目的探讨基础疾病评分系统查尔森基础疾病权重指数(Charlson’s weighted index of comorbidities,WIC)评估脓毒症患者预后的价值。方法回顾性分析3年收治的234例脓毒症患者的临床资料,计算WIC评分及急性病理生理和慢性健康状况评分Ⅱ(A...目的探讨基础疾病评分系统查尔森基础疾病权重指数(Charlson’s weighted index of comorbidities,WIC)评估脓毒症患者预后的价值。方法回顾性分析3年收治的234例脓毒症患者的临床资料,计算WIC评分及急性病理生理和慢性健康状况评分Ⅱ(APACHEⅡ),根据28d预后情况分为存活组和死亡组,分析WIC评分对患者预后的评估价值。结果共有234例脓毒症患者纳入研究,死亡77例(32.9%)。WIC评分越高,患者的死亡风险越大;多因素logistic回归分析提示WIC评分是决定脓毒症患者预后的危险因素(OR=1.434,95%CI:1.097～1.875,P=0.008);WIC评分、APACHEⅡ评分以及两者联合预测死亡概率的ROC曲线下面积(95%CI)分别0.670(0.591～0.748)、0.770(0.703～0.837)和0.821(0.757～0.885)。结论 WIC评分可以较好地评估基础疾病对于危重病患者预后的影响。展开更多
For a computer to perform intelligent information processing requires functions that can extract concepts from words, as humans do, and then associate those concepts with related concepts. In order to implement this a...For a computer to perform intelligent information processing requires functions that can extract concepts from words, as humans do, and then associate those concepts with related concepts. In order to implement this association function, it is necessary to quantify the degree of association between two concepts. In the present paper, we propose a method for quantifying degree of association focusing on the viewpoint that uses a concept base （a knowledge base that expresses concepts as a collection of pairs, each pair consisting of an attribute word used to describe the concept and a weighting that expresses the word＇s importance）. Here, ＂Viewpoint＂ is the perspective from which a concept is viewed; for example, consider the degree of association between ＂airplane＂ and ＂automobile＂, and the degree of association between ＂airplane＂ and ＂bird＂. From the viewpoint of ＂vehicle＂, ＂airplane＂ and ＂automobile＂ are highly related, while from the viewpoint of ＂flight＂, ＂airplane＂ and ＂bird＂ are highly related. We present herein a comparison of two methods for calculating degree of association focusing on the viewpoint, and demonstrate that the method involving modulation of attribute weightings based on viewpoint results in degree of association calculations that are closer to human senses.展开更多
文摘目的探讨基础疾病评分系统查尔森基础疾病权重指数(Charlson’s weighted index of comorbidities,WIC)评估脓毒症患者预后的价值。方法回顾性分析3年收治的234例脓毒症患者的临床资料,计算WIC评分及急性病理生理和慢性健康状况评分Ⅱ(APACHEⅡ),根据28d预后情况分为存活组和死亡组,分析WIC评分对患者预后的评估价值。结果共有234例脓毒症患者纳入研究,死亡77例(32.9%)。WIC评分越高,患者的死亡风险越大;多因素logistic回归分析提示WIC评分是决定脓毒症患者预后的危险因素(OR=1.434,95%CI:1.097～1.875,P=0.008);WIC评分、APACHEⅡ评分以及两者联合预测死亡概率的ROC曲线下面积(95%CI)分别0.670(0.591～0.748)、0.770(0.703～0.837)和0.821(0.757～0.885)。结论 WIC评分可以较好地评估基础疾病对于危重病患者预后的影响。
文摘For a computer to perform intelligent information processing requires functions that can extract concepts from words, as humans do, and then associate those concepts with related concepts. In order to implement this association function, it is necessary to quantify the degree of association between two concepts. In the present paper, we propose a method for quantifying degree of association focusing on the viewpoint that uses a concept base （a knowledge base that expresses concepts as a collection of pairs, each pair consisting of an attribute word used to describe the concept and a weighting that expresses the word＇s importance）. Here, ＂Viewpoint＂ is the perspective from which a concept is viewed; for example, consider the degree of association between ＂airplane＂ and ＂automobile＂, and the degree of association between ＂airplane＂ and ＂bird＂. From the viewpoint of ＂vehicle＂, ＂airplane＂ and ＂automobile＂ are highly related, while from the viewpoint of ＂flight＂, ＂airplane＂ and ＂bird＂ are highly related. We present herein a comparison of two methods for calculating degree of association focusing on the viewpoint, and demonstrate that the method involving modulation of attribute weightings based on viewpoint results in degree of association calculations that are closer to human senses.
