Zhang Li, Zhao Shuying, Li Fang, Rao Guozheng
School of Economics and Management, Tianjin University of Science and Technology, Tianjin 300457, China.
College of Intelligence and Computing, Tianjin University, Tianjin 300350, China.
Healthcare (Basel). 2020 Aug 24;8(3):295. doi: 10.3390/healthcare8030295.
To the on-site nursing staff or field management in prehospital emergency care, it seems baffling to conduct more targeted checklist tests for a specific disease. To address this problem, we proposed a decision support method for prehospital emergency care based on ranking the importance of physiological variables. We used multiple logistic regression models to explore the effects of various physiological variables on diseases based on the area under the curve (AUC) value. We implemented the method on the intensive care database (i.e., the Medical Information Mart for Intensive Care (MIMIC-III) database) and explored the importance of 17 physiological variables for 24 diseases, both chronic and acute. We included 33,798 adult patients, using the full physiological dataset as experiment data. We ranked the importance of the physiological variables related to the diseases according to the experiments' AUC value. We discussed which physiological variables should be considered more important in adult intensive care units (ICUs) for prehospital emergency care conditions. We also discussed the relationships among the diseases based on ranking the importance of physiological variables. We used large-scale ICU patient data to obtain a cohort of physiological variables related to specific diseases. Ranking a cohort of physiological variables is a cost-effective means of reducing morbidity and mortality under prehospital emergency care conditions.
对于院前急救中的现场护理人员或现场管理人员而言，针对特定疾病进行更具针对性的检查表测试似乎令人困惑。为了解决这个问题，我们提出了一种基于对生理变量重要性进行排序的院前急救决策支持方法。我们使用多个逻辑回归模型，基于曲线下面积（AUC）值来探究各种生理变量对疾病的影响。我们在重症监护数据库（即重症监护医学信息集市（MIMIC-III）数据库）上实施了该方法，并探究了17个生理变量对24种急慢性疾病的重要性。我们纳入了33798名成年患者，使用完整的生理数据集作为实验数据。根据实验的AUC值对与疾病相关的生理变量的重要性进行排序。我们讨论了在院前急救条件下的成人重症监护病房（ICU）中，哪些生理变量应被视为更重要。我们还基于对生理变量重要性的排序讨论了疾病之间的关系。我们使用大规模ICU患者数据来获取与特定疾病相关的一组生理变量。对一组生理变量进行排序是在院前急救条件下降低发病率和死亡率的一种经济有效的方法。
