目的:探讨低致吐化疗药物(low-emetic-risk chemotherapy,LEC)引发延迟性化疗相关恶心呕吐(chemotherapy-induced nausea and vomiting,CINV)的风险因素,以帮助个体化止吐和止呕。方法:在2016年9月至2018年9月期间收治的接受LEC治疗的...目的:探讨低致吐化疗药物(low-emetic-risk chemotherapy,LEC)引发延迟性化疗相关恶心呕吐(chemotherapy-induced nausea and vomiting,CINV)的风险因素,以帮助个体化止吐和止呕。方法:在2016年9月至2018年9月期间收治的接受LEC治疗的实体瘤患者。在患者接受LEC的第一个周期开始每天记录恶心、呕吐情况,连续记录5日,以描述CINV的每日发病情况。结果:共125名患者具有完善的信息记录,这些患者不同程度的延迟性CINV发生率为28.8%。使用多变量逻辑回归分析延迟CINV的风险因素,结果显示ECOG评分≥1、出现急性CINV和单日预防止吐被确定为延迟CINV的独立危险因素。结论:LEC引发延迟性恶心呕吐更常见于体力状态差、有急性CINV发生、仅接受单日预防止吐治疗的患者。对这些患者应根据其症状调整预防止吐方案。展开更多
High-precision filtering estimation is one of the key techniques for strapdown inertial navigation system/global navigation satellite system(SINS/GNSS)integrated navigation system,and its estimation plays an important...High-precision filtering estimation is one of the key techniques for strapdown inertial navigation system/global navigation satellite system(SINS/GNSS)integrated navigation system,and its estimation plays an important role in the performance evaluation of the navigation system.Traditional filter estimation methods usually assume that the measurement noise conforms to the Gaussian distribution,without considering the influence of the pollution introduced by the GNSS signal,which is susceptible to external interference.To address this problem,a high-precision filter estimation method using Gaussian process regression(GPR)is proposed to enhance the prediction and estimation capability of the unscented quaternion estimator(USQUE)to improve the navigation accuracy.Based on the advantage of the GPR machine learning function,the estimation performance of the sliding window for model training is measured.This method estimates the output of the observation information source through the measurement window and realizes the robust measurement update of the filter.The combination of GPR and the USQUE algorithm establishes a robust mechanism framework,which enhances the robustness and stability of traditional methods.The results of the trajectory simulation experiment and SINS/GNSS car-mounted tests indicate that the strategy has strong robustness and high estimation accuracy,which demonstrates the effectiveness of the proposed method.展开更多
文摘目的:探讨低致吐化疗药物(low-emetic-risk chemotherapy,LEC)引发延迟性化疗相关恶心呕吐(chemotherapy-induced nausea and vomiting,CINV)的风险因素,以帮助个体化止吐和止呕。方法:在2016年9月至2018年9月期间收治的接受LEC治疗的实体瘤患者。在患者接受LEC的第一个周期开始每天记录恶心、呕吐情况,连续记录5日,以描述CINV的每日发病情况。结果:共125名患者具有完善的信息记录,这些患者不同程度的延迟性CINV发生率为28.8%。使用多变量逻辑回归分析延迟CINV的风险因素,结果显示ECOG评分≥1、出现急性CINV和单日预防止吐被确定为延迟CINV的独立危险因素。结论:LEC引发延迟性恶心呕吐更常见于体力状态差、有急性CINV发生、仅接受单日预防止吐治疗的患者。对这些患者应根据其症状调整预防止吐方案。
基金supported by the National Natural Science Foundation of China(61873275,61703419,425317829).
文摘High-precision filtering estimation is one of the key techniques for strapdown inertial navigation system/global navigation satellite system(SINS/GNSS)integrated navigation system,and its estimation plays an important role in the performance evaluation of the navigation system.Traditional filter estimation methods usually assume that the measurement noise conforms to the Gaussian distribution,without considering the influence of the pollution introduced by the GNSS signal,which is susceptible to external interference.To address this problem,a high-precision filter estimation method using Gaussian process regression(GPR)is proposed to enhance the prediction and estimation capability of the unscented quaternion estimator(USQUE)to improve the navigation accuracy.Based on the advantage of the GPR machine learning function,the estimation performance of the sliding window for model training is measured.This method estimates the output of the observation information source through the measurement window and realizes the robust measurement update of the filter.The combination of GPR and the USQUE algorithm establishes a robust mechanism framework,which enhances the robustness and stability of traditional methods.The results of the trajectory simulation experiment and SINS/GNSS car-mounted tests indicate that the strategy has strong robustness and high estimation accuracy,which demonstrates the effectiveness of the proposed method.
