{"title":"基于物联网云计算的智能护理在丙种球蛋白治疗肺炎脓毒症患儿中的应用","authors":"Aihua Qin, Yuling Liu, Changming Shao, Hongyan Dong","doi":"10.1177/1721727x231194144","DOIUrl":null,"url":null,"abstract":"Purpose: To explore the application of intelligent nursing (IN) based on the Internet of Things (IoT) in children with pneumonia and sepsis treated with human gamma globulin (HGG). Methods: A total of 200 children with pneumonia combined with sepsis who attended the First People’s Hospital of Shangqiu from January 1, 2020 to February 13, 2022 were consecutively collected. Children were randomly divided into IN group and routine nursing (RN) group, with 100 children in each group. All children received standard anti-infection treatment along with intravenous HGG. In IN group, IN measures based on the IoT cloud computing platform monitored the treatment process of children with HGG throughout the whole process, while children in the RN group only received RN measures. Information on both groups was collected from the medical records, such as gender, age, duration of hospitalization, fever, antibiotic use, serological indicators, pulmonary function indicators, immune function indicators and adverse effects of HGG. Multi-factorial logistic regression was performed to access the correlation between IN and the duration of hospitalization and a range of other factors studied above. Results: After adjusting for numerous confounding factors, multifactorial logistic regression revealed that the application of IN was associated with a shorter duration of hospitalization ( p = .030) and lower white blood cell (WBC) and creatinine (Cr) levels in post-treatment children ( p = .003, p = .010). It was also associated with higher levels of forced expiratory volume in one second (FEV1), forced vital capacity (FVC) and peak expiratory flow (PEV) after treatment ( p = .014, p = .001, p = .002) and higher levels of immune CD4+/CD8+ ratio after treatment ( p = .001) and reduced symptoms of vomiting among the adverse effects ( p = .047). Conclusion: The IoT cloud-based IN model significantly improved the efficacy of HGG in the treatment of pneumonia sepsis in children and reduce occurrence of some adverse reactions.","PeriodicalId":55162,"journal":{"name":"European Journal of Inflammation","volume":" ","pages":""},"PeriodicalIF":0.6000,"publicationDate":"2023-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Application of intelligent nursing based on cloud computing of internet of things in children with pneumonia and sepsis treated with human gamma globulin\",\"authors\":\"Aihua Qin, Yuling Liu, Changming Shao, Hongyan Dong\",\"doi\":\"10.1177/1721727x231194144\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Purpose: To explore the application of intelligent nursing (IN) based on the Internet of Things (IoT) in children with pneumonia and sepsis treated with human gamma globulin (HGG). Methods: A total of 200 children with pneumonia combined with sepsis who attended the First People’s Hospital of Shangqiu from January 1, 2020 to February 13, 2022 were consecutively collected. Children were randomly divided into IN group and routine nursing (RN) group, with 100 children in each group. All children received standard anti-infection treatment along with intravenous HGG. In IN group, IN measures based on the IoT cloud computing platform monitored the treatment process of children with HGG throughout the whole process, while children in the RN group only received RN measures. Information on both groups was collected from the medical records, such as gender, age, duration of hospitalization, fever, antibiotic use, serological indicators, pulmonary function indicators, immune function indicators and adverse effects of HGG. Multi-factorial logistic regression was performed to access the correlation between IN and the duration of hospitalization and a range of other factors studied above. Results: After adjusting for numerous confounding factors, multifactorial logistic regression revealed that the application of IN was associated with a shorter duration of hospitalization ( p = .030) and lower white blood cell (WBC) and creatinine (Cr) levels in post-treatment children ( p = .003, p = .010). It was also associated with higher levels of forced expiratory volume in one second (FEV1), forced vital capacity (FVC) and peak expiratory flow (PEV) after treatment ( p = .014, p = .001, p = .002) and higher levels of immune CD4+/CD8+ ratio after treatment ( p = .001) and reduced symptoms of vomiting among the adverse effects ( p = .047). Conclusion: The IoT cloud-based IN model significantly improved the efficacy of HGG in the treatment of pneumonia sepsis in children and reduce occurrence of some adverse reactions.\",\"PeriodicalId\":55162,\"journal\":{\"name\":\"European Journal of Inflammation\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2023-08-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"European Journal of Inflammation\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1177/1721727x231194144\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"IMMUNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Journal of Inflammation","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/1721727x231194144","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"IMMUNOLOGY","Score":null,"Total":0}
引用次数: 0
摘要
目的:探讨基于物联网(IoT)的智能护理(IN)在接受人γ球蛋白(HGG)治疗的肺炎脓毒症患儿中的应用。方法:连续收集2020年1月1日至2022年2月13日在商丘市第一人民医院就诊的肺炎合并脓毒症患儿200例。将患儿随机分为IN组和常规护理组,每组100例。所有儿童均接受标准抗感染治疗并静脉注射HGG。In组基于IoT云计算平台的In措施全程监控HGG患儿的治疗过程,而RN组患儿仅接受RN措施。从病历中收集两组患者的信息,如性别、年龄、住院时间、发热、抗生素使用、血清学指标、肺功能指标、免疫功能指标和HGG的不良反应。我们采用多因素logistic回归来获得IN与住院时间以及上述研究的一系列其他因素之间的相关性。结果:在对众多混杂因素进行校正后,多因素logistic回归显示,使用IN与治疗后儿童住院时间缩短(p = 0.030)和白细胞(WBC)和肌酐(Cr)水平降低相关(p = 0.003, p = 0.010)。治疗后的一秒钟用力呼气量(FEV1)、用力肺活量(FVC)和呼气峰流量(PEV)水平升高(p = 0.014, p = 0.001, p = 0.002),治疗后免疫CD4+/CD8+比值升高(p = 0.001),不良反应中呕吐症状减轻(p = 0.047)。结论:基于IoT云的IN模型可显著提高HGG治疗儿童肺炎脓毒症的疗效,减少部分不良反应的发生。
Application of intelligent nursing based on cloud computing of internet of things in children with pneumonia and sepsis treated with human gamma globulin
Purpose: To explore the application of intelligent nursing (IN) based on the Internet of Things (IoT) in children with pneumonia and sepsis treated with human gamma globulin (HGG). Methods: A total of 200 children with pneumonia combined with sepsis who attended the First People’s Hospital of Shangqiu from January 1, 2020 to February 13, 2022 were consecutively collected. Children were randomly divided into IN group and routine nursing (RN) group, with 100 children in each group. All children received standard anti-infection treatment along with intravenous HGG. In IN group, IN measures based on the IoT cloud computing platform monitored the treatment process of children with HGG throughout the whole process, while children in the RN group only received RN measures. Information on both groups was collected from the medical records, such as gender, age, duration of hospitalization, fever, antibiotic use, serological indicators, pulmonary function indicators, immune function indicators and adverse effects of HGG. Multi-factorial logistic regression was performed to access the correlation between IN and the duration of hospitalization and a range of other factors studied above. Results: After adjusting for numerous confounding factors, multifactorial logistic regression revealed that the application of IN was associated with a shorter duration of hospitalization ( p = .030) and lower white blood cell (WBC) and creatinine (Cr) levels in post-treatment children ( p = .003, p = .010). It was also associated with higher levels of forced expiratory volume in one second (FEV1), forced vital capacity (FVC) and peak expiratory flow (PEV) after treatment ( p = .014, p = .001, p = .002) and higher levels of immune CD4+/CD8+ ratio after treatment ( p = .001) and reduced symptoms of vomiting among the adverse effects ( p = .047). Conclusion: The IoT cloud-based IN model significantly improved the efficacy of HGG in the treatment of pneumonia sepsis in children and reduce occurrence of some adverse reactions.
期刊介绍:
European Journal of Inflammation is a multidisciplinary, peer-reviewed, open access journal covering a wide range of topics in inflammation, including immunology, pathology, pharmacology and related general experimental and clinical research.