AIM: To investigate outcomes and predictors of inhospital morbidity and mortality after total pancreatectomy(TP) and islet autotransplantation. METHODS: The nationwide inpatient sample(NIS) database was used to identi...AIM: To investigate outcomes and predictors of inhospital morbidity and mortality after total pancreatectomy(TP) and islet autotransplantation. METHODS: The nationwide inpatient sample(NIS) database was used to identify patients who underwent TP and islet autotransplantation(IAT) between 2002-2012 in the United States. Variables of interest were inherent variables of NIS database which included demographic data(age, sex, and race), comorbidities(such as diabetes mellitus, hypertension, and deficiency anemia), and admission type(elective vs nonelective). The primary endpoints were mortality and postoperative complications according to the ICD-9 diagnosis codes which were reported as the second to 25 th diagnosis of patients in the database. Risk adjusted analysis was performed to investigate morbidity predictors. Multivariate regression analysis was used to identify predictors of in-hospital morbidity.RESULTS: We evaluated a total of 923 patients who underwent IAT after pancreatectomy during 2002-2012. Among them, there were 754 patients who had TP + IAT. The most common indication ofsurgery was chronic pancreatitis(86%) followed by acute pancreatitis(12%). The number of patients undergoing TP + IAT annually significantly increased during the 11 years of study from 53 cases in 2002 to 155 cases in 2012. Overall mortality and morbidity of patients were 0% and 57.8 %, respectively. Postsurgical hypoinsulinemia was reported in 42.3% of patients, indicating that 57.7% of patients were insulin independent during hospitalization. Predictors of inhospital morbidity were obesity [adjusted odds ratio(AOR): 3.02, P = 0.01], fluid and electrolyte disorders(AOR: 2.71, P < 0.01), alcohol abuse(AOR: 2.63, P < 0.01), and weight loss(AOR: 2.43, P < 0.01). CONCLUSION: TP + IAT is a safe procedure with no mortality, acceptable morbidity, and achieved high rate of early insulin independence. Obesity is the most significant predictor of in-hospital morbidity.展开更多
核电站数字化仪控系统(Digital Control System,简称DCS)是核电站的信息神经和控制中枢,对于保证核电站安全、可靠、稳定和经济运行以及提升生产管理水平都起着至关重要的作用。但长期以来这一关键系统却被国外供应商垄断,这种现状不符...核电站数字化仪控系统(Digital Control System,简称DCS)是核电站的信息神经和控制中枢,对于保证核电站安全、可靠、稳定和经济运行以及提升生产管理水平都起着至关重要的作用。但长期以来这一关键系统却被国外供应商垄断,这种现状不符合国家推进核电设备国产化的战略要求,为此实现核电站数字化仪控系统设备国产化和设计自主化迫在眉睫。本文作者从核电站非安全级数字化仪控系统国产化及自主化工作实践的基础上,对核电站非安全级仪控系统设备国产化、设计自主化的过程进行了相关的探讨和介绍。展开更多
This paper proposes a new approach of feature selection based on the independent measure between features for text categorization. A fundamental hypothesis that occurrence of the terms in documents is independent of e...This paper proposes a new approach of feature selection based on the independent measure between features for text categorization. A fundamental hypothesis that occurrence of the terms in documents is independent of each other, widely used in the probabilistic models for text categorization （TC）, is discussed. However, the basic hypothesis is incom plete for independence of feature set. From the view of feature selection, a new independent measure between features is designed, by which a feature selection algorithm is given to ob rain a feature subset. The selected subset is high in relevance with category and strong in independence between features, satisfies the basic hypothesis at maximum degree. Compared with other traditional feature selection method in TC （which is only taken into the relevance account）, the performance of feature subset selected by our method is prior to others with experiments on the benchmark dataset of 20 Newsgroups.展开更多
文摘AIM: To investigate outcomes and predictors of inhospital morbidity and mortality after total pancreatectomy(TP) and islet autotransplantation. METHODS: The nationwide inpatient sample(NIS) database was used to identify patients who underwent TP and islet autotransplantation(IAT) between 2002-2012 in the United States. Variables of interest were inherent variables of NIS database which included demographic data(age, sex, and race), comorbidities(such as diabetes mellitus, hypertension, and deficiency anemia), and admission type(elective vs nonelective). The primary endpoints were mortality and postoperative complications according to the ICD-9 diagnosis codes which were reported as the second to 25 th diagnosis of patients in the database. Risk adjusted analysis was performed to investigate morbidity predictors. Multivariate regression analysis was used to identify predictors of in-hospital morbidity.RESULTS: We evaluated a total of 923 patients who underwent IAT after pancreatectomy during 2002-2012. Among them, there were 754 patients who had TP + IAT. The most common indication ofsurgery was chronic pancreatitis(86%) followed by acute pancreatitis(12%). The number of patients undergoing TP + IAT annually significantly increased during the 11 years of study from 53 cases in 2002 to 155 cases in 2012. Overall mortality and morbidity of patients were 0% and 57.8 %, respectively. Postsurgical hypoinsulinemia was reported in 42.3% of patients, indicating that 57.7% of patients were insulin independent during hospitalization. Predictors of inhospital morbidity were obesity [adjusted odds ratio(AOR): 3.02, P = 0.01], fluid and electrolyte disorders(AOR: 2.71, P < 0.01), alcohol abuse(AOR: 2.63, P < 0.01), and weight loss(AOR: 2.43, P < 0.01). CONCLUSION: TP + IAT is a safe procedure with no mortality, acceptable morbidity, and achieved high rate of early insulin independence. Obesity is the most significant predictor of in-hospital morbidity.
文摘核电站数字化仪控系统(Digital Control System,简称DCS)是核电站的信息神经和控制中枢,对于保证核电站安全、可靠、稳定和经济运行以及提升生产管理水平都起着至关重要的作用。但长期以来这一关键系统却被国外供应商垄断,这种现状不符合国家推进核电设备国产化的战略要求,为此实现核电站数字化仪控系统设备国产化和设计自主化迫在眉睫。本文作者从核电站非安全级数字化仪控系统国产化及自主化工作实践的基础上,对核电站非安全级仪控系统设备国产化、设计自主化的过程进行了相关的探讨和介绍。
基金Supported by the National Natural Science Foun-dation of China (60373066 ,60503020) the Outstanding Young Sci-entist’s Fund(60425206) Doctor Foundatoin of Nanjing Universityof Posts and Telecommunications (2003-02)
文摘This paper proposes a new approach of feature selection based on the independent measure between features for text categorization. A fundamental hypothesis that occurrence of the terms in documents is independent of each other, widely used in the probabilistic models for text categorization （TC）, is discussed. However, the basic hypothesis is incom plete for independence of feature set. From the view of feature selection, a new independent measure between features is designed, by which a feature selection algorithm is given to ob rain a feature subset. The selected subset is high in relevance with category and strong in independence between features, satisfies the basic hypothesis at maximum degree. Compared with other traditional feature selection method in TC （which is only taken into the relevance account）, the performance of feature subset selected by our method is prior to others with experiments on the benchmark dataset of 20 Newsgroups.
