目的比较CURB一65评分和强化CURB评分对老年重症社区获得性肺炎（severe community acquired pneumonia，SCAP）预后的临床预测价值。方法回顾性分析2009—12—2015-07入住我院急诊科、呼吸内科以及老年呼吸内科的87例老年SCAP相关临床...目的比较CURB一65评分和强化CURB评分对老年重症社区获得性肺炎（severe community acquired pneumonia，SCAP）预后的临床预测价值。方法回顾性分析2009—12—2015-07入住我院急诊科、呼吸内科以及老年呼吸内科的87例老年SCAP相关临床资料，分别统计每例患者的CURB-65评分、强化CURB评分，以患者28d预后为临床观察终点，绘制受试者工作特征（receiver operator characteristic，ROC）曲线，通过比较曲线下面积（area under the curve，AUC）分析两种评分工具对老年SCAP预后的预测价值。结果87例患者CURB一65评分为3（2—3）分，强化CURB评分为11（10～12）分。死亡组中CURB-65评分和强化CURB评分均明显高于存活组，差异有统计学意义（P〈0．05）。强化CURB评分AUC为0．722，最佳截断值为12，敏感度为58．82％，特异度为69．81％，P=0．0001；CURB-65评分AUC为0．660，最佳截断值为3，敏感度为73．53％，特异度为49．06％，P=0．0091。强化CURB评分AUC大于CURB-65评分，差异有统计学意义（0．722vs．0．660，Z=2．176，P=0．029）。结论CURB-65评分和强化CURB评分均可预测老年SCAP预后，强化CURB评分预测价值高于CURB-65评分，且其特异度高于CURB-65评分。展开更多
In order to improve the use efficiency of curb parking, a reasonable curb parking pricing is evaluated by considering individual parking choice behavior. The parking choice behavior is analyzed from micro-aspects, and...In order to improve the use efficiency of curb parking, a reasonable curb parking pricing is evaluated by considering individual parking choice behavior. The parking choice behavior is analyzed from micro-aspects, and the choice behavior utility function is established combining trip time, search time, waiting time, access time and parking fee. By the utility function, a probit-based parking choice behavior model is constructed. On the basis of these, the curb parking pricing model is deduced by considering the constrained conditions, and an incremental assignment algorithm of the model is also designed. Finally, the model is applied to the parking planning of Tongling city. It is pointed out that the average parking time of curb parking decreases 34%, and the average turnover rate increases 67% under the computed parking price system. The results show that the model can optimize the utilization of static traffic facilities.展开更多
文摘目的:探讨基于微小核糖核酸(micrornas,miR)-221-3p、miR-155-5p及英国胸科协会改良肺炎(confusion,uremia,respiratory,BP,age 65years,CURB-65)评分构建的Nomogram预测模型对重症肺炎(severe pneumonia,SP)预后不良的预测价值。方法:前瞻性选取2021年1月至2024年6月宜春市人民医院收治的439例SP患者,按7:3比例随机分为建模组(n=307)与验证组(n=132)。治疗前检测患者血清miR-221-3p、miR-155-5p水平,并使用CURB-65得分进行评估。观察患者住院28 d内预后情况,根据28 d内预后情况将SP患者分为死亡组与存活组。采用Lasso回归分析SP患者预后不好的影响因素,多元素Logistic回归分析SP预后不良的危险因素。构建SP患者预后不良Nomogram预测模型,并采用受试者工作特征(receiver operating characteristic,ROC)曲线评估Nomogram模型对SP预后不良的预测效能。结果:建模组、验证组死亡率分别为29.32%(90/307)、28.79%(38/132),两组死亡率以及临床资料比较无统计学差异(P>0.05)。建模、验证人群中死亡组的年龄、肺部基础疾病比例、肺炎严重指数(pneumonia severity index,PSI)评分、急性生理学和慢性健康状况评分系统Ⅱ(Acute Physiology and Chronic Health EvaluationⅡ,APACHEⅡ)评分、CURB-65评分、血清miR-221-3p、miR-155-5p、C反应蛋白(C-reactive protein,CRP)、白细胞介素-6(interleukin-6,IL-6)、肿瘤坏死因子-α(tumor necrosis factor-α,TNF-α)、降钙素原(procalcitonin,PCT)指标均高于存活组(P<0.05)。Logistic多因素回归分析显示高龄、高APACHEⅡ评分、miR-221-3p高表达、miR-155-5p高表达、高CURB-65评分是SP预后不良的危险因素(P<0.05)。构建的SP预后不良Nomogram预测模型对SP预后不良的曲线下面积(area under the curve,AUC)达0.824,具有良好的预测效能。结论:miR-221-3p高表达、miR-155-5p高表达、高CURB-65评分、高龄、高APACHEⅡ评分是SP患者预后不良的危险因素,基于上述因素构建的Nomogram预测模型对SP预后不良的预测价值较高。
文摘目的比较CURB一65评分和强化CURB评分对老年重症社区获得性肺炎（severe community acquired pneumonia，SCAP）预后的临床预测价值。方法回顾性分析2009—12—2015-07入住我院急诊科、呼吸内科以及老年呼吸内科的87例老年SCAP相关临床资料，分别统计每例患者的CURB-65评分、强化CURB评分，以患者28d预后为临床观察终点，绘制受试者工作特征（receiver operator characteristic，ROC）曲线，通过比较曲线下面积（area under the curve，AUC）分析两种评分工具对老年SCAP预后的预测价值。结果87例患者CURB一65评分为3（2—3）分，强化CURB评分为11（10～12）分。死亡组中CURB-65评分和强化CURB评分均明显高于存活组，差异有统计学意义（P〈0．05）。强化CURB评分AUC为0．722，最佳截断值为12，敏感度为58．82％，特异度为69．81％，P=0．0001；CURB-65评分AUC为0．660，最佳截断值为3，敏感度为73．53％，特异度为49．06％，P=0．0091。强化CURB评分AUC大于CURB-65评分，差异有统计学意义（0．722vs．0．660，Z=2．176，P=0．029）。结论CURB-65评分和强化CURB评分均可预测老年SCAP预后，强化CURB评分预测价值高于CURB-65评分，且其特异度高于CURB-65评分。
基金The National Natural Science Foundation of China(No50308005), the National Basic Research Program of China (973Program) (No2006CB705500)
文摘In order to improve the use efficiency of curb parking, a reasonable curb parking pricing is evaluated by considering individual parking choice behavior. The parking choice behavior is analyzed from micro-aspects, and the choice behavior utility function is established combining trip time, search time, waiting time, access time and parking fee. By the utility function, a probit-based parking choice behavior model is constructed. On the basis of these, the curb parking pricing model is deduced by considering the constrained conditions, and an incremental assignment algorithm of the model is also designed. Finally, the model is applied to the parking planning of Tongling city. It is pointed out that the average parking time of curb parking decreases 34%, and the average turnover rate increases 67% under the computed parking price system. The results show that the model can optimize the utilization of static traffic facilities.
