目的·探讨基于EMS[环境管理(environment management,E)、用药指导(medicine direction,M)与自我监测(self monitoring,S)]管理模式的延续性护理在学龄前喘息性疾病儿童中的应用效果。方法·选取2019年12月至2020年11月,在上...目的·探讨基于EMS[环境管理(environment management,E)、用药指导(medicine direction,M)与自我监测(self monitoring,S)]管理模式的延续性护理在学龄前喘息性疾病儿童中的应用效果。方法·选取2019年12月至2020年11月,在上海交通大学医学院附属儿童医院呼吸科收治的67例0~6岁喘息性疾病患儿,按照随机数字表分为观察组33例和对照组34例,其中失访3例,最终每组32例。观察组采用基于EMS管理模式的延续性护理,对照组给予常规护理和出院电话随访。2组患儿出院后1、3、6个月随访评估儿童呼吸和哮喘测试(Test for Respiratory and Asthma Control in Kids,TRACK)结果、喘息复发情况;出院后6个月随访采用支气管哮喘用药依从性评分表(Medication Adherence Report Scale for Asthma,MARS-A)和护理工作满意度调查表评估用药依从性及护理工作满意度。结果·2组患儿人口学特征及临床基线特征差异无统计学意义。重复测量方差分析结果显示,时间、组别、组别×时间的交互作用对TRACK总分的影响均有统计学意义;出院后1、3、6个月,观察组TRACK总分均显著高于对照组(均P=0.000);2组患儿TRACK总分均随时间推移逐渐上升(P=0.000)。观察组1、3、6个月随访发现喘息复发率分别为25.0%、18.7%、9.4%,均显著低于对照组(分别为50.0%、43.7%、31.3%,均P<0.05);广义估计方程分析显示组间比较差异有统计学意义(P=0.013),观察组干预效果优于对照组(OR=0.292)。出院后6个月观察组MARS-A得分为(4.519±0.395)分,显著高于对照组[(3.994±0.739)分,P=0.001]。护理工作满意度调查结果显示,观察组显著高于对照组(P=0.000)。患儿MARS-A得分与护理工作满意度呈中度正相关(r=0.389,P=0.001)。结论·基于EMS管理模式的延续性护理可显著提高学龄前喘息性疾病儿童的用药依从性和喘息控制水平,明显降低喘息复发率,以及提高护理工作满意度。展开更多
This study presents a kinematic calibration method for exoskeletal inertial motion capture (EI-MoCap) system with considering the random colored noise such as gyroscopic drift.In this method, the geometric parameters ...This study presents a kinematic calibration method for exoskeletal inertial motion capture (EI-MoCap) system with considering the random colored noise such as gyroscopic drift.In this method, the geometric parameters are calibrated by the traditional calibration method at first. Then, in order to calibrate the parameters affected by the random colored noise, the expectation maximization (EM) algorithm is introduced. Through the use of geometric parameters calibrated by the traditional calibration method, the iterations under the EM framework are decreased and the efficiency of the proposed method on embedded system is improved. The performance of the proposed kinematic calibration method is compared to the traditional calibration method. Furthermore, the feasibility of the proposed method is verified on the EI-MoCap system. The simulation and experiment demonstrate that the motion capture precision is significantly improved by 16.79%and 7.16%respectively in comparison to the traditional calibration method.展开更多
文摘目的·探讨基于EMS[环境管理(environment management,E)、用药指导(medicine direction,M)与自我监测(self monitoring,S)]管理模式的延续性护理在学龄前喘息性疾病儿童中的应用效果。方法·选取2019年12月至2020年11月,在上海交通大学医学院附属儿童医院呼吸科收治的67例0~6岁喘息性疾病患儿,按照随机数字表分为观察组33例和对照组34例,其中失访3例,最终每组32例。观察组采用基于EMS管理模式的延续性护理,对照组给予常规护理和出院电话随访。2组患儿出院后1、3、6个月随访评估儿童呼吸和哮喘测试(Test for Respiratory and Asthma Control in Kids,TRACK)结果、喘息复发情况;出院后6个月随访采用支气管哮喘用药依从性评分表(Medication Adherence Report Scale for Asthma,MARS-A)和护理工作满意度调查表评估用药依从性及护理工作满意度。结果·2组患儿人口学特征及临床基线特征差异无统计学意义。重复测量方差分析结果显示,时间、组别、组别×时间的交互作用对TRACK总分的影响均有统计学意义;出院后1、3、6个月,观察组TRACK总分均显著高于对照组(均P=0.000);2组患儿TRACK总分均随时间推移逐渐上升(P=0.000)。观察组1、3、6个月随访发现喘息复发率分别为25.0%、18.7%、9.4%,均显著低于对照组(分别为50.0%、43.7%、31.3%,均P<0.05);广义估计方程分析显示组间比较差异有统计学意义(P=0.013),观察组干预效果优于对照组(OR=0.292)。出院后6个月观察组MARS-A得分为(4.519±0.395)分,显著高于对照组[(3.994±0.739)分,P=0.001]。护理工作满意度调查结果显示,观察组显著高于对照组(P=0.000)。患儿MARS-A得分与护理工作满意度呈中度正相关(r=0.389,P=0.001)。结论·基于EMS管理模式的延续性护理可显著提高学龄前喘息性疾病儿童的用药依从性和喘息控制水平,明显降低喘息复发率,以及提高护理工作满意度。
基金supported by the National Natural Science Foundation of China (61503392)。
文摘This study presents a kinematic calibration method for exoskeletal inertial motion capture (EI-MoCap) system with considering the random colored noise such as gyroscopic drift.In this method, the geometric parameters are calibrated by the traditional calibration method at first. Then, in order to calibrate the parameters affected by the random colored noise, the expectation maximization (EM) algorithm is introduced. Through the use of geometric parameters calibrated by the traditional calibration method, the iterations under the EM framework are decreased and the efficiency of the proposed method on embedded system is improved. The performance of the proposed kinematic calibration method is compared to the traditional calibration method. Furthermore, the feasibility of the proposed method is verified on the EI-MoCap system. The simulation and experiment demonstrate that the motion capture precision is significantly improved by 16.79%and 7.16%respectively in comparison to the traditional calibration method.