Clinical Value of Continuous Blood Purification in the Treatment of Severe Sepsis

2021 ◽  
2021 ◽  
Vol 5 (3) ◽  
Author(s):  
Weikai Wang ◽  
Yun Du ◽  
Aiqin Cheng ◽  
Shunli Liu ◽  
Lin Wei ◽  
...  

Pediatric sepsis is the most common disease in pediatric critical illness, because the main reason for the disease is that children's immune level is not high or the immune system is not perfect, when children's lung, abdominal cavity and blood system are infected, it will cause systemic inflammation and immune dysfunction. Early clinical symptoms are mainly irregular and intermittent fever. When the disease develops to severe sepsis, the children will suffer from acute heart failure, oliguria, respiratory alkalosis and even multiple organ failure. The incidence of death is high. It is reported that the incidence rate of sepsis in children can reach 0.3%, and the mortality rate is 50%. High incidence rate, high mortality rate and high treatment cost are the biggest problems in the pediatric field. In the past, the clinical hope of clearing away heat and toxin, promoting blood circulation and removing stasis, strengthening inflammation and other methods in traditional Chinese medicine, but the treatment effect is not ideal. With the improvement of modern medical understanding of sepsis, continuous blood purification therapy is introduced into the treatment of children with severe sepsis. In order to further explore the effect of continuous blood purification in the treatment of children with severe sepsis, the author summarizes the clinical practice experience and relevant literature, hoping to provide reference for relevant medical staff.


2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Liping Liu ◽  
Yanyan Liu ◽  
Aimin Xing ◽  
Siyu Chen ◽  
Mingli Gu

This study was to explore the CT image features based on intelligent algorithm to evaluate continuous blood purification in the treatment of severe sepsis caused by pulmonary infection and nursing. 50 patients in the hospital were selected as the research objects. Convolutional neural network algorithm was used to segment CT images of severe sepsis caused by pulmonary infection. They were randomly divided into 25 cases of experimental group and 25 cases of control group. The experimental group was given continuous blood purification treatment, combined with comprehensive nursing. The control group was given routine treatment and basic nursing. Fasting plasma glucose (FPG) and fasting insulin (FIN), interleukin-6 (IL-6), tumor necrosis factor (TNF-α), high-sensitivity c-reactive protein (hs-CRP) levels, CD3+, CD4+, CD4+/CD8+ levels, ICU monitoring time, malnutrition inflammation score (MIS), and incidence of adverse events were compared between the two groups before and after treatment. There was no difference in FPG and FIN between the two groups before treatment. After treatment, the FPG and FIN of the experimental group were lower than those of the control group, and there was statistical significance ( P < 0.05 ). There was no difference in IL-6, TNF-α, and hs-CRP between the two groups before treatment. After treatment, IL-6, TNF-α, and hs-CRP in the experimental group were lower than those in the control group. There was no difference in the percentage of CD3+, CD4+, and CD4+/CD8+ between the two groups before treatment. After treatment, the CD3+, CD4+, and CD4+/CD8+ in the experimental group were higher than those in the control group. The ICU monitoring time, MIS, and incidence of adverse events in the experimental group were lower than those in the control group ( P > 0.05 ). Convolutional neural network algorithm can accurately identify and segment CT images of patients with severe sepsis, which has high clinical application value. Continuous blood purification therapy can effectively control blood glucose level, improve immune function, and reduce the content of inflammatory factors in patients with severe sepsis caused by pulmonary infection. Effective nursing measures can improve the therapeutic effect.


Medicine ◽  
2019 ◽  
Vol 98 (12) ◽  
pp. e14873 ◽  
Author(s):  
Yong Hu ◽  
Wenjun Xiong ◽  
Chunyan Li ◽  
Yunfeng Cui

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