@article {Chakraborty, Mallinath and Watkins, William John and Tansey, Katherine and King, William E. and Banerjee, Sujoy}， title ={使用早产儿心率特征指数预测拔管结果:队列研究},体积= {56}= {4},elocation-id = {1901755} = {2020}, doi ={10.1183/13993003.01755 -2019},出版商={欧洲呼吸学会},文摘={早期拔管无创呼吸支持的策略在早产儿可能会受到临床医生的决策188bet官网地址支持工具的可用性。利用心率特征指数(HRCi)和临床参数，我们推导并验证了拔管准备和成功的预测模型。在一项涉及8个新生儿中心的随机试验中，收集了一组机械通气婴儿长达96小时的拔管前后人口统计学、临床和HRCi数据，在该试验中，临床医生对HRCi评分不知情。这些数据被用来建立一个关于再次插管概率的多变量回归模型。此外，我们还建立了一个生存模型来估计拔管后再次插管的概率。在577名符合条件的婴儿中，397名(69\%)婴儿的数据被用于推导拔管前模型，180名(31\%)婴儿的数据被用于验证。该模型还采用了培训(五个中心)和测试(三个中心)中心的所有组合进行了拟合和验证。验证集的估计概率显示了具有高统计学意义的区别，曲线下的面积为0.72 (95\% CI 0.71{\textendash}0.74;p < 0.001)。 Data from all infants were used to derive models of the predictive instantaneous hazard of re-intubation adjusted for clinical parameters.Predictive models of extubation readiness and success in real-time can be derived using physiological and clinical variables. The models from our analyses can be accessed using an online tool available at www.heroscore.com/extubation, and have the potential to inform and supplement the confidence of the clinician considering extubation in preterm infants.Using the Heart Rate Characteristics index, we have derived models predicting extubation outcomes for preterm infants, both for extubation readiness and success. These models are intended as a decision support tool for clinicians. https://bit.ly/2LKNEKk}, issn = {0903-1936}, URL = {//www.qdcxjkg.com/content/56/4/1901755}, eprint = {//www.qdcxjkg.com/content/56/4/1901755.full.pdf}, journal = {European Respiratory Journal} }