Over the past four decades after World War II a great deal of data and clinical experiences have been accumulated relating to the diagnosis and surgical treatment of cardiovascular diseases in Korea. Clinical data after the first open heart surgery by Professor Yung Kyoon Lee on August 7, 1959 up to 1984 revealed the total number of cardiovascular surgery in Korea as 13,100 cases performed in 22 institutes with overall hospital mortality of 7.7%[Cardiovascular Surgery in Korea 1985], Publishing committee of the Korean Thoracic and Cardiovascular Surgical Society collected the data of cardiovascular surgical cases in Korea again in between 1985 and 1990 from 38 institutes out of total 42 institutes of open heart centers in Korea. The results are: 1. The survey reply ratio was 90.5%[38 out of 42 institutes]. 2. Of the total 30,061 cases of cardiovascular surgery reported from 38 institutes 1,402 cases were failed as hospital mortality of 4.7%[4.5% of the 21,761 operations for congenital, and 5.2% of the 8,300 operations for acquired heart diseases]. Out of the total congenital cases, 17,303 cases were acyanotic group with a operative mortality as 2.0%, and 4,458 cases were cyanotic group with a hospital mortality as 14.le The incidence of corrective operations for complex congenital cardiac anomalies were increasing recently with decreasing age group. 3. During the year in 1990, 38 institutes performed 5,427 cardiovascular surgery with a hospital mortality of 3.4%. 4. Of the total cumulative 6,458 cases for cardiac valve surgery more than 90% cases were put to prosthetic valve replacement with hospital mortality as 4.8%. And the incidence of re-Do valve surgery was increasing recently as 13.1% in 1990. 5. Coronary artery bypass graft was increasing recently with 7.9% of hospital mortality in total 440 cases. Intracardiac operation for intractable arrhythmia was started since 1987 as 49 cases in total. Experiences on VAD and ECMO were also reported sporadically in recent year. 6. Home made oxygenator[OXYREX] is now in clinical use, and under animal experiment for clinical trial in near future.
Purpose: This study was to evaluate the validity of the Pediatric Index of Mortality Ⅱ(PIM Ⅱ). Method: The first values on PIM Ⅱ variables following ICU admission were collected from the patient's charts of 548 admissions retrospectively in three ICUs(medical, surgical, and neurosurgical) at P University Hospital and a cardiac ICU at D University Hospital in Busan from January 1, 2002 to December 31, 2003. Data was analyzed with the SPSSWIN 10.0 program for the descriptive statistics, correlation coefficient, standardized mortality ratio(SMR), validity index(sensitivity, specificity, positive predictive value, negative predictive value), and AUC of ROC curve. Result: The mortality rate was 10.9% (60 cases) and the predicted death rate was 9.5%. The correlation coefficient(r) between observed and expected death rates was .929(p<.01) and SMR was 1.15. Se, Sp, pPv, nPv, and the correct classification rate were .80, .96, .70, .98, and 94.0% respectively. In addition, areas under the curve (AUC) of the receiver operating characteristic(ROC) was 0.954 (95% CI=0.919~0.989). According to demographic characteristics, mortality was underestimated in the medical group and overestimated in the surgical group. In addition, the AUCs of ROC curve were generally high in all subgroups. Conclusion: The PIM Ⅱ showed a good, so it can be utilized for the subject hospital. better.
Objectives: To evaluate the performance of models to predict AMI patients death using severity adjustment measures in Korea. Methods: Medical records of 861 patients treated by AMI in 7 general hospitals during 1996 and 1997 were reviewed by trained nurses. We measured the severity of patients by APACHE III, MedisGroups, CSI and DS. Using each severity method a predictive mortality for each patient was calculated from a logistic regression model including the severity score. The statistical performance of each severity method model was evaluated by using c-statistics and R2. For each hospital, z scores compared actual and expected mortality rates. Results: The overall in-hospital mortality was 14.5%, ranged from 10.0% to 22.2%. The distributions of severity scores for each method was significantly different by hospitals. The four severity-adjusted models to predict AMI patients death varied in their statistical performance for discrimination power of patients death. Order of Severity-adjusted mortality rates and z scores by four severity measures was different. Conclusion: Severity-adjusted mortality rates of AMI patients might be applied as an indicator for hospital performance evaluation in Korea. Because different severity methods frequently produce different impressions about relative hospital performance, more studies has to be done to use it as quality indicator and more attention should be paid to select appropriate severity measures.
Kim, Jae-Hyun;Park, Eun-Cheol;Kim, Young Hoon;Kim, Tae Hyun;Lee, Kwang Soo;Lee, Sang Gyu
Health Policy and Management
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v.28
no.1
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pp.53-69
/
2018
Background: This study investigates association modified category medical specialization (CMS) and hospital charge, length of stay (LOS), and mortality among lumbar spine disease inpatients. Methods: This study used National Health Insurance Service-cohort sample database from 2002 to 2013, using stratified representative sampling released by the National Health Insurance Service. A total of 56,622 samples were analyzed. The primary analysis was based on generalized estimating equation model accounting for correlation among individuals within each hospital. Results: Inpatients admitted with lumbar spine disease at hospitals with higher modified CMS had a shorter LOS (estimate, -1.700; 95% confidence interval [CI], -1.886 to -1.514; p<0.0001). Inpatients admitted with lumbar spine disease at hospitals with higher modified CMS had a lower mortality rate (odds ratio, 0.635; 95% CI, 0.521 to 0.775; p<0.0001). Inpatients admitted with lumbar spine disease at hospitals with higher modified CMS had higher hospital cost per case (estimate, 192,658 Korean won; 95% CI, 125,701 to 259,614; p<0.0001). However, inpatients admitted with lumbar spine surgery patients at hospitals with higher modified CMS had lower hospital cost per case (estimate, -152,060 Korean won; 95% CI, -287,236 to -16,884; p=0.028). Inpatients admitted with lumbar spine disease at hospitals with higher modified CMS had higher hospital cost per diem (estimate, 55,694 Korean won; 95% CI, 46,205 to 65,183; p<0.0001). Conclusion: Our results showed that increase in hospital specialization had a substantial effect on decrease in hospital cost per case, LOS, and mortality, and on increase in hospital cost per diem among lumbar spine disease surgery patients.
Purposes: This study purposed to evaluate the effect of a value incentive program(VIP) on the in-hospital mortality of acute stroke. Methodology: Study period was from January 2010 to December 2018. This study included 63 hospitals for acute hemorrhagic stroke that the mortality rate per month was more than one during study period. Independent variables were time variables and hospital characteristics such as hospital type, district and bed number. Interrupted time series analysis was applied to analyze the data. Findings: In case of general hospitals, the in-hospital mortality rate per month for acute hemorrhagic stroke tends to be increased by 0.03% in overall study periods but decreased by 0.32% after the implementation of the policy. On the other hand, tertiary hospital changes are not statistically meaningful. Conclusion: This study provides evidences how the VIP was effective in improving quality of acute hemorrhagic stroke care. General hospitals showed higher policy effect compare to that of tertiary hospitals.
Objectives: Prospective studies on vaccination status and mortality related to coronavirus disease 2019 (COVID-19) in low-resource settings are still limited. We assessed the association between vaccination status (full, partial, or none) and in-hospital mortality among COVID-19 patients at most hospitals in Jakarta, Indonesia during the Delta predomination wave. Methods: We conducted a retrospective cohort study among hospitalized COVID-19 patients who met the study criteria (>18 years old and admitted for inpatient treatment because of laboratory-confirmed severe acute respiratory syndrome coronavirus 2 infection). We linked individual-level data in the hospital admission database with vaccination records. Several socio-demographic and clinical characteristics were also analyzed. A Cox proportional hazards regression model was used to explore the association between vaccination status and in-hospital mortality in this patient group. Results: In total, 40 827 patients were included in this study. Of these, 70% were unvaccinated (n=28 543) and 19.3% (n=7882) died during hospitalization. The mean age of the patients was 49 years (range, 35-59), 53.2% were female, 22.0% had hypertension, and 14.2% were treated in the intensive care unit, and the median hospital length of stay across the group was 9 days. Our study showed that the risk of in-hospital mortality among fully and partially vaccinated patients was lower than among unvaccinated adults (adjusted hazard ratio [aHR], 0.43; 95% confidence interval [CI], 0.40 to 0.47 and aHR, 0.70; 95% CI, 0.64 to 0.77, respectively). Conclusions: Vaccinated patients had fewer severe outcomes among hospitalized adults during the Delta wave in Jakarta. These features should be carefully considered by healthcare professionals in treating adults within this patient group.
Background: External-cause mortality is an important public health issue worldwide. Considering its significance to workers' health and inequalities across industries, we aimed to describe the state of external-cause mortality and investigate its difference by industry in Republic of Korea based on data for 2018. Methods: Data obtained from the Statistics Korea and Korean Employment Information System were used. External causes of death were divided into three categories (suicide, transport accident, and others), and death occurred during employment period or within 90 days after unemployment was regarded as workers' death. We calculated age- and sex-standardized mortalities per 100,000, standardized mortality ratios (SMRs) compared to the general population and total workers, and mortality rate ratios (RRs) across industries using information and communication as a reference. Correlation analyses between income, education, and mortality were conducted. Results: Age- and sex-standardized external-cause mortality per 100,000 in all workers was 29.4 (suicide: 16.2, transport accident: 6.6, others: 6.6). Compared to the general population, all external-cause and suicide SMRs were significantly lower; however, there was no significant difference in transport accidents. When compared to total workers, wholesale, transportation, and business facilities management showed higher SMR for suicide, and agriculture, forestry, and fishing, mining and quarrying, construction, transportation and storage, and public administration and defense showed higher SMR for transport accidents. A moderate to strong negative correlation was observed between education level and mortality (both age- and sex-standardized mortality rates and SMR compared to the general population). Conclusion: Inequalities in external-cause mortalities from suicide, transport accidents, and other causes were found. For reducing the differences, improved policies are needed for industries with higher mortalities.
da Costa, Joao Cordeiro;Manso, Maria Conceicao;Gregorio Susana;Leite, Marcia;Pinto, Joao Moreira
Tuberculosis and Respiratory Diseases
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v.85
no.4
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pp.349-357
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2022
Background: The most consistently identified mortality determinants for the new coronavirus 2019 (COVID-19) infection are aging, male sex, cardiovascular/respiratory diseases, and cancer. They were determined from heterogeneous cohorts that included patients with different disease severity and previous conditions. The main goal of this study was to determine if activities of daily living (ADL) dependence measured by Barthel's index could be a predictor for COVID-19 mortality. Methods: A prospective cohort study was performed with a consecutive sample of 340 COVID-19 patients representing patients from all over the northern region of Portugal from October 2020 to March 2021. Mortality risk factors were determined after controlling for demographics, ADL dependence, admission time, comorbidities, clinical manifestations, and delay-time for diagnosis. Central tendency measures were used to analyze continuous variables and absolute numbers (proportions) for categorical variables. For univariable analysis, we used t test, chi-square test, or Fisher exact test as appropriate (α=0.05). Multivariable analysis was performed using logistic regression. IBM SPSS version 27 statistical software was used for data analysis. Results: The cohort included 340 patients (55.3% females) with a mean age of 80.6±11.0 years. The mortality rate was 19.7%. Univariate analysis revealed that aging, ADL dependence, pneumonia, and dementia were associated with mortality and that dyslipidemia and obesity were associated with survival. In multivariable analysis, dyslipidemia (odds ratio [OR], 0.35; 95% confidence interval [CI], 0.17-0.71) was independently associated with survival. Age ≥86 years (pooled OR, 2.239; 95% CI, 1.100-4.559), pneumonia (pooled OR, 3.00; 95% CI, 1.362-6.606), and ADL dependence (pooled OR, 6.296; 95% CI, 1.795-22.088) were significantly related to mortality (receiver operating characteristic area under the curve, 82.1%; p<0.001). Conclusion: ADL dependence, aging, and pneumonia are three main predictors for COVID-19 mortality in an elderly population.
Background: Although the mortality rate in cancers has been decreased recently, it is still one of the leading causes of death in most of the countries. This study analyzed the relationship between surgery volume and in hospital mortality of cancer patients. The purpose of this study is to investigate the relationship in Korean healthcare environment and to provide information for the policy development in reducing cancer mortality. Methods: The study sample was the 20,517 cancer patients who underwent surgery and discharged during a month period between 2008-2011. The data were collected in Patient Survey by Korean Institute of Social Affairs. Logistic regression was used to analyse a comprehensive analytic model that includes a binary dependent variable indicating death discharge and independent variables such as surgery volume, organizational characteristics of hospitals, socio-economical characteristics of the patients, and severity of disease indicators. Results: In chi-square test, as the surgery volume increases, the in-hospitals mortality showed a downward trends. In regression analysis, the relationship between surgery volume and mortality showed significant negative associations in all types of cancer except for pancreatic cancer. Conclusion: In the absence of other information patients undergoing cancer surgery can reduce their risk of operative death by selecting a high-volume hospital. Therefore, policies to enhance centralization of cancer surgery services should be considered.
Kim, Ho Jin;Kim, Joon Bum;Kim, Seon-Ok;Yun, Sung-Cheol;Lee, Sak;Lim, Cheong;Choi, Jae Woong;Hwang, Ho Young;Kim, Kyung Hwan;Lee, Seung Hyun;Yoo, Jae Suk;Sung, Kiick;Je, Hyung Gon;Hong, Soon Chang;Kim, Yun Jung;Kim, Sung-Hyun;Chang, Byung-Chul
Journal of Chest Surgery
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v.54
no.2
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pp.88-98
/
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.
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