Objective:To explore the risk factors for severe acute kidney injury (AKI) in children with sepsis in the pediatric intensive care unit (PICU) and construct a prediction model to assist early clinical identification.Methods:A retrospective analysis was performed on clinical data of 987 children with sepsis admitted to the PICU of Hunan Children′s Hospital from July 1, 2018 to January 31, 2021. Children who developed severe AKI during hospitalization were included in the AKI stage 2-3 group ( n=228), and the remaining were included in the No-AKI/AKI stage 1 group ( n=759). General information and biochemical indicators were compared between the two groups. Logistic regression analysis was used to identify risk factors for severe AKI in children with sepsis, and a prediction model and nomogram were established. Results:The mortality rate in the AKI stage 2-3 group was 2.49 times that of the No-AKI/AKI stage 1 group [31.1%(71/228) vs 12.5%(95/759), P<0.05]. Compared with the No-AKI/AKI stage 1 group, the AKI stage 2-3 group had lower levels of platelet count (PLT), total protein (TP), albumin (ALB), antithrombin Ⅲ (AT3), and fibrinogen (FIB), but higher levels of lactate dehydrogenase (LDH), serum creatinine (SCr), blood urea nitrogen (BUN), magnesium ion (Mg 2+ ), activated partial thromboplastin time (APTT), fibrinogen degradation products (FDP), and D-dimer (D-D) (all P<0.05), with no significant difference in total bile acid (TBAC) ( P>0.05). Multivariate logistic regression analysis showed that decreased AT3 ( OR=0.989, 95% CI: 0.980-0.997, P=0.007), increased LDH ( OR=1.001, 95% CI: 1.000-1.001, P<0.001), increased SCr ( OR=1.051, 95% CI: 1.037-1.066, P<0.001), and increased BUN ( OR=1.099, 95% CI: 1.028-1.174, P=0.005) were risk factors for severe AKI in children with sepsis. The prediction model was Logist Pr=-3.184-0.012 X1+ 0.001 X2+ 0.050 X3+ 0.094 X4 ( X1=AT3, X2=LDH, X3=SCr, X4=BUN), with the optimal cut-off value of 0.374 (Youden index=0.560). A nomogram was constructed by binary assignment of predictive variables, with an area under the curve of 0.826 (95% CI: 0.790-0.861, P<0.001). Conclusions:The mortality rate of septic children with severe AKI in PICU is significantly increased. Decreased AT3, and increased LDH, SCr, and BUN are risk factors for severe AKI in children with sepsis. Clinicians should be alert to severe AKI when the predicted probability of the early warning model exceeds 0.374.

[Objective] To validate and optimize the platelet transfusion refractoriness (PTR) prediction model for patients with hematological disorders established by our center. [Methods] The data of patients with hematological diseases who received platelet transfusions from December 2021 to December 2022 were used as the training set, and data from January 2023 to December 2023 as the validation set. The validation set data was used to validate the predictive model constructed on the training set. Relevant risk factors for PTR were collected through literature review and preliminary studies。 The patients were divided into effective and ineffective groups according to the corrected count increment (CCI) of platelet counts. Predictive factors were screened using univariate and multivariate logistic regression. The calibration of the model were assessed via calibration curves, while discrimination, accuracy, sensitivity, and specificity were evaluated using receiver operating characteristic (ROC) curves Clinical utility was further analyzed with decision curve analysis (DCA). [Results] The Hosmer-Lemeshow (H-L) goodness-of-fit test for the validation set yielded S: P=0.000, indicating that the original model needs optimization. Baseline comparisons and logistic regression identified the number of red blood cell units (RBCU) and platelet units (PLT-U) transfused as key predictors for the optimized model. The H-L goodness-of-fit test S: P values for the training and validation sets were 0.930 and 0.056, respectively; the ROC areas were 0.793 5 and 0.809 4, specificities 90.95% and 84.21%, sensitivities 59.26% and 70.04%, and accuracies 78.14% and 74.10%, respectively. DCA demonstrated clinical net benefit within a prediction probability threshold range of 0.2-0.8. [Conclusion] Transfusion volumes of RBC-U and PLT-U were inversely associated with PTR in hematological patients. The resulting PTR prediction model exhibits moderate predictive efficacy and clinical benefit.

On August 24 2024, Xiaoshan District Center for Disease Control and Prevention, Hangzhou City, received a report of two cases of varicella infection among staff in the intensive care unit (ICU) of a hospital in its jurisdiction. The center immediately organized personnel to conduct an epidemiological investigation of the cases and their close contacts. The index case was a patient admitted to the ICU who had large areas of red rash and pustules on the chest, back, and right axilla. This case was diagnosed with herpes zoster by a dermatology consultation within the hospital. The other nine secondary cases were all nursing staff in the ICU, who were clinically diagnosed with varicella between August 21 and September 1, with an attack rate of 14.06%. All secondary varicella cases had a history of contact with the herpes zoster case and no history of varicella infection. Their varicella vaccination history was unknown. Based on the results of the on-site epidemiological and sanitary investigations, it was determined that this was an outbreak of varicella in the hospital caused by a herpes zoster case. After the last case was diagnosed, no new cases were reported within the longest incubation period (21 days), and the outbreak was declared over on September 21. Close contact with the herpes zoster case was likely the main cause of the outbreak. This highlights the need for early identification and isolation of suspected herpes zoster cases in hospitals in the future, as well as enhanced protective measures to prevent nosocomial infections.

Objective:To explore the risk factors for severe acute kidney injury (AKI) in children with sepsis in the pediatric intensive care unit (PICU) and construct a prediction model to assist early clinical identification.Methods:A retrospective analysis was performed on clinical data of 987 children with sepsis admitted to the PICU of Hunan Children′s Hospital from July 1, 2018 to January 31, 2021. Children who developed severe AKI during hospitalization were included in the AKI stage 2-3 group ( n=228), and the remaining were included in the No-AKI/AKI stage 1 group ( n=759). General information and biochemical indicators were compared between the two groups. Logistic regression analysis was used to identify risk factors for severe AKI in children with sepsis, and a prediction model and nomogram were established. Results:The mortality rate in the AKI stage 2-3 group was 2.49 times that of the No-AKI/AKI stage 1 group [31.1%(71/228) vs 12.5%(95/759), P<0.05]. Compared with the No-AKI/AKI stage 1 group, the AKI stage 2-3 group had lower levels of platelet count (PLT), total protein (TP), albumin (ALB), antithrombin Ⅲ (AT3), and fibrinogen (FIB), but higher levels of lactate dehydrogenase (LDH), serum creatinine (SCr), blood urea nitrogen (BUN), magnesium ion (Mg 2+ ), activated partial thromboplastin time (APTT), fibrinogen degradation products (FDP), and D-dimer (D-D) (all P<0.05), with no significant difference in total bile acid (TBAC) ( P>0.05). Multivariate logistic regression analysis showed that decreased AT3 ( OR=0.989, 95% CI: 0.980-0.997, P=0.007), increased LDH ( OR=1.001, 95% CI: 1.000-1.001, P<0.001), increased SCr ( OR=1.051, 95% CI: 1.037-1.066, P<0.001), and increased BUN ( OR=1.099, 95% CI: 1.028-1.174, P=0.005) were risk factors for severe AKI in children with sepsis. The prediction model was Logist Pr=-3.184-0.012 X1+ 0.001 X2+ 0.050 X3+ 0.094 X4 ( X1=AT3, X2=LDH, X3=SCr, X4=BUN), with the optimal cut-off value of 0.374 (Youden index=0.560). A nomogram was constructed by binary assignment of predictive variables, with an area under the curve of 0.826 (95% CI: 0.790-0.861, P<0.001). Conclusions:The mortality rate of septic children with severe AKI in PICU is significantly increased. Decreased AT3, and increased LDH, SCr, and BUN are risk factors for severe AKI in children with sepsis. Clinicians should be alert to severe AKI when the predicted probability of the early warning model exceeds 0.374.

Objective To investigate the protective effect of recombinant Schistosoma japonicum cystatin(rSj-Cys)against acute liver injury induced by lipopolysaccharide(LPS)and D-GalN in mice.Methods Adult male C57BL/6J mice with or without LPS/D-GaIN-induced acute liver injury were given intraperitoneal injections of rSj-Cys or PBS 30 min after modeling(n=18),and serum and liver tissues samples were collected from 8 mice in each group 6 h after modeling.The survival of the remaining 10 mice in each group within 24 h was observed.Serum levels of ALT,AST,TNF-α and IL-6 of the mice were measured,and liver pathologies was observed with HE staining.The hepatic expressions of macrophage marker CD68,Bax,Bcl-2 and endoplasmic reticulum stress(ERS)-related proteins were detected using immunohistochemistry or immunoblotting,and TUNEL staining was used to detect hepatocyte apoptosis.Results The survival rates of PBS-and rSj-Cys-treated mouse models of acute liver injury were 30%and 80%at 12 h and were 10%and 60%at 24 h after modeling,respectively;no death occurred in the two control groups within 24 h.The mouse models showed significantly increased serum levels of AST,ALT,IL-6 and TNF-α and serious liver pathologies with increased hepatic expressions of CD68 and Bax,lowered expression of Bcl-2,increased hepatocyte apoptosis,and up-regulated expressions of ERS-related signaling pathway proteins GRP78,CHOP and NF-κB p-p65.Treatment of the mouse models significantly lowered the levels of AST,ALT,IL-6 and TNF-α,alleviated liver pathologies,reduced hepatic expressions of CD68,Bax,GRP78,CHOP and NF-κB p-p65,and enhanced the expression of Bcl-2.In the normal control mice,rSj-Cys injection did not produce any significant changes in these parameters compared with PBS.Conclusion rSj-Cys alleviates LPS/D-GalN-induced acute liver injury in mice by suppressing ERS,attenuating inflammation and inhibiting hepatocyte apoptosis.

Phage therapy is one of the most important tools for the treatment of infections with multi-drug resistant bacteria. Such phages are usually isolated from hospital effluents, however, no systematic study on the distribution of phages in hospital effluents has been conducted so far. The aim of this study was to isolate the corresponding phages of common pathogenic bacteria isolated in the clinic as hosts, so as to assess the ecological distribution of phages in hospital wastewater and to provide a reference for the isolation and application of phages of drug-resistant bacteria in the clinic. A cross-sectional study design was used in this study. The 125 pathogenic bacteria (belonging to 16 different strains) isolated from the clinical microbiology laboratory of Qilu Hospital of Shandong University from May to June 2023 were selected as the target strains, and the phages corresponding to these strains were isolated and purified from the hospital wastewater by using the double-layer plate sandwich method. At the same time, the distribution of pathogenic bacteria in the same batch of wastewater was analyzed with the help of mNGS sequencing technology, so as to preliminarily investigate the abundance correspondence between pathogenic bacteria and phages in wastewater. The results showed that a total of 56 phage strains were isolated from 125 clinical pathogens as hosts, corresponding to six pathogens, including Acinetobacter baumannii, Klebsiella pneumoniae, Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa, and Stenotrophomonas maltophilia. All six pathogenic bacteria contained strains with different degrees of drug resistance, with a higher percentage of multi-drug resistant strains in A. baumannii, Escherichia coli and P. aeruginosa. The phage acquisition rates of these six pathogens were, in descending order, Escherichia coli (80%), Stenotrophomonas maltophilia (75%), Pseudomonas aeruginosa (70%), Klebsiella pneumoniae (66.67%), Acinetobacter baumannii (36.36%) and Staphylococcus aureus (12.5%). Preliminary mNGS sequencing results showed that the pathogenic bacteria with higher abundance in the batch of effluent were Enterococcus faecalis, Klebsiella pneumoniae, Escherichia coli, Enterococcus faecalis, Acinetobacter baumannii, Klebsiella aerogenes, Klebsiella michiganensis and Pseudomonas aeruginosa. In conclusion, phages of most common clinical Gram-negative pathogens were isolated from hospital wastewater with high isolation rates; however, phages of Gram-positive pathogens were isolated at lower rates, and only phages corresponding to Staphylococcus aureus were isolated in this study. The corresponding mNGS sequencing results showed that the distribution of Gram-negative pathogens in sewage may had a positive correlation with the ecological distribution of phages.

Objective:To summarize and analyze the results of gene detection and clinical characteristics of children with unknown etiology in pediatric intensive care unit (PICU).Methods:The clinical data from children with unknown clinical diagnosis and completed the whole exon sequencing who were admitted to PICU at Hunan Children's Hospital from September 20,2014 to December 30,2018 were collected .According to the results of gene detection,patients were divided into positive gene test group and regative gene test group,and the clinical characteristics between two groups were compared.Results:A total of 58 cases were included,and 119 samples were sent for the whole exone sequencing (including samples from both children and their families).Pathogenic mutations were identified in 34 cases (58.6%),with 39 pathogenic genes detected.Three pathogenic genes were detected in one patient (1.7%),two pathogenic genes were detected in each of the three patients (5.2%),and one pathogenic gene was detected in each of the 30 patients (51.7%).Among the 39 pathogenic genes,18 genes(46.2%) were autosomal dominant,15 genes(38.5%) were autosomal recessive,four genes(10.3%) were X-linked recessive,and two genes(5.1%) were copy number variants .The proportion of congenital heart disease in positive gene test group was higher than that in negative gene test group（32.4% vs.8.3%，χ 2=4.668， P=0.031）,while there was no statistical difference in other clinical features（ P>0.05）.There was no significant difference in clinical characteristics between the positive gene test group and the negative gene test group among the death children ( P>0.05）.Among 58 cases,39 cases (67.2%) resulted in death,and the positive rate of genetic disease diagnosis of the dead children was 66.7%(26/39).The mortality rate of children with positive genetic test was 76.5%(26/34),22 cases (84.7%) died directly from genetic diseases,and four cases died indirectly. Conclusion:Genetic diseases are one of the important causes of death among children in PICU.The clinical characteristics of children with genetic diseases in PICU are complex and diverse,lacking specificity.The whole exon sequencing presents a high diagnosis rate in severe and fatal PICU patients.It is recommended that children with unknown etiology in PICU should undergo genetic testing,especially those with congenital heart disease,in order to help make a clear diagnosis and guide treatment.

Trajectories refer to the motion paths followed by objects in space. Disease trajectories, which depict the evolution of disease processes over time, are significantly important for assessing diseases, formulating treatment strategies, and predicting prognosis. Critical illness is one of the leading causes of death. With advances in critical care medicine, there is increasing focus on the occurrence and development of critical illnesses. Understanding the development trajectory of critical illness is helpful to promote the early identification, intervention, and treatment of high-risk patients, avoid prolongation of the course of disease, reduce the risk of multiple organ failure, and provide important reference for the development of targeted prevention and intervention strategies, thereby reducing the incidence and mortality of critical illness. In recent years, various trajectory modeling methods have been applied to the study of critical illness. These include, but are not limited to, latent growth curve modeling (LGCM), growth mixture modeling (GMM), group-based trajectory modeling (GBTM), latent transition analysis (LTA), and latent class analysis (LCA). The aim of this article is to review the definition of disease trajectories, the methods used in trajectory modeling, and their applications and future prospects in critical illness research.

Medical simulation training,with the characteristics of safety,repeatability,authenticity,and controllability,can provide an immersive teaching experience to students by shortening their learning curve of clinical practice,improving clinical post competence and making medical practice education accessible.The technical types of medical simulation training include in basic anatomical models,single task training models,standardized patients/personnel,computer interactive training models,virtual training systems,physiological driven simulation systems,etc.It is an important component of modern medical education that can be mainly used for imparting knowledge,training skills,clinical simulation training,non operational skills,etc.

Objective:To explore the clinical characteristics of children with septic shock and analyze the drug resistance of blood culture positive bacteria.Methods:The clinical data,positive blood culture strains and drug sensitivity results of 127 children with septic shock admitted to the Department of Intensive Care Medicine of Hunan Children's Hospital from September 2015 to August 2021 were retrospectively analyzed.Results:A total of 134 strains of bacteria or fungi were isolated from the blood culture samples of 127 children with septic shock,and gram-negative strains were the main ones,accounting for 67.16% (90/134).Haemophilus influenzae and Escherichia coli were the main gram-negative bacteria,accounting for 38.81% (52/134) and 20.15% (27/134)，respectively,while Streptococcus pneumoniae was the main gram-positive bacteria,accounting for 8.21% (11/134),and Candida albicans was the main fungus,accounting for 10.45% (14/134).The number of white blood cells,the levels of serum C-reactive protein,procalcitonin,venous blood sugar and arterial blood lactic acid in patients were all significantly higher than normal values,and the white blood cells count and neutrophil percentage in gram-positive bacterial infections were significantly higher than those with gram-negative bacterial infections and fungal infections( P<0.05).Procalcitonin increased most obviously when infected by gram-negative bacteria,and the difference was statistically significant ( P<0.05).Gram-positive strains were sensitive to vancomycin,teicoplanin,and linezolid,but only 50% of Streptococcus pneumoniae were sensitive to penicillin.Gram-negative strains had relatively high drug resistance,among which Klebsiella pneumoniae were only highly resistant to imipenem,cilastatin and levofloxacin,reaching 50%.Haemophilus influenzae was resistant to cephalosporins and β-amides enzyme antibiotic,and the drug sensitivity rate of lactamase antibiotics was high,with a resistance rate of 50% only to ampicillin,cefuroxime,amikacin,and compound sulfamethoxazole.There were not many fungal strains,and most antifungal drugs were effective against blood culture-positive fungi. Conclusion:The main pathogens of infection in children with septic shock are gram-negative bacteria,and have high resistance to general antibiotics.We should pay attention to their drug resistance when using antibiotics empirically.