ObjectiveTo explore the clinical characteristics and risk factors for 30-day mortality in hospitalized patients with bloodstream infections (BSI) caused by carbapenem-resistant Klebsiella pneumoniae (CRKP). MethodsData were obtained retrospectively from the electronic medical records of inpatients at a tertiary A-grade hospital in Shanghai from January 2016 to December 2023. The collected variables included age, gender, department, surgical treatment, empirical antibiotic therapy, Pitt Bacteremia score (PBS), Charlson comorbidity index (CCI), INCREMENT-CPE score (ICS), length of hospital stay, the time from CRKP-BSI to discharge and, etc. The follow-up period ended upon discharge, with the follow-up outcomes defined as in-hospital mortality or discharge. The endpoint was defined as death within 30 days (including day 30) caused by CRKP-BSI or infection-related complications. Patients who survived within 30 days after CRKP-BSI were classified into the survival group, while those who died within 30 days were classified into the death group. Independent risk factors for 30-day mortality in patients with CRKP-BSI were analyzed using univariate and multivariate Cox regression analysis. ResultsA total of 71 hospitalized patients with CRKP-BSI, comprising 51 males and 20 females, with an average age of (65.12±18.25) years, were included during the study period. The M (P₂₅, P₇₅) of hospital stay were 37.00 (24.00, 56.00) days, and M (P₂₅, P₇₅) of the duration from CRKP-BSI to discharge or death were 18.00 (7.00, 35.00) days. There were 20 deaths (28.17%) in the death group and 51 survivors (71.83%) in the survival group. The results of multivariate Cox regression analysis showed that the ICS as an independent risk factor for 30-day mortality in CRKP-BSI patients (HR=1.379, 95%CI: 1.137‒1.671, P=0.001). Each 1-point increase in the ICS was associated with a 37.9% increase in the risk of mortality. ConclusionThe ICS is found to be a risk factor for 30-day mortality in patients with CRKP-BSI, which may facilitate the prediction for the risk of 30-day mortality and thereby support clinical decision-making for patients with CRKP-BSI.

Female ; Humans ; Adenocarcinoma in Situ ; Uterine Cervical Neoplasms/pathology* ; Papillomavirus Infections ; Cervix Uteri/pathology* ; Adenocarcinoma/pathology* ; Papillomaviridae ; DNA, Viral

Objective:To report the results of national surveillance on the distribution and antimicrobial resistance profile of clinical Gram-negative bacteria isolates from bloodstream infections in China in 2022.Methods:The clinical isolates of Gram-negative bacteria from blood cultures in member hospitals of national bloodstream infection Bacterial Resistant Investigation Collaborative System（BRICS）were collected during January 2022 to December 2022. Antibiotic susceptibility tests were conducted by agar dilution or broth dilution methods recommended by Clinical and Laboratory Standards Institute（CLSI）. WHONET 5.6 and SPSS 25.0 software were used to analyze the data.Results:During the study period，9 035 strains of Gram-negative bacteria were collected from 51 hospitals，of which 7 895（87.4%）were Enterobacteriaceae and 1 140（12.6%）were non-fermenting bacteria. The top 5 bacterial species were Escherichia coli（ n=4 510，49.9%）， Klebsiella pneumoniae（ n=2 340，25.9%）， Pseudomonas aeruginosa（ n=534，5.9%）， Acinetobacter baumannii complex（ n=405，4.5%）and Enterobacter cloacae（ n=327，3.6%）. The ESBLs-producing rates in Escherichia coli， Klebsiella pneumoniae and Proteus spp. were 47.1%（2 095/4 452），21.0%（427/2 033）and 41.1%（58/141），respectively. The prevalence of carbapenem-resistant Escherichia coli（CREC）and carbapenem-resistant Klebsiella pneumoniae（CRKP）were 1.3%（58/4 510）and 13.1%（307/2 340）；62.1%（36/58）and 9.8%（30/307）of CREC and CRKP were resistant to ceftazidime/avibactam combination，respectively. The prevalence of carbapenem-resistant Acinetobacter baumannii（CRAB）complex was 59.5%（241/405），while less than 5% of Acinetobacter baumannii complex was resistant to tigecycline and polymyxin B. The prevalence of carbapenem-resistant Pseudomonas aeruginosa（CRPA）was 18.4%（98/534）. There were differences in the composition ratio of Gram-negative bacteria in bloodstream infections and the prevalence of main Gram-negative bacteria resistance among different regions，with statistically significant differences in the prevalence of CRKP and CRPA（ χ2=20.489 and 20.252， P<0.001）. The prevalence of CREC，CRKP，CRPA，CRAB，ESBLs-producing Escherichia coli and Klebsiella pneumoniae were higher in provinicial hospitals than those in municipal hospitals（ χ2=11.953，81.183，10.404，5.915，12.415 and 6.459， P<0.01 or <0.05），while the prevalence of CRPA was higher in economically developed regions（per capita GDP ≥ 92 059 Yuan）than that in economically less-developed regions（per capita GDP <92 059 Yuan）（ χ2=6.240， P=0.012）. Conclusions:The proportion of Gram-negative bacteria in bloodstream infections shows an increasing trend，and Escherichia coli is ranked in the top，while the trend of CRKP decreases continuously with time. Decreasing trends are noted in ESBLs-producing Escherichia coli and Klebsiella pneumoniae. Low prevalence of carbapenem resistance in Escherichia coli and high prevalence in CRAB complex have been observed. The composition ratio and antibacterial spectrum of bloodstream infections in different regions of China are slightly different，and the proportion of main drug resistant bacteria in provincial hospitals is higher than those in municipal hospitals.

BackgroundPatients demonstrating depressive disorder with psychotic symptoms often have increased risk of death and poor prognosis. A large amount of research has explored the factors influencing psychotic symptoms in adult patients with depressive disorder， but few has focused on adolescent patients. ObjectiveTo explore the influencing factors of psychotic symptoms in adolescent patients with depressive disorder， so as to provide references for early screening and intervention in clinic. MethodsA total of 96 adolescent patients who met the Diagnostic and Statistical Manual of Mental Disorders， fifth edition （DSM-5） for depressive disorder and were seen in the psychiatry departments of Chaohu Hospital of Anhui Medical University and The Fourth People's Hospital of Hefei from September 2022 to January 2023 were included. Another 56 healthy individuals from the health examination center of Chaohu Hospital of Anhui Medical University were concurrently recruited as control group. Patients were assigned into psychotic group （n=32） and non-psychotic group （n=64） according to the presence or absence of psychotic symptoms. Hamilton Depression Scale-24 item （HAMD-24）， Positive and Negative Syndrome Scale （PANSS）， Positive and Negative Suicide Ideation （PANSI） and Childhood Trauma Questionnaire-Short Form （CTQ-SF） were used for evaluation. Plasma brain-derived neurotrophic factor （BDNF） concentration was obtained using Meso Scale Discovery electrochemiluminescence assay. Pearson and Spearman correlation analysis were adopted to determine the correlation of PANSS positive symptom subscale score with plasma BDNF concentration and clinical characteristics of adolescent depression patients with psychotic symptoms. Binary Logistic regression analysis was used to identify the factors influencing the presence of psychotic symptoms in adolescent patients with depressive disorder， and multiple linear regression analysis was utilized to screen the factors affecting the severity of psychotic symptoms. ResultsThe plasma BDNF concentration of adolescent patients with depressive disorder was lower than that of control group （t=-3.080， P<0.01）.The plasma BDNF concentration of psychotic group was lower than that of non-psychotic group （t=2.418， P<0.05）， while the body mass index （BMI） PANSI scores， CTQ-SF scores and HAMD-24 total scores were all higher than those of non-psychotic group （t=-2.024， -2.530， -2.187， -4.977， P<0.05 or 0.01）. Correlation analysis showed that PANSS positive symptom subscale scores were negatively correlated with anxiety/somatization factor score and weight factor score in HAMD-24 of psychotic group （r=-0.438， -0.498， P<0.05 or 0.01）. Binary Logistic regression showed that BMI， plasma BDNF concentration， HAMD-24 total scores and cognitive dysfunction factor score were the influencing factors of psychotic symptoms in adolescent patients with depressive disorder. Multiple linear regression analysis demonstrated that weight factor scores （β=-0.349， P<0.05） and anxiety/somatization factor score （β=-0.433， P<0.05） in HAMD-24 were the factors influencing the severity of psychotic symptoms. ConclusionHigh BMI， low plasma BDNF concentration， severe depressive symptoms and cognitive dysfunction may be the risk factors of psychotic symptoms in adolescent patients with depressive disorder， furthermore， BMI and anxiety symptoms are found to be associated with the severity of psychotic symptoms. ［Funded by Scientific Research Fund Project of Anhui Institute of Translational Medicine （number， 2022zhyx-B01）； Central Finance Supported Provincial Key Clinical Specialty Construction Project of Anhui Province in 2019］

Objective:To explore the role of Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)combined with Rank Sum Ration(RSR)comprehensive evaluation method in establishing the China Healthcare Security Diagnosis Related Groups(CHS-DRG)operational performance system under the CHS-DRG payment system.Methods:SPSSPRO statistical analysis software was used,and TOPSIS method was used to regularly evaluate and rank the CHS-DRG disease groups in the hospital based on five indicators:Case Mix Index(CMI),total weight,average cost per weight,average length of stay per weight,and group profit and loss.RSR method was used to classify the TOPSIS disease group ranking results,establish performance reward standards for different grades of disease groups,and summarize and restore the reward results for each patient in the disease group to each clinical department,ultimately forming a department performance reward plan.The changes in key operational indicators related to medical insurance patients in hospitals were observed to verify the effectiveness of implementing performance reward programs.Results:After the application of TOPSIS combined with RSR comprehensive evaluation method in the construction of CHS-DRG operational performance system,the number of hospital medical insurance patients were increased,CMI value were stabilized,average cost per visit were decreased,average length of stay were shortened,and DRG disease group surplus were increased.Conclusion:The TOPSIS combined with RSR comprehensive evaluation method has played a good role in the construction of the CHS-DRG operational performance system.As a method of hospital economic operation evaluation,it is practical and innovative.

Objective:To explore the role of Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)combined with Rank Sum Ration(RSR)comprehensive evaluation method in establishing the China Healthcare Security Diagnosis Related Groups(CHS-DRG)operational performance system under the CHS-DRG payment system.Methods:SPSSPRO statistical analysis software was used,and TOPSIS method was used to regularly evaluate and rank the CHS-DRG disease groups in the hospital based on five indicators:Case Mix Index(CMI),total weight,average cost per weight,average length of stay per weight,and group profit and loss.RSR method was used to classify the TOPSIS disease group ranking results,establish performance reward standards for different grades of disease groups,and summarize and restore the reward results for each patient in the disease group to each clinical department,ultimately forming a department performance reward plan.The changes in key operational indicators related to medical insurance patients in hospitals were observed to verify the effectiveness of implementing performance reward programs.Results:After the application of TOPSIS combined with RSR comprehensive evaluation method in the construction of CHS-DRG operational performance system,the number of hospital medical insurance patients were increased,CMI value were stabilized,average cost per visit were decreased,average length of stay were shortened,and DRG disease group surplus were increased.Conclusion:The TOPSIS combined with RSR comprehensive evaluation method has played a good role in the construction of the CHS-DRG operational performance system.As a method of hospital economic operation evaluation,it is practical and innovative.

Objective:To explore the role of Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)combined with Rank Sum Ration(RSR)comprehensive evaluation method in establishing the China Healthcare Security Diagnosis Related Groups(CHS-DRG)operational performance system under the CHS-DRG payment system.Methods:SPSSPRO statistical analysis software was used,and TOPSIS method was used to regularly evaluate and rank the CHS-DRG disease groups in the hospital based on five indicators:Case Mix Index(CMI),total weight,average cost per weight,average length of stay per weight,and group profit and loss.RSR method was used to classify the TOPSIS disease group ranking results,establish performance reward standards for different grades of disease groups,and summarize and restore the reward results for each patient in the disease group to each clinical department,ultimately forming a department performance reward plan.The changes in key operational indicators related to medical insurance patients in hospitals were observed to verify the effectiveness of implementing performance reward programs.Results:After the application of TOPSIS combined with RSR comprehensive evaluation method in the construction of CHS-DRG operational performance system,the number of hospital medical insurance patients were increased,CMI value were stabilized,average cost per visit were decreased,average length of stay were shortened,and DRG disease group surplus were increased.Conclusion:The TOPSIS combined with RSR comprehensive evaluation method has played a good role in the construction of the CHS-DRG operational performance system.As a method of hospital economic operation evaluation,it is practical and innovative.

Objective:To explore the role of Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)combined with Rank Sum Ration(RSR)comprehensive evaluation method in establishing the China Healthcare Security Diagnosis Related Groups(CHS-DRG)operational performance system under the CHS-DRG payment system.Methods:SPSSPRO statistical analysis software was used,and TOPSIS method was used to regularly evaluate and rank the CHS-DRG disease groups in the hospital based on five indicators:Case Mix Index(CMI),total weight,average cost per weight,average length of stay per weight,and group profit and loss.RSR method was used to classify the TOPSIS disease group ranking results,establish performance reward standards for different grades of disease groups,and summarize and restore the reward results for each patient in the disease group to each clinical department,ultimately forming a department performance reward plan.The changes in key operational indicators related to medical insurance patients in hospitals were observed to verify the effectiveness of implementing performance reward programs.Results:After the application of TOPSIS combined with RSR comprehensive evaluation method in the construction of CHS-DRG operational performance system,the number of hospital medical insurance patients were increased,CMI value were stabilized,average cost per visit were decreased,average length of stay were shortened,and DRG disease group surplus were increased.Conclusion:The TOPSIS combined with RSR comprehensive evaluation method has played a good role in the construction of the CHS-DRG operational performance system.As a method of hospital economic operation evaluation,it is practical and innovative.

Objective:To explore the role of Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)combined with Rank Sum Ration(RSR)comprehensive evaluation method in establishing the China Healthcare Security Diagnosis Related Groups(CHS-DRG)operational performance system under the CHS-DRG payment system.Methods:SPSSPRO statistical analysis software was used,and TOPSIS method was used to regularly evaluate and rank the CHS-DRG disease groups in the hospital based on five indicators:Case Mix Index(CMI),total weight,average cost per weight,average length of stay per weight,and group profit and loss.RSR method was used to classify the TOPSIS disease group ranking results,establish performance reward standards for different grades of disease groups,and summarize and restore the reward results for each patient in the disease group to each clinical department,ultimately forming a department performance reward plan.The changes in key operational indicators related to medical insurance patients in hospitals were observed to verify the effectiveness of implementing performance reward programs.Results:After the application of TOPSIS combined with RSR comprehensive evaluation method in the construction of CHS-DRG operational performance system,the number of hospital medical insurance patients were increased,CMI value were stabilized,average cost per visit were decreased,average length of stay were shortened,and DRG disease group surplus were increased.Conclusion:The TOPSIS combined with RSR comprehensive evaluation method has played a good role in the construction of the CHS-DRG operational performance system.As a method of hospital economic operation evaluation,it is practical and innovative.

Objective:To explore the role of Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)combined with Rank Sum Ration(RSR)comprehensive evaluation method in establishing the China Healthcare Security Diagnosis Related Groups(CHS-DRG)operational performance system under the CHS-DRG payment system.Methods:SPSSPRO statistical analysis software was used,and TOPSIS method was used to regularly evaluate and rank the CHS-DRG disease groups in the hospital based on five indicators:Case Mix Index(CMI),total weight,average cost per weight,average length of stay per weight,and group profit and loss.RSR method was used to classify the TOPSIS disease group ranking results,establish performance reward standards for different grades of disease groups,and summarize and restore the reward results for each patient in the disease group to each clinical department,ultimately forming a department performance reward plan.The changes in key operational indicators related to medical insurance patients in hospitals were observed to verify the effectiveness of implementing performance reward programs.Results:After the application of TOPSIS combined with RSR comprehensive evaluation method in the construction of CHS-DRG operational performance system,the number of hospital medical insurance patients were increased,CMI value were stabilized,average cost per visit were decreased,average length of stay were shortened,and DRG disease group surplus were increased.Conclusion:The TOPSIS combined with RSR comprehensive evaluation method has played a good role in the construction of the CHS-DRG operational performance system.As a method of hospital economic operation evaluation,it is practical and innovative.