OBJECTIVE To analyze the changing trend of hospital-acquired infections(HAIs)in hospitals from 2017 to 2023,and identify the distribution of different departments,infection sites and pathogens,so as to provide a scientific basis for the prevention and control of HAI.METHODS During the study period,the HAI data were col-lected and classified by year,department and infection site.Joinpoint regression model was used to analyze the trend of HAI rate,calculate the average annual percentage change(AAPC),and evaluate the distribution of infec-tion sites and pathogenic bacteria.RESULTS The overall infection situation showed that the average HAI rate was 1.19％,with a trend of increasing first and then decreasing during the study period,and AAPC was 8.33％(95％CI:0.025-0.173).The infection rate was the highest in the emergency department with an AAPC of 13.51％(95％CI:0.074-0.250),while the infection rates in the department of traditional Chinese medicine and orthope-dics were relatively stable.Lower respiratory tract infections accounted for the major proportion,followed by uri-nary tract infections and bloodstream infections.The AAPC for lower respiratory tract infections was 18.64％.The pathogenic analysis showed that bacterial infections were mainly gram-negative bacteria,with Kleb-siella pneumoniae,Pseudomonas aeruginosa,and Acinetobacter baumannii being the most common pathogens causing HAI.CONCLUSIONS The results of the study reveal that significant differences in HAI rates among dif-ferent departments and infection sites,especially the increasing infection rate in the emergency department should be highly concerned.In view of the persistent high incidence of respiratory and urinary tract infections,it is recom-mended to strengthen the relevant prevention and control measures.To effectively reduce the incidence of HAIs,it is necessary to focus on the monitoring and management of drug-resistant pathogens in the future.

OBJECTIVE: To explore the clinical phenotypes and genetic characteristics of a child with Acid-labile subunit deficiency (ALS). METHODS: A male child diagnosed with ALS at Dongguan Maternal and Child Health Care Hospital in March 2021 was selected as the study subject. Clinical data of his family was collected. Peripheral blood samples were collected from the child and his parents. Following extraction of genomic DNA, whole-exome sequencing (WES) was carried out, and Sanger sequencing was used for family verification of candidate variants. Based on guidelines from the American College of Medical Genetics and Genomics (ACMG), the pathogenicity of the candidate variant was classified. This study was approved by the Medical Ethics Committee of the hospital (Ethics No.: 2020-6). RESULTS: The patient, a 5-year-and-7-month-old boy, presented with short stature and delayed bone age. Endocrine examinations showed decreased serum concentrations of insulin-like growth factor-1 (IGF-1) and IGF binding protein-3 (IGFBP3). WES revealed that he has harbored compound heterozygous variants of the IGFALS gene, namely c.741_742del, p.Y248Pfs83 and c.272del, p.P91Rfs31. Sanger sequencing verified that the variants were inherited from his father and mother, respectively. According to the ACMG guidelines, c.741_742del, p.Y248Pfs83 and c.272del, p.P91Rfs31 variants were classified as likely pathogenic (PVS1+PM2_supporting). Based on the pre-set literature search strategy, 11 research literature on ALS were retrieved, which involved a total of 33 families and 62 patients. Combined with the patient in this study, 31 IGFALS gene variants were identified among the 63 patients, which mainly consisted of missense variants (20 types), with variant sites concentrated in exon 2. The main clinical features were short stature in conjunct with delayed puberty, with a significant genotype-phenotype correlation. CONCLUSION The IGFALS gene variants NM_004970.2: c.741_742del, p.Y248Pfs83 and c.272del, p.P91Rfs31 may be the genetic etiology in this family. This study has expanded the variant spectrum of the IGFALS gene and provided valuable information for the diagnosis, genetic counseling and clinical treatment of the disease.
Humans ; Male ; Phenotype ; Child, Preschool ; Carrier Proteins/genetics* ; Glycoproteins/deficiency* ; Exome Sequencing ; Female ; Mutation ; Insulin-Like Growth Factor I/metabolism* ; Growth Disorders/genetics*

OBJECTIVE To establish the an optimal prediction model for carbapenem-resistant Acinetobacter bau-mannii(CRAB)infection in ICU patients based on machine learning(ML)so as to help clinicians to diagnose and make decisions.METHODS The clinical data were collected from the patients who were hospitalized in ICUs of a three-A hospital from Jan.1,2017 to Dec.31,2024 and were randomly divided into the training set and the test set in a 7∶3 ratio.The characteristic variables were selected by means of LASSO regression analysis in combina-tion with multivariate logistic regression analysis.Five types of M L classification models were integrated,the opti-mal model was analyzed and identified.The performance of the prediction model for CRAB infection in the ICU patients was evaluated with the use of sensitivity,specificity,accuracy,areas under receiver operating characteris-tic curves(AUCs),calibration curves,Hosmer-Lemeshow test and decision curve analysis(DCA).The outputs of the ML models were interpreted by Shapley additive explanations(SHAP)and permutation importance.RESULTS A total of 2 904 patients were enrolled in the study,695(23.93％)of whom had CRAB infection.The AUC of XGBoost model was highest in the training set and the test set,respectively(0.994 and 0.907).The result of Hosmer-Lemeshow test showed that the calibration curves of the XGBoost model indicated that the predicated risk was highly con-sistent with the observed risk(x2=7.323 and 4.609,P=0.513 and 0.764,respectively).The DCA curves showed that the XGBoost model performed best within the whole range of threshold,with the highest net profit.The length of ICU stay,use of tigecycline,central venous catheterization,use of carbapenems and use of ventilator were determined as the major predictive factors by means of SHAP.CONCLUSIONS The XGBoost model is established and interpreted by SHAP.It provides bases for screening of the ICU patients at high risk of CRAB infection.

OBJECTIVE To analyze the changing trend of hospital-acquired infections(HAIs)in hospitals from 2017 to 2023,and identify the distribution of different departments,infection sites and pathogens,so as to provide a scientific basis for the prevention and control of HAI.METHODS During the study period,the HAI data were col-lected and classified by year,department and infection site.Joinpoint regression model was used to analyze the trend of HAI rate,calculate the average annual percentage change(AAPC),and evaluate the distribution of infec-tion sites and pathogenic bacteria.RESULTS The overall infection situation showed that the average HAI rate was 1.19％,with a trend of increasing first and then decreasing during the study period,and AAPC was 8.33％(95％CI:0.025-0.173).The infection rate was the highest in the emergency department with an AAPC of 13.51％(95％CI:0.074-0.250),while the infection rates in the department of traditional Chinese medicine and orthope-dics were relatively stable.Lower respiratory tract infections accounted for the major proportion,followed by uri-nary tract infections and bloodstream infections.The AAPC for lower respiratory tract infections was 18.64％.The pathogenic analysis showed that bacterial infections were mainly gram-negative bacteria,with Kleb-siella pneumoniae,Pseudomonas aeruginosa,and Acinetobacter baumannii being the most common pathogens causing HAI.CONCLUSIONS The results of the study reveal that significant differences in HAI rates among dif-ferent departments and infection sites,especially the increasing infection rate in the emergency department should be highly concerned.In view of the persistent high incidence of respiratory and urinary tract infections,it is recom-mended to strengthen the relevant prevention and control measures.To effectively reduce the incidence of HAIs,it is necessary to focus on the monitoring and management of drug-resistant pathogens in the future.

OBJECTIVE To establish the an optimal prediction model for carbapenem-resistant Acinetobacter bau-mannii(CRAB)infection in ICU patients based on machine learning(ML)so as to help clinicians to diagnose and make decisions.METHODS The clinical data were collected from the patients who were hospitalized in ICUs of a three-A hospital from Jan.1,2017 to Dec.31,2024 and were randomly divided into the training set and the test set in a 7∶3 ratio.The characteristic variables were selected by means of LASSO regression analysis in combina-tion with multivariate logistic regression analysis.Five types of M L classification models were integrated,the opti-mal model was analyzed and identified.The performance of the prediction model for CRAB infection in the ICU patients was evaluated with the use of sensitivity,specificity,accuracy,areas under receiver operating characteris-tic curves(AUCs),calibration curves,Hosmer-Lemeshow test and decision curve analysis(DCA).The outputs of the ML models were interpreted by Shapley additive explanations(SHAP)and permutation importance.RESULTS A total of 2 904 patients were enrolled in the study,695(23.93％)of whom had CRAB infection.The AUC of XGBoost model was highest in the training set and the test set,respectively(0.994 and 0.907).The result of Hosmer-Lemeshow test showed that the calibration curves of the XGBoost model indicated that the predicated risk was highly con-sistent with the observed risk(x2=7.323 and 4.609,P=0.513 and 0.764,respectively).The DCA curves showed that the XGBoost model performed best within the whole range of threshold,with the highest net profit.The length of ICU stay,use of tigecycline,central venous catheterization,use of carbapenems and use of ventilator were determined as the major predictive factors by means of SHAP.CONCLUSIONS The XGBoost model is established and interpreted by SHAP.It provides bases for screening of the ICU patients at high risk of CRAB infection.

Bladder cancer is one of the common malignant tumors of the urinary system,and the results of conventional diagnosis and treatment methods are not satisfactory at this stage.In recent years,photodynamic technology has been applied in the diagnosis and treatment of bladder cancer due to its rapid development,and its effect has been widely recognized in clinical practice.Photodynamic diagnosis(PDD)has shown value in the diagnosis of bladder cancer,and compared with white light cystoscopy(WLC),blue light cystoscopy(BLC)has higher sensitivity and specificity,and is better suitable for the diagnosis of minor lesions and hidden lesions such as CIS,but it is expensive and time-consuming.Non-invasive targeted photodynamic diagnostic techniques using urine as a sample are beginning to show potential;PDD-guided TURBT has better diagnostic sensitivity and surgical precision.Photodynamic therapy(PDT)is an ideal treatment modality for bladder cancer.New photosensitizers have been developed,and two-photon PDT technology,intermittent and rhythmic PDT technology have been applied,which can help to reduce the number of PDT operations and reduce additional trauma while improving the efficacy.Some scholars have tried to use nanotechnology to combine PDT with chemotherapy drugs to further improve the efficacy.Monoclonal antibodies,antibody fragments,protein scaffolds,peptides and small molecule targeted molecular tracers have different characteristics,and new combination therapy methods are being researched and developed,bringing new opportunities for bladder cancer treatment.

Objective:To describe demographic,clinical and physiological characteristics,treatment between first-episode major depressive disorder(MDD)and relapse MDD,and to explore characteristics of relapse MDD.Methods:Totally 858 patients who met the diagnostic criteria for depression of the Diagnostic and Statistical Manual of Mental Disorders,Fifth Edition(DSM-5),were included by using the Mini International Neuropsychiatric Interview(MINI),Clinician-Rated Dimensions of Psychosis Symptom Severity,and Hamilton Depression Scale etc.Among them,529(58.6％)were first-episode depression and 329(36.0％)were relapsed.The differences of demographic characteristics,clinical and physiological characteristics,treatment were compared byx2test and Kruskal-Wallis rank sum test.Multivariate logistic regression was used to explore the characteristics of MDD recur-rence.Results:Compared to first-episode MDD,relapse MDD had more comorbidity(OR=2.11,95％CI:1.00-4.44),more days out of role(OR=1.26,95％CI:1.01-1.56),more history of using psychiatric drug more than one month(OR=1.41,95％CI:1.02-1.97)and electroconvulsive therapy(OR=3.23,95％CI:1.42-7.36),and higher waist-hip ratio(OR=33.88,95％CI:2.88-399.32).Conclusion:Relapse MDD has positive as-sociation with comorbidity of mental disorders,out of role,and higher waist-hip ratio.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.

During coronavirus disease 2019 epidemic, the treatment of severe trauma has been impacted. The Consensus on emergency surgery and infection prevention and control for severe trauma patients with 2019 novel corona virus pneumonia was published online on February 12, 2020, providing a strong guidance for the emergency treatment of severe trauma and the self-protection of medical staffs in the early stage of the epidemic. With the Joint Prevention and Control Mechanism of the State Council renaming "novel coronavirus pneumonia" to "novel coronavirus infection" and the infection being managed with measures against class B infectious diseases since January 8, 2023, the consensus published in 2020 is no longer applicable to the emergency treatment of severe trauma in the new stage of epidemic prevention and control. In this context, led by the Chinese Traumatology Association, Chinese Trauma Surgeon Association, Trauma Medicine Branch of Chinese International Exchange and Promotive Association for Medical and Health Care, and Editorial Board of Chinese Journal of Traumatology, the Chinese expert consensus on emergency surgery for severe trauma and infection prevention during coronavirus disease 2019 epidemic ( version 2023) is formulated to ensure the effectiveness and safety in the treatment of severe trauma in the new stage. Based on the policy of the Joint Prevention and Control Mechanism of the State Council and by using evidence-based medical evidence as well as Delphi expert consultation and voting, 16 recommendations are put forward from the four aspects of the related definitions, infection prevention, preoperative assessment and preparation, emergency operation and postoperative management, hoping to provide a reference for severe trauma care in the new stage of the epidemic prevention and control.

Background: The mechanism of peripheral axon transport in neuropathic pain is still unclear. Chemokine ligand 13 (CXCL13) and its receptor (C-X-C chemokine receptor type 5, CXCR5) as well as GABA transporter 1 (GAT-1) play an important role in the development of pain. The aim of this study was to explore the axonal transport of CXCL13/CXCR5 and GAT-1 with the aid of the analgesic effect of botulinum toxin type A (BTX-A) in rats. Methods: Chronic constriction injury (CCI) rat models were established. BTX-A was administered to rats through subcutaneous injection in the hind paw. The pain behaviors in CCI rats were measured by paw withdrawal threshold and paw withdrawal latencies. The levels of CXCL13/CXCR5 and GAT-1 were measured by western blots. Results: The subcutaneous injection of BTX-A relieved the mechanical allodynia and heat hyperalgesia induced by CCI surgery and reversed the overexpression of CXCL13/CXCR5 and GAT-1 in the spinal cord, dorsal root ganglia (DRG), sciatic nerve, and plantar skin in CCI rats. After 10 mmol/L colchicine blocked the axon transport of sciatic nerve, the inhibitory effect of BTX-A disappeared, and the levels of CXCL13/CXCR5 and GAT-1 in the spinal cord and DRG were reduced in CCI rats. Conclusions BTX-A regulated the levels of CXCL13/CXCR5 and GAT-1 in the spine and DRG through axonal transport. Chemokines (such as CXCL13) may be transported from the injury site to the spine or DRG through axonal transport. Axon molecular transport may be a target to enhance pain management in neuropathic pain.