Korea. However, with the limitations of the hybrid approach in mind, it is necessary to conduct more research using a disease classification system suitable for Korea. Furthermore, more detailed and valid data sources should be established before conducting studies using a broader variety of DALY estimation approaches. This review study will help researchers on burden of disease use an appropriate DALY estimation approach and will contribute to enhancing researchers’ ability to critically interpret burden of disease studies.

Measuring the Burden of Disease in Korea, 2008-2018 / 예방의학회지

The study aims to examine the current status and differences in the burden of disease in Korea during 2008-2018. We calculated the burden of disease for Koreans from 2008 to 2018 using an incidence-based approach. Disability adjusted life years (DALYs) were expressed in units per 100 000 population by adding years of life lost (YLLs) and years lived with disability (YLDs). DALY calculation results were presented by gender, age group, disease, region, and income level. To explore differences in DALYs by region and income level, we used administrative district and insurance premium information from the National Health Insurance Service claims data. The burden of disease among Koreans showed an increasing trend from 2008 to 2018. By 2017, the burden of disease among men was higher than that among women. Diabetes mellitus, low back pain, and chronic lower respiratory disease were ranked high in the burden of disease; the sum of DALY rates for these diseases accounted for 18.4% of the total burden of disease among Koreans in 2018. The top leading causes associated with a high burden of disease differed slightly according to gender, age group, and income level. In this study, we measured the health status of Koreans and differences in the population health level according to gender, age group, region, and income level. This data can be used as an indicator of health equity, and the results derived from this study can be used to guide community-centered (or customized) health promotion policies and projects, and for setting national health policy goals.

Prediction of Neurological Outcomes in Out-of-hospital Cardiac Arrest Survivors Immediately after Return of Spontaneous Circulation: Ensemble Technique with Four Machine Learning Models

Background@#We performed this study to establish a prediction model for 1-year neurological outcomes in out-of-hospital cardiac arrest (OHCA) patients who achieved return of spontaneous circulation (ROSC) immediately after ROSC using machine learning methods. @*Methods@#We performed a retrospective analysis of an OHCA survivor registry. Patients aged ≥ 18 years were included. Study participants who had registered between March 31, 2013 and December 31, 2018 were divided into a develop dataset (80% of total) and an internal validation dataset (20% of total), and those who had registered between January 1, 2019 and December 31, 2019 were assigned to an external validation dataset. Four machine learning methods, including random forest, support vector machine, ElasticNet and extreme gradient boost, were implemented to establish prediction models with the develop dataset, and the ensemble technique was used to build the final prediction model. The prediction performance of the model in the internal validation and the external validation dataset was described with accuracy, area under the receiver-operating characteristic curve, area under the precision-recall curve, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Futhermore, we established multivariable logistic regression models with the develop set and compared prediction performance with the ensemble models. The primary outcome was an unfavorable 1-year neurological outcome. @*Results@#A total of 1,207 patients were included in the study. Among them, 631, 139, and 153were assigned to the develop, the internal validation and the external validation datasets, respectively. Prediction performance metrics for the ensemble prediction model in the internal validation dataset were as follows: accuracy, 0.9620 (95% confidence interval [CI],0.9352–0.9889); area under receiver-operator characteristics curve, 0.9800 (95% CI, 0.9612– 0.9988); area under precision-recall curve, 0.9950 (95% CI, 0.9860–1.0000); sensitivity, 0.9594 (95% CI, 0.9245–0.9943); specificity, 0.9714 (95% CI, 0.9162–1.0000); PPV, 0.9916 (95% CI, 0.9752–1.0000); NPV, 0.8718 (95% CI, 0.7669–0.9767). Prediction performance metrics for the model in the external validation dataset were as follows: accuracy, 0.8509 (95% CI, 0.7825–0.9192); area under receiver-operator characteristics curve, 0.9301 (95% CI, 0.8845–0.9756); area under precision-recall curve, 0.9476 (95% CI, 0.9087–0.9867); sensitivity, 0.9595 (95% CI, 0.9145–1.0000); specificity, 0.6500 (95% CI, 0.5022–0.7978); PPV, 0.8353 (95% CI, 0.7564–0.9142); NPV, 0.8966 (95% CI, 0.7857–1.0000). All the prediction metrics were higher in the ensemble models, except NPVs in both the internal and the external validation datasets. @*Conclusion@#We established an ensemble prediction model for prediction of unfavorable 1-year neurological outcomes in OHCA survivors using four machine learning methods. The prediction performance of the ensemble model was higher than the multivariable logistic regression model, while its performance was slightly decreased in the external validation dataset.

Trend of Disease Burden of North Korean Defectors in South Korea Using Disability-adjusted Life Years from 2010 to 2018

Background@#This study aimed to examine the disease burden of North Korean defectors in South Korea by sex, age, and disease from 2000 to 2018 and to study the changes in the disease burden over time. @*Methods@#Based on the incidence-based disability-adjusted life year (DALY) developed in a Korean National Burden of Disease (KNBD) study, we calculated the years of life lost (YLL), years lived with disability (YLD), and disability-adjusted life years (DALY) for approximately 22,753 North Korean defectors in South Korea whose claims data were available from the National Health Insurance Service (NHIS). @*Results@#In 2018, the rates of YLL, YLD, and DALY for North Korean defectors per 100,000 population was 3,763 (male 8,491; female 2,404), 37,683 (male 27,742; female 40,539), and 41,446 (male 36,233; female 42,943), respectively. Major depressive disorders constituted the highest DALY, followed by cirrhosis of the liver and low back pain. The disease burden of North Korean defectors consistently decreased from 2010 to 2018. The decrease in YLD contributed to the overall decline in DALY per 100,000 population in 2018, which decreased by 25.2% compared to that in 2010. @*Conclusion@#This is the first study to measure the disease burden of North Korean defectors in South Korea. Given the decreasing or substantially increasing trends in disease burden, it is necessary to establish appropriate public health policies in a timely manner, and the results of this study provide a basis for the development of customized public health and healthcare policies for North Korean defectors in South Korea.

Prediction of Neurological Outcomes in Out-of-hospital Cardiac Arrest Survivors Immediately after Return of Spontaneous Circulation: Ensemble Technique with Four Machine Learning Models

Background@#We performed this study to establish a prediction model for 1-year neurological outcomes in out-of-hospital cardiac arrest (OHCA) patients who achieved return of spontaneous circulation (ROSC) immediately after ROSC using machine learning methods. @*Methods@#We performed a retrospective analysis of an OHCA survivor registry. Patients aged ≥ 18 years were included. Study participants who had registered between March 31, 2013 and December 31, 2018 were divided into a develop dataset (80% of total) and an internal validation dataset (20% of total), and those who had registered between January 1, 2019 and December 31, 2019 were assigned to an external validation dataset. Four machine learning methods, including random forest, support vector machine, ElasticNet and extreme gradient boost, were implemented to establish prediction models with the develop dataset, and the ensemble technique was used to build the final prediction model. The prediction performance of the model in the internal validation and the external validation dataset was described with accuracy, area under the receiver-operating characteristic curve, area under the precision-recall curve, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Futhermore, we established multivariable logistic regression models with the develop set and compared prediction performance with the ensemble models. The primary outcome was an unfavorable 1-year neurological outcome. @*Results@#A total of 1,207 patients were included in the study. Among them, 631, 139, and 153were assigned to the develop, the internal validation and the external validation datasets, respectively. Prediction performance metrics for the ensemble prediction model in the internal validation dataset were as follows: accuracy, 0.9620 (95% confidence interval [CI],0.9352–0.9889); area under receiver-operator characteristics curve, 0.9800 (95% CI, 0.9612– 0.9988); area under precision-recall curve, 0.9950 (95% CI, 0.9860–1.0000); sensitivity, 0.9594 (95% CI, 0.9245–0.9943); specificity, 0.9714 (95% CI, 0.9162–1.0000); PPV, 0.9916 (95% CI, 0.9752–1.0000); NPV, 0.8718 (95% CI, 0.7669–0.9767). Prediction performance metrics for the model in the external validation dataset were as follows: accuracy, 0.8509 (95% CI, 0.7825–0.9192); area under receiver-operator characteristics curve, 0.9301 (95% CI, 0.8845–0.9756); area under precision-recall curve, 0.9476 (95% CI, 0.9087–0.9867); sensitivity, 0.9595 (95% CI, 0.9145–1.0000); specificity, 0.6500 (95% CI, 0.5022–0.7978); PPV, 0.8353 (95% CI, 0.7564–0.9142); NPV, 0.8966 (95% CI, 0.7857–1.0000). All the prediction metrics were higher in the ensemble models, except NPVs in both the internal and the external validation datasets. @*Conclusion@#We established an ensemble prediction model for prediction of unfavorable 1-year neurological outcomes in OHCA survivors using four machine learning methods. The prediction performance of the ensemble model was higher than the multivariable logistic regression model, while its performance was slightly decreased in the external validation dataset.

Trend of Disease Burden of North Korean Defectors in South Korea Using Disability-adjusted Life Years from 2010 to 2018

Background@#This study aimed to examine the disease burden of North Korean defectors in South Korea by sex, age, and disease from 2000 to 2018 and to study the changes in the disease burden over time. @*Methods@#Based on the incidence-based disability-adjusted life year (DALY) developed in a Korean National Burden of Disease (KNBD) study, we calculated the years of life lost (YLL), years lived with disability (YLD), and disability-adjusted life years (DALY) for approximately 22,753 North Korean defectors in South Korea whose claims data were available from the National Health Insurance Service (NHIS). @*Results@#In 2018, the rates of YLL, YLD, and DALY for North Korean defectors per 100,000 population was 3,763 (male 8,491; female 2,404), 37,683 (male 27,742; female 40,539), and 41,446 (male 36,233; female 42,943), respectively. Major depressive disorders constituted the highest DALY, followed by cirrhosis of the liver and low back pain. The disease burden of North Korean defectors consistently decreased from 2010 to 2018. The decrease in YLD contributed to the overall decline in DALY per 100,000 population in 2018, which decreased by 25.2% compared to that in 2010. @*Conclusion@#This is the first study to measure the disease burden of North Korean defectors in South Korea. Given the decreasing or substantially increasing trends in disease burden, it is necessary to establish appropriate public health policies in a timely manner, and the results of this study provide a basis for the development of customized public health and healthcare policies for North Korean defectors in South Korea.

Measuring the Burden of Disease in Korea, 2008-2018 / 예방의학회지

The study aims to examine the current status and differences in the burden of disease in Korea during 2008-2018. We calculated the burden of disease for Koreans from 2008 to 2018 using an incidence-based approach. Disability adjusted life years (DALYs) were expressed in units per 100 000 population by adding years of life lost (YLLs) and years lived with disability (YLDs). DALY calculation results were presented by gender, age group, disease, region, and income level. To explore differences in DALYs by region and income level, we used administrative district and insurance premium information from the National Health Insurance Service claims data. The burden of disease among Koreans showed an increasing trend from 2008 to 2018. By 2017, the burden of disease among men was higher than that among women. Diabetes mellitus, low back pain, and chronic lower respiratory disease were ranked high in the burden of disease; the sum of DALY rates for these diseases accounted for 18.4% of the total burden of disease among Koreans in 2018. The top leading causes associated with a high burden of disease differed slightly according to gender, age group, and income level. In this study, we measured the health status of Koreans and differences in the population health level according to gender, age group, region, and income level. This data can be used as an indicator of health equity, and the results derived from this study can be used to guide community-centered (or customized) health promotion policies and projects, and for setting national health policy goals.

Years of Life Lost Attributable to COVID-19 in High-incidence Countries

Background@#The coronavirus disease 2019 (COVID-19) pandemic is a major public health problem of international concern. It is important to estimate its impact of COVID-19 for health policy decision-making. We estimated the years of life lost (YLLs) due to COVID-19 in high-incidence countries. @*Methods@#We collected the YLLs due to COVID-19 in 30 high-incidence countries as of April 13, 2020 and followed up as of July 14, 2020. Incidence and mortality were collected using each country's formal reports, articles, and other electronic sources. The life expectancy of Japanese females by age and the UN population data were used to calculate YLLs in total and per 100,000. @*Results@#As of April 22, 2020, there were 1,699,574 YLLs due to COVID-19 in 30 high-incidence countries. On July 14, 2020, this increased to 4,072,325. Both on April 22 and July 14, the total YLLs due to COVID-19 was highest in the USA (April 22, 534,481 YLLs; July 14, 1,199,510 YLLs), and the YLLs per 100,000 population was highest in Belgium (April 22, 868.12 YLLs/100,000;July 14, 1,593.72 YLLs/100,000). YLLs due to COVID-19 were higher among males than among females and higher in those aged ≥ 60 years than in younger individuals. Belgium had the highest proportion of YLLs attributable to COVID-19 as a proportion of the total YLLs and the highest disability-adjusted life years per 100,000 population. @*Conclusion@#This study estimated YLLs due to COVID-19 in 30 countries. COVID-19 is a high burden in the USA and Belgium, among males and the elderly. The YLLs are very closely related with the incidence as well as the mortality. This highlights the importance of the early detection of incident case that minimizes severe acute respiratory syndrome coronavirus-2 fatality.

Copeptin with high-sensitivity troponin at presentation is not inferior to serial troponin measurements for ruling out acute myocardial infarction

Objective@#We aimed to compare the multi-marker strategy (copeptin and high-sensitivity cardiac troponin I [hs-cTnI]) with serial hs-cTnI measurements to rule out acute myocardial infarction (AMI) in patients with chest pain. @*Methods@#This prospective observational study was performed in a single emergency department. To test the non-inferiority margin of 4% in terms of negative predictive value (NPV) between the multi-marker strategy (0 hour) and serial hs-cTnI measurements (0 and 2 hours), 262 participants were required. Samples for copeptin and hs-cTnI assays were collected at presentation (0 hour) and after 2 hours. The measured biomarkers were considered abnormal when hs-cTnI was >26.2 ng/L and when copeptin was >10 pmol/L. @*Results@#AMI was diagnosed in 28 patients (10.7%). The NPV of the multi-marker strategy was 100% (160/160; 95% confidence interval [CI], 97.7% to 100%), which was not inferior to that of serial hs-cTnI measurements (201/201; 100%; 95% CI, 98.2% to 100%). The sensitivity, specificity, and positive predictive value of the multi-marker strategy were 100% (95% CI, 87.7% to 100%), 68.1% (95% CI, 61.7% to 74.0%), and 27.2% (95% CI, 18.9% to 36.8%), respectively. The sensitivity, specificity, and positive predictive value of serial hs-cTnI measurements were 100% (95% CI, 87.7% to 100%), 85.5% (95% CI, 80.4% to 89.8%), and 45.2% (95% CI, 32.5% to 58.3%), respectively. @*Conclusion@#The multi-marker strategy (copeptin and hs-cTnI measurement) was not inferior to serial hs-cTnI measurements in terms of NPV for AMI diagnosis, with a sensitivity and NPV of 100%. Copeptin may help in the early rule-out of AMI in patients with chest pain.

Comparison of Intubation Efficiency by Suction Device in a Hemorrhagic Airway Manikin Model: Yankauer Suction Tip vs. Polyvinyl Chloride Catheter Suction Tip

PURPOSE: Tracheal intubation in a hemorrhagic airway is a difficult procedure because the visibility can be obscured by blood or vomitus. Several devices and methods have been developed to overcome such obstacles, but they are not available at all practical sites. Therefore, this study was conducted to assess the time and success rate of tracheal intubation according to the type of suction tip used in a hemorrhagic airway manikin model. METHODS: This study was a randomized crossover manikin simulation study. We recruited 18 emergency physicians to perform intubation with suction using a Yankauer suction tip and a polyvinyl chloride (PVC) catheter suction tip in a hemorrhagic airway manikin model. We then measured the time and success rate of intubation for each suction tip. RESULTS: The mean intubation time using the Yankauer suction tip was 42.3 seconds, and the mean intubation time using the PVC catheter suction tip was 91.1 seconds (p < 0.001). Two cases of esophageal intubation occurred when the PVC catheter suction tip was used (success rate, 88.9%). In contrast, there was no esophageal intubation when the Yankauer suction tip was used (success rate, 100%) (p=0.217). CONCLUSION: Intubation of a hemorrhagic airway manikin model can be performed in a shorter time when a Yankauer suction tip is used than when a PVC catheter suction tip is used.

Association between the simultaneous decrease in the levels of soluble vascular cell adhesion molecule-1 and S100 protein and good neurological outcomes in cardiac arrest survivors

OBJECTIVE: This study aimed to determine whether simultaneous decreases in the serum levels of cell adhesion molecules (intracellular cell adhesion molecule-1 [ICAM-1], vascular cell adhesion molecule-1 [VCAM-1], and E-selectin) and S100 proteins within the first 24 hours after the return of spontaneous circulation were associated with good neurological outcomes in cardiac arrest survivors. METHODS: This retrospective observational study was based on prospectively collected data from a single emergency intensive care unit (ICU). Twenty-nine out-of-hospital cardiac arrest survivors who were admitted to the ICU for post-resuscitation care were enrolled. Blood samples were collected at 0 and 24 hours after ICU admission. According to the 6-month cerebral performance category (CPC) scale, the patients were divided into good (CPC 1 and 2, n=12) and poor (CPC 3 to 5, n=17) outcome groups. RESULTS: No difference was observed between the two groups in terms of the serum levels of ICAM-1, VCAM-1, E-selectin, and S100 at 0 and 24 hours. A simultaneous decrease in the serum levels of VCAM-1 and S100 as well as E-selectin and S100 was associated with good neurological outcomes. When other variables were adjusted, a simultaneous decrease in the serum levels of VCAM-1 and S100 was independently associated with good neurological outcomes (odds ratio, 9.285; 95% confidence interval, 1.073 to 80.318; P=0.043). CONCLUSION: A simultaneous decrease in the serum levels of soluble VCAM-1 and S100 within the first 24 hours after the return of spontaneous circulation was associated with a good neurological outcome in out-of-hospital cardiac arrest survivors.

Changes in Inflammatory Cytokines during Rewarming Period of Therapeutic Hypothermia for Post-Cardiac Arrest Patients

PURPOSE: Therapeutic hypothermia is an important treatment strategy for control of the overwhelming inflammatory reactions of cardiac arrest patients. Rapid rewarming is related to poor outcome, however the kinds of inflammatory processes that occur during the rewarming period are not well understood. Our aim in the current study was to evaluate the changes in inflammatory cytokine levels during cardiac arrest patients' rewarming period. METHODS: This study was conducted in an emergency intensive care unit of a tertiary referral hospital. Blood samples were collected on admission (0 h) and 24, 26, 28, and 32 h after return of spontaneous circulation. Eight inflammatory cytokines (E-selectin, soluble ICAM, interleukin-10, interleukin-1ra, interleukin-6, interleukin-8, monocyte chemotactic protein-1, and tumor necrosis factor-α) were measured. RESULTS: Twenty-eight patients were enrolled and completed a protocol of 24 h hypothermia and 8h rewarming. Eight patients were of the good cerebral performance category (CPC) and 20 of the bad. The IL-1Ra level in the good CPC group was statistically changed at 26 (p=0.039) and 28 (p=0.003) but not at 32 h (p=0.632) when compared with the 24 h level. The IL-10 levels of the bad CPC group were decreased at 26 (p=0.017) and 28h (p=0.013) but not at 32 h (p=0.074) when compared with 24 h. None of the other cytokines showed meaningful differences during the rewarming period. CONCLUSION: Change in inflammatory-cytokine-level change during the rewarming period is not significant.