• Journal of Chest Surgery
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• 제54권2호
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• pp.88-98
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• 2021

Background: This study aimed to develop a new risk prediction model for operative mortality in a Korean cohort undergoing heart valve surgery using the Korea Heart Valve Surgery Registry (KHVSR) database. Methods: We analyzed data from 4,742 patients registered in the KHVSR who underwent heart valve surgery at 9 institutions between 2017 and 2018. A risk prediction model was developed for operative mortality, defined as death within 30 days after surgery or during the same hospitalization. A statistical model was generated with a scoring system by multiple logistic regression analyses. The performance of the model was evaluated by its discrimination and calibration abilities. Results: Operative mortality occurred in 142 patients. The final regression models identified 13 risk variables. The risk prediction model showed good discrimination, with a c-statistic of 0.805 and calibration with Hosmer-Lemeshow goodness-of-fit p-value of 0.630. The risk scores ranged from -1 to 15, and were associated with an increase in predicted mortality. The predicted mortality across the risk scores ranged from 0.3% to 80.6%. Conclusion: This risk prediction model using a scoring system specific to heart valve surgery was developed from the KHVSR database. The risk prediction model showed that operative mortality could be predicted well in a Korean cohort.

• Journal of Korean Neurosurgical Society
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• 제60권2호
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• pp.239-249
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• 2017

Objective : The purpose of this study is to evaluate the associations between 30-day mortality and various radiological and clinical factors in patients with traumatic acute subdural hematoma (SDH). During the 11-year study period, young patients who underwent surgery for SDH were followed for 30 days. Patients who died due to other medical comorbidities or other organ problems were not included in the study population. Methods : From January 1, 2004 to December 31, 2014, 318 consecutive surgically-treated traumatic acute SDH patients were registered for the study. The Kaplan-Meier method was used to analyze 30-day survival rates. We also estimated the hazard ratios of various variables in order to identify the independent predictors of 30-day mortality. Results : We observed a negative correlation between 30-day mortality and Glasgow coma scale score (per 1-point score increase) (hazard ratio [HR], 0.60; 95% confidence interval [CI], 0.52-0.70; p<0.001). In addition, use of antithrombotics (HR, 2.34; 95% CI, 1.27-4.33; p=0.008), history of diabetes mellitus (HR, 2.28; 95% CI, 1.20-4.32; p=0.015), and accompanying traumatic subarachnoid hemorrhage (hazard ratio, 2.13; 95% CI, 1.27-3.58; p=0.005) were positively associated with 30-day mortality. Conclusion : We found significant associations between short-term mortality after surgery for traumatic acute SDH and lower Glasgow Coma Scale scores, use of antithrombotics, history of diabetes mellitus, and accompanying traumatic subarachnoid hemorrhage at admission. We expect these findings to be helpful for selecting patients for surgical treatment of traumatic acute SDH, and for making accurate prognoses.

• Journal of Preventive Medicine and Public Health
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• 제34권1호
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• pp.21-27
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• 2001

Objectives : To develop a model that will predict the mortality of patients undergoing Coronary Artery Bypass Graft (CABG) and evaluate the perfermance of hospitals. Methods : Data from 564 CABGs peformed in six general hospitals were collected through medical record abstraction by registered nurses. Variables studied involved risk factors determined by severity measures. Risk modeling was performed through logistic repression and validated with cross-validation. The statistical performance of the developed model was evaluated using c-statistic, $R^2$, and Hosmer-Lemeshow statistic. Hospital performance was assessed by severity-adjusted mortalities. Results : The developed model included age, sex, BUN, EKG rhythm, Congestive Heart Failure at admission. acute mental change within 24 hours, and previous angina pectoris history. The c-statistic and $R^2$ were 0.791 and 0.001, respectively. Hosmer-Lemeshow statistic was 10.3(p value=0.2415). One hospital had a significantly higher mortality rate than the average mortality rate, while others were net significantly different. Conclusion : Comparing the quality of service by severity adjusted mortality rates, there were significant differences in hospital performance. The severity adjusted mortality rate of CABG surgery may He an indicator for evaluating hospital performance in Korea.

• 한국병원경영학회지
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• 제25권4호
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• pp.1-12
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• 2020

During the COVID-19 pandemic, most of the western countries with advanced medical technology failed to contain coronavirus. This fact triggered our research question of what factors influence the clinical outcomes like infection rates and case mortality rates. This study aims to identify the determinants of COVID-19 related infection rates and case mortality rates. We considered three sets of independent variables: 1) socio-demographic characteristics; 2) cultural characteristics; 3) healthcare system characteristics. For the analysis, we created an international dataset from diverse sources like World Bank, Worldometers, Hofstede Insight, GHS index etc. The COVID-19 related statistics were retrieved from Aug. 1. Total cases are from 95 countries. We used hierarchical regression method to examine the linear relationship among variables. We found that obesity, uncertainty avoidance, hospital beds per 1,000 made a significant influence on the standardized COVID-19 infection rates. The countries with higher BMI score or higher uncertainty avoidance showed higher infection rates. The standardized COVID-19 infection rates were inversely related to hospital beds per 1,000. In the analysis on the standardized COVID-19 case mortality rates, we found that two cultural characteristics(e.g., individualism, uncertainty avoidance) showed statistically significant influence on the case mortality rates. The healthcare system characteristics did not show any statistically significant relationship with the case mortality rates. The cultural characteristics turn out to be significant factors influencing the clinical outcomes during COVID-19 pandemic. The results imply that the persuasive communication is important to trigger the public commitment to follow preventive measures. The strategy to keep the hospital surge capacity needs to be developed.

• Journal of Chest Surgery
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• 제56권2호
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• pp.99-107
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• 2023

Background: The neutrophil-to-lymphocyte ratio (NLR) has been suggested as a novel predictive marker of cardiovascular disease. However, its prognostic role in patients under-going coronary artery bypass grafting (CABG) is unclear. This study aimed to determine the association between the preoperative NLR and early mortality in patients undergoing CABG. Methods: Cardiac surgery was performed in 2,504 patients at Seoul St. Mary's Hospital from January 2010 to December 2021. This study retrospectively reviewed 920 patients who underwent isolated CABG, excluding those for whom the preoperative NLR was unavailable. The primary endpoints were the 30- and 90-day mortality after isolated CABG. Risk factor analysis was performed using logistic regression analysis. Based on the optimal cut-off value of preoperative NLR on the receiver operating characteristic curve, high and low NLR groups were compared. Results: The 30- and 90-day mortality rates were 3.8% (n=35) and 7.0% (n=64), respectively. In the multivariable analysis, preoperative NLR was significantly associated with 30-day mortality (odds ratio [OR], 1.28; 95% confidence interval [CI], 1.17-1.39; p<0.001) and 90-day mortality (OR, 1.17; 95% CI, 1.07-1.28; p<0.001). The optimal cut-off value of the preoperative NLR was 3.4. Compared to the low NLR group (<3.4), the high NLR group (≥3.4) showed higher 30- and 90-day mortality rates (1.4% vs. 12.1%, p<0.001; 2.8% vs. 21.3%, p<0.001, respectively). Conclusion: Preoperative NLR was strongly associated with early mortality after isolated CABG, especially in patients with a high preoperative NLR (≥3.4). Further studies with larger cohorts are necessary to validate these results.

• Journal of Preventive Medicine and Public Health
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• 제54권5호
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• pp.352-359
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• 2021

Objectives: The aim of this study was to examine the geographic distribution of diabetes mortality in Japan and identify socioeconomic factors affecting differences in municipality-specific diabetes mortality. Methods: Diabetes mortality data by year and municipality from 2013 to 2017 were extracted from Japanese Vital Statistics, and the socioeconomic characteristics of municipalities were obtained from government statistics. We calculated the standardized mortality ratio (SMR) of diabetes for each municipality using the empirical Bayes method and represented geographic differences in SMRs in a map of Japan. Multiple linear regression was conducted to identify the socioeconomic factors affecting differences in SMR. Statistically significant socioeconomic factors were further assessed by calculating the relative risk of mortality of quintiles of municipalities classified according to the degree of each socioeconomic factor using Poisson regression analysis. Results: The geographic distribution of diabetes mortality differed by gender. Of the municipality-specific socioeconomic factors, high rates of single-person households and unemployment and a high number of hospital beds were associated with a high SMR for men. High rates of fatherless households and blue-collar workers were associated with a high SMR for women, while high taxable income per-capita income and total population were associated with low SMR for women. Quintile analysis revealed a complex relationship between taxable income and mortality for women. The mortality risk of quintiles with the highest and lowest taxable per-capita income was significantly lower than that of the middle-income quintile. Conclusions: Socioeconomic factors of municipalities in Japan were found to affect geographic differences in diabetes mortality.

• Journal of Korean Neurosurgical Society
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• 제64권1호
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• pp.51-59
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• 2021

Objective : Several studies have reported inconsistent findings among countries on whether off-hour hospital presentation is associated with worse outcome in patients with acute stroke. However, its association is yet not clear and has not been thoroughly studied in Korea. We assessed nationwide administrative data to verify off-hour effect in different subtypes of acute stroke in Korea. Methods : We respectively analyzed the nationwide administrative data of National Emergency Department Information System in Korea; 7144 of ischemic stroke (IS), 2424 of intracerebral hemorrhage (ICH), and 1482 of subarachnoid hemorrhage (SAH), respectively. "Off-hour hospital presentation" was defined as weekends, holidays, and any times except 8:00 AM to 6:00 PM on weekdays. The primary outcome measure was in-hospital mortality in different subtypes of acute stroke. We adjusted for covariates to influence the primary outcome using binary logistic regression model and Cox's proportional hazard model. Results : In subjects with IS, off-hour hospital presentation was associated with unfavorable outcome (24.6% off hours vs. 20.9% working hours, p<0.001) and in-hospital mortality (5.3% off hours vs. 3.9% working hours, p=0.004), even after adjustment for compounding variables (hazard ratio [HR], 1.244; 95% confidence interval [CI], 1.106-1.400; HR, 1.402; 95% CI, 1.124-1.747, respectively). Off-hours had significantly more elderly ≥65 years (35.4% off hours vs. 32.1% working hours, p=0.029) and significantly more frequent intensive care unit admission (32.5% off hours vs. 29.9% working hours, p=0.017) than working hours. However, off-hour hospital presentation was not related to poor short-term outcome in subjects with ICH and SAH. Conclusion : This study indicates that off-hour hospital presentation may lead to poor short-term morbidity and mortality in patients with IS, but not in patients with ICH and SAH in Korea. Excessive death seems to be ascribed to old age or the higher severity of medical conditions apart from that of stroke during off hours.

• Tuberculosis and Respiratory Diseases
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• 제83권4호
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• pp.268-275
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• 2020

Background: It is not evident that the attributable risk of smoking on mortality in Korea has decreased. We investigated the impact of smoking on all-cause mortality and estimated the attributable risk of smoking in Korean adults. Methods: Those aged ≥20 years with smoking history in the Korean National Health and Nutrition Examination Surveys (KNHANES) 2007-2015 were enrolled. We categorized the participants into three groups as follows: never smoker, <20 pack-years (PY) smokers, and ≥20 PY smokers. We applied inverse probability weighting using propensity scores to control various confounders between the groups. All-cause mortality risks were compared between the groups using the Kaplan-Meier log-rank test. The effects of smoking-attributable risks (ARs) on mortality were also calculated. Results: A total of 50,458 participants were included. Among them, 19,334 (38.3%) were smokers and 31,124 (61.7%) were never smokers. Those with a smoking history of 20 PY or more (≥20 PY smokers), those with a smoking history of less than 20 PY (<20 PY smokers), and never smokers were 18.1%, 20.2%, and 61.7%, respectively, of the study population. Smokers had a higher risk of all-cause mortality compared to never smokers (log-rank test p<0.01). The ARs of smoking were 21.8% (95% confidence interval [CI], 5.7%-37.9%) and 9.0% (95% CI, 6.1%-12.0%) in males and females, respectively. ARs decreased from 24.2% to 19.5% in males and from 9.5% to 4.1% in females between 2007-2010 and 2011-2015. Conclusion: Our study using KNHANES IV-VI data demonstrated that smoking increased the risk of all-cause mortality in a dose-response manner and the ARs of smoking on mortality were 21.8% in males and 9.0% in females during 2007-2015. This suggests that the ARs of smoking on mortality have decreased since around 2010.

• Journal of Preventive Medicine and Public Health
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• 제39권1호
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• pp.13-20
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• 2006

Objectives: To propose a risk-adjustment model with using insurance claims data and to analyze whether or not the outcomes of non-emergent and isolated coronary artery bypass graft surgery (CABG) differed between the low- and high-volume hospitals for the patients who are at different levels of surgical risk. Methods: This is a cross-sectional study that used the 2002 data of the national health insurance claims. The study data set included the patient level data as well as all the ICD-10 diagnosis and procedure codes that were recorded in the claims. The patient's biological, admission and comorbidity information were used in the risk-adjustment model. The risk factors were adjusted with the logistic regression model. The subjects were classified into five groups based on the predicted surgical risk: minimal (<0.5%), low (0.5% to 2%), moderate (2% to 5%), high (5% to 20%), and severe (=20%). The differences between the low- and high-volume hospitals were assessed in each of the five risk groups. Results: The final risk-adjustment model consisted of ten risk factors and these factors were found to have statistically significant effects on patient mortality. The C-statistic (0.83) and Hosmer-Lemeshow test ($x^2=6.92$, p=0.55) showed that the model's performance was good. A total of 30 low-volume hospitals (971 patients) and 4 high-volume hospitals (1,087 patients) were identified. Significant differences for the in-hospital mortality were found between the low- and high-volume hospitals for the high (21.6% vs. 7.2%, p=0.00) and severe (44.4% vs. 11.8%, p=0.00) risk patient groups. Conclusions: Good model performance showed that insurance claims data can be used for comparing hospital mortality after adjusting for the patients' risk. Negative correlation was existed between surgery volume and in-hospital mortality. However, only patients in high and severe risk groups had such a relationship.

• Asian Pacific Journal of Cancer Prevention
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• 제14권8호
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• pp.4785-4790
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• 2013

Background and Objectives: Evidence for associations between alcohol consumption with breast cancer survival are conflicting, so we conducted the present meta-analysis. Methods: Comprehensive searches were conducted to find cohort studies that evaluated the relationship between alcohol consumption with breast cancer survival. Data were analyzed with meta-analysis software. Results: We included 25 cohort studies. The meta-analysis results showed that alcohol consumption was not associated with increased breast cancer mortality and recurrence after pooling all data from highest versus lowest comparisons. Subgroup analyses showed that pre-diagnostic or post-diagnostic consumpotion, and ER status did not affect the relationship with breast cancer mortality and recurrence. Although the relationships of different alcohol consumption with breast cancer mortality and recurrence were not significant, there seemed to be a dose-response relationship of alcohol consumption with breast cancer mortality and recurrence. Only alcohol consumption of >20 g/d was associated with increased breast cancer mortality, but not with increased breast cancer recurrence. Conclusion: Although our meta-analysis showed alcohol drinking was not associated with increased breast cancer mortality and recurrence, there seemed to be a dose-response relationship of alcohol consumption with breast cancer mortality and recurrence and alcohol consumption of >20 g/d was associated with increased breast cancer mortality.