Prediction of Renal Damage in Children with Henoch-Schönlein Purpura Based on Machine Learning

Background This article is objected to explore the value of machine learning algorithm in predicting the risk of renal damage in children with Henoch-Schönlein Purpura, and to construct a predictive model of Henoch-Schönlein Purpura Nephritis in children and analyze the related risk factors of Henoch-Schönlein Purpura Nephritis in children. Methods Case data of 288 hospitalized children with Henoch-Schönlein Purpura from November 2018 to October 2021 were collected. The data included 42 indicators such as demographic characteristics, clinical symptoms and laboratory tests, etc. Univariate feature selection was used for feature extraction, and Logistic regression, support vector machine, decision tree and random forest algorithm were used respectively for classification prediction. Last, the performance of four algorithms are compared using accuracy rate and recall rate. Results The accuracy rate, recall rate and AUC of the established random forest model were 0.83, 0.86 and 0.91 respectively, which were higher than 0.74, 0.80 and 0.89 of the Logistic regression model; higher than 0.70, 0.80 and 0.89 of support vector machine model; higher than 0.74, 0.80 and 0.81 of the decision tree model. The top 10 important features provided by random forest model are Persistent purpura≥4weeks, Cr, Clinic time, ALB, WBC, TC, TG, Relapse, TG, Recurrent purpura and EB-DNA. Conclusion The model based on random forest algorithm has better performance in the prediction of children with allergic purpura renal damage, indicated by better classification accuracy, better classification effect and better generalization performance.

Intestinal dysbiosis featuring abundance of Streptococcus associates with Henoch-Schönlein purpura nephritis (IgA vasculitis with nephritis) in adult

Background The pathogenesis of Henoch-Schönlein purpura nephritis (HSPN) is closely associated with mucosal infection. But whether intestinal microbiota dysbiosis plays a role in it is not clear. Methods A total of 52 participants including 26 HSPN patients and 26 healthy controls were included. By using 16S ribosomal RNA gene sequencing, the intestinal microbiota composition between HSPN and healthy controls was compared. The diagnostic potency was evaluated by Receiver operating characteristic (ROC) with area under curves (AUC). Meanwhile, correlation analysis was also performed. Results The lower community richness and diversity of fecal microbiota was displayed in HSPN patients and the structure of gut microbiota was remarkedly different. A genus-level comparison indicated a significant increase in the proportions of g-Bacteroides, g-Escherichia–Shigella and g-Streptococcus, and a marked reduction of g-Prevotella_9 in HSPN patients, suggesting that the overrepresentation of potential pathogens and reduction of profitable strains were the main feature of the dysbiosis. The differential taxonomic abundance might make sense for distinguishing HSPN from healthy controls, with AUC of 0.86. The relative abundance of the differential bacteria was also concerned with clinical indices. Among them, Streptococcus spp. was positively associated with the severity of HSPN (P < 0.050). It was found that HSPN patients with higher level of Streptococcus spp. were more likely to suffering from hematuria and hypoalbuminemia (P < 0.050). Conclusions The dysbiosis of gut microbiota was obvious in HSPN patients, and the intestinal mucosal streptococcal infection was distinctive, which was closely related to its severity.

Henoch-Schonlein purpura due to sodium valproate: A Case report

The etiology of Henoch-Schönlein purpura (HSP) has been frequently attributed to certain drugs. Anticonvulsive drugs are reported rarely in drug-induced HSP.We report a 5-year-old girl with a seizure treated with sodium valproate. we report a case of HSP due to the consumption of sodium valproate..

Analysis of Nursing Effect of Children with Henoch-Schonlein Purpura Based on the PDCA Nursing Model

By applying the PDCA model to the care of children with Henoch-Schonlein purpura, the nursing process can be divided into four stages: planning, execution, inspection, and treatment. According to the age characteristics and disease progression of pediatric patients, a complete nursing plan is formulated to efficiently implement the nursing content and improve the nursing effect. This paper studies the application of the PDCA nursing model in the nursing of children with Henoch-Schonlein purpura and statistically analyzes the disappearance of skin rash, joint pain relief, disappearance of urine protein, disappearance of gastrointestinal symptoms, etc. Finally, this paper combines the experiment to evaluate the intervention effect of this nursing model and provides reference for the follow-up care of children with Henoch-Schonlein purpura. From the results of experimental research, it can be known that PDCA nursing can improve the comfort of children with Henoch-Schonlein purpura, shorten the time for symptom disappearance, and speed up the recovery process.

Effect of gut microbiota from Henoch-Schönlein Purpura patients on acid-sensitive ion channel 3 expression and intestinal motility in germ-free rats

Background It has been proven that gut microbiota alterations are involved in the development of Henoch-Schönlein Purpura (HSP). However, the pathogenesis of HSP hasn’t been eluciated. This study was to investigate the impact of gut microbiota from HSP on ASIC3 expression and interactions between microbiota and ASIC3 expression in the development of HSP. Methods Feces collected from HSP and healthy children at the First Affiliated Hospital of Anhui Medical University were made into fecal microbial solutions. Germ-free rats were randomly assigned to either the control or HSP groups. The HSP group of rats were administered the fecal microbiota solution of HSP children, while the control group rats were administered the fecal microbiota solution of healthy children. Abdominal withdrawal reflex (AWR) and intestinal propulsion rate of the rats were used to determine visceral sensitivity. Composition of the gut microbiota of HSP children was determined using 16S rRNA gene sequencing. ASIC3 expression in the colon was ascertained through qRT-PCR as well as western blotting analysis. Results The results showed a reduction in the number of species and abundance in the intestinal microbiota of children with HSP. Visceral sensitivity and intestinal propulsion rate of HSP group rats increased significantly, compared with the control group. Colon ASIC3 mRNA and protein levels in the HSP group were found to be upregulated. The microbiota dysbiosis of HSP patients could stimulate ASIC3 expression in the colon of Germ-free rats, which in turn affected intestinal motility. Conclusions These results suggested that HSP children had intestinal microbiota disorder, which might affect gut motility by down-regulating colon ASIC3 expression in rats.