Application of intelligent nursing based on cloud computing of internet of things in children with pneumonia and sepsis treated with human gamma globulin

Author:

Qin Aihua1ORCID,Liu Yuling2,Shao Changming1,Dong Hongyan1

Affiliation:

1. Shangqiu Medical College, Shangqiu, China

2. The First People’s Hospital of Shangqiu, Shangqiu, China

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.

Funder

Henan Province Higher Education Teaching Reform Research and Practice Project

Henan Province Higher Vocational School Young Key Teacher Training Program Project

Publisher

SAGE Publications

Subject

Immunology,Immunology and Allergy,General Medicine

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