基于无创参数辨识儿科ARDS患者疾病程度的研究

王萌萌; 王业军

doi:10.13201/j.issn.1009-5918.2019.01.011

基于无创参数辨识儿科ARDS患者疾病程度的研究

王萌萌¹,
王业军^2, ,

- 1 青岛市妇女儿童医院儿科(山东青岛, 266000);
- 2 青岛市妇女儿童医院急诊科

详细信息

通讯作者: 王业军,E-mail:qdwyj2008@126.com

中图分类号: R563.8

收稿日期: 2018-09-19

Research on algorithms for identifying the severity of pediatric patients with ARDS based on noninvasive parameters

WANG Mengmeng¹,
WANG Yejun^2, ,

- 1 Department of Pediatrics, Qingdao Women and Children Hospital, Qingdao, Shandong, 266000, China;
- 2 Department of Emergency, Qingdao Women and Children Hospital

More Information

Corresponding author: WANG Yejun, E-mail: qdwyj2008@126.com

Received Date: 19 September 2018

摘要

摘要: 目的:现阶段儿科ICU诊断急性呼吸窘迫综合征 (ARDS) 主要依赖于氧合指数, 也就是PaO₂/FiO₂, 而动脉血氧分压 (PaO₂) 必须通过血气分析获得, 但是血气分析是一个有创、不连续的监测手段。本文研究无创参数SpO₂/FiO₂和PaO₂/FiO₂以及OSI和OI之间的关系, 探索使用无创参数辨识ARDS患儿疾病严重程度的可能性。方法:本研究利用MIMIC-III数据库, 获取患者相关生理参数, 将患儿人群随机分为训练集和测试集, 在训练集上利用广义线性回归模型, 分别建立S/F与P/F、Lg (S/F) 与Lg (P/F)、OSI与OI之间的线性回归模型, 在测试集上研究3种模型对于重度ARDS、中度ARDS、轻度ARDS的辨识效果。结果:在训练集分别建立了S/F-P/F、Lg (S/F) -Lg (P/F)、OSI-OI3种模型的线性回归方程, 对于S/F-P/F、Lg (S/F) -Lg (P/F) 两种模型分别确定了P/F在100、200、300处对应的S/F阈值, 对于OSI-OI模型确定了OI在4、8、16处的对应的OSI阈值。在测试集上使用对应阈值对ARDS疾病严重程度进行辨识, 获得了3种模型的辨识敏感性、特异性、准确率、AUC值。结论:通过以上研究可知, 相较于S/F-P/F、Lg (S/F) -Lg (P/F) 模型, OSI-OI模型对于患儿ARDS疾病严重程度有较好的辨识能力, 在患儿血气分析结果缺失的情况下, 可以考虑使用无创参数OSI代替PaO₂/FiO₂, 作为ARDS患儿病情诊断的辅助手段。
- 急性呼吸窘迫综合征 /
- 血氧饱和度 /
- 氧合指数 /
- 动脉血氧分压 /
- 儿科
Abstract: Objective: At present, pediatric ICU diagnosis of acute respiratory distress syndrome (ARDS) mainly depends on the oxygenation index (PaO₂/FiO₂), and arterial oxygen partial pressure (PaO₂) must be obtained through blood gas analysis, but blood gas analysis is an invasive, discontinuous Monitoring means.This article studies the relationship between non-invasive parameters SpO₂/FiO₂-PaO₂/FiO₂ and OSI-OI, and explores the possibility of using non-invasive parameters to identify the severity of disease in children with ARDS.Method: In this study, MIMIC-III database was used to obtain patient-related physiological parameters.The children were randomly divided into training set and test set.Generalized linear regression model was used on the training set to establish S/F and P/F and Lg, respectively./F) Linear regression model between Lg (P/F), OSI and OI.The effect of the three models on the detection of severe ARDS, moderate ARDS, and mild ARDS was studied on the test set.Result: In the training set, the linear regression equations of S/F-P/F, Lg (S/F) -Lg (P/F), and OSI-OI were established respectively for S/FP/F and Lg (S/F).The Lg (P/F) models respectively determine the corresponding S/F thresholds at 100, 200, and 300 for the P/F, and the corresponding OSI thresholds at 4, 8, and 16 for the OSI-OI model.The corresponding thresholds were used to identify the severity of ARDS disease on the test set.The sensitivity, specificity, accuracy, and AUC values of the three models were obtained.Conclusion: The above study shows that the OSI-OI model has better ability to identify the severity of ARDS disease in children compared with the S/F-P/F and Lg (S/F) -Lg (P/F) models.In the absence of blood gas analysis results in children, noninvasive parameters OSI can be used instead of PaO₂/FiO₂ as an aid in the diagnosis of children with ARDS.
- acute respiratory distress syndrome /
- blood oxygen saturation /
- oxygenation index /
- arterial partial pressure of oxygen /
- children

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