ObjectiveTo investigate the microbial contamination status of commercially available ready-to-eat (RTE) foods in Songjiang District of Shanghai, to verify the potential food safety hazards, so as to provide a scientific basis for the local regulation of RTE foods and the prevention of foodborne diseases. MethodsA total of 882 food samples from 9 categories of RTE foods were collected in Shanghai from 2017 to 2022. Salmonella, Listeria monocytogenes, Vibrio parahaemolyticus, Staphyloccus aureus and Bacillus cereus were detected according to the standard operating procedures in the Manual for China National Food Contamination and Harmful Factors Risk Monitoring, and which were determined with reference to relevant standards. ResultsA total of 77 samples were found to carry foodborne pathogens, with a total detection rate of 8.73%. Among the 5 foodborne pathogens, Bacillus cereus had the highest detection rate (8.35%), followed by Vibrio parahaemolyticus (5.05%), and the difference of detection rates among the 5 foodborne pathogens was statistically significant (χ²=112.307, P<0.001). Among the 9 categories of RTE food products, the detection rate of foodborne pathogens in RTE fermented/non-fermented soybean products was the highest (27.50%), followed by cold noodles (17.33%) and raw edible aquatic products (9.50%), and the difference in the detection rates of foodborne pathogens among different RTE food categories was statistically significant (χ²=45.909, P<0.001). The detection rate of foodborne pathogens in the third quarter of the year was 10.99%, significantly higher than that in other quarters (χ²=10.329, P=0.016). The detection rate of foodborne pathogens in samples from supermarkets was highest (15.08%), followed by snack bars (11.58%), with a statistically significant difference (χ²=14.108, P=0.015). ConclusionFoodborne pathogens contamination is found in commercially available RTE foods in Songjiang District of Shanghai, especially in RTE fermented/non-fermented soybean products, RTE cold noodles and raw edible aquatic products from supermarkets, snack bars and farm products markets during summer and autumn. Therefore, it is crucial to strengthen supervision and management to avoid the foodborne diseases.

With the increasing aging population in China and rising incidence rates of diseases such as cancer and cardiovascular conditions, the demand for palliative care services continues to grow. In recent years, the integration of artificial intelligence and medical disciplines has advanced significantly, with machine learning research and applications in the palliative care field progressing steadily. This paper reviews the overview of machine learning, its applications in palliative care, and effectiveness evaluations. It also discusses existing limitations in current research and provides recommendations for future studies. The aim is to assist healthcare professionals in improving palliative care services and offer valuable insights for the development of palliative care in China.

Objective:To summarize the current status of the application of automated interactive voice response systems (AIVRS) in post-diagnosis management of chronic disease patients.Methods:A computer search was conducted in PubMed, Embase, Web of Science, CINAHL, Cochrane Library, China National Knowledge Infrastructure, Wanfang Data, China Biology Medicine disc, and VIP, covering the literature from establishing these databases to May 25, 2024. Two researchers screened the literature and extracted data based on inclusion and exclusion criteria.Results:A total of 16 articles were included. The content of AIVRS in post-diagnosis management of chronic disease patients mainly includes self-care guidance, medication management, and decision support. The outcome indicators primarily focus on feasibility evaluation and effect evaluation.Conclusions:AIVRS is feasible in post-diagnosis management of chronic disease patients. However, there are still shortcomings, such as technical limitations, performance issues, and the use of unimodal data to assess patient outcome indicators. Future research could strengthen the theoretical foundation of AIVRS in post-diagnosis management interventions, appropriately add interactive modules, and provide real-time guidance to improve the effectiveness of AIVRS in post-diagnosis management.

Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1％(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5％,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3％(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1％)were isolated from sputum and respiratory secretions,followed by urine(10.7％)and blood samples(8.1％).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1％.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4％in the patients＜18 years old to 20.6％in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.

Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43％(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38％,9.73％,and 8.47％,respectively.The prevalence of CRE strains in Escherichia coli was 1.99％.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)％,followed by blood(20.88±3.40)％and urine(18.40±3.45)％.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)％.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.

Objective To characterize the changing species distribution and antibiotic resistance profiles of respiratory isolates in hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Commercial automated antimicrobial susceptibility testing systems and disk diffusion method were used to test the susceptibility of respiratory bacterial isolates to antimicrobial agents following the standardized technical protocol established by the CHINET program.Results A total of 589 746 respiratory isolates were collected from 2015 to 2021.Overall,82.6％of the isolates were Gram-negative bacteria and 17.4％were Gram-positive bacteria.The bacterial isolates from outpatients and inpatients accounted for(6.0±0.9)％and(94.0±0.1)％,respectively.The top microorganisms were Klebsiella spp.,Acinetobacter spp.,Pseudomonas aeruginosa,Staphylococcus aureus,Haemophilus spp.,Stenotrophomonas maltophilia,Escherichia coli,and Streptococcus pneumoniae.Each microorganism was isolated from significantly more males than from females(P＜0.05).The overall prevalence of methicillin-resistant S.aureus(MRSA)was 39.9％.The prevalence of penicillin-resistant S.pneumoniae was 1.4％.The prevalence of extended-spectrum β-lactamase(ESBL)-producing E.coli and K.pneumoniae was 67.8％and 41.3％,respectively.The overall prevalence of carbapenem-resistant E.coli,K.pneumoniae,Enterobacter cloacae,Pseudomonas aeruginosa,and Acinetobacter baumannii was 3.7％,20.8％,9.4％,29.8％,and 73.3％,respectively.The prevalence of β-lactamase was 96.1％in Moraxella catarrhalis and 60.0％in Haemophilus influenzae.The H.influenzae isolates from children(＜18 years)showed significantly higher resistance rates to β-lactam antibiotics than the isolates from adults(P＜0.05).Conclusions Gram-negative bacteria are still predominant in respiratory isolates associated with serious antibiotic resistance.Antimicrobial resistance surveillance should be strengthened in clinical practice to support accurate etiological diagnosis and appropriate antimicrobial therapy based on antimicrobial susceptibility testing results.

Objective To investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3％)and from outpatient and emergency care patients(4.7％).Overall,19.6％of the isolates were from children and 80.4％were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0％and 32.0％,respectively.Coagulase negative Staphylococcus accounted for 73.0％of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2％in children and 45.6％in adults.The prevalence of MRCNS was 67.6％in adults and 69.5％in children.A small number of vancomycin-resistant Enterococcus faecium(2.2％)and linezolid-resistant Enterococcus faecalis(3.1％)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2％and 76.4％in children,70.5％and 63.5％in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3％and 47.7％in children,6.4％and 47.9％in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0％and 37.1％in children,81.7％and 39.9％in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.

Objective To investigate the antimicrobial resistance of clinical isolates from elderly patients(≥65 years)in major medical institutions across China.Methods Bacterial strains were isolated from elderly patients in 52 hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program during the period from 2015 to 2021.Antimicrobial susceptibility test was carried out by disk diffusion method and automated systems according to the same CHINET protocol.The data were interpreted in accordance with the breakpoints recommended by the Clinical and Laboratory Standards Institute(CLSI)in 2021.Results A total of 514 715 nonduplicate clinical isolates were collected from elderly patients in 52 hospitals from January 1,2015 to December 31,2021.The number of isolates accounted for 34.3％of the total number of clinical isolates from all patients.Overall,21.8％of the 514 715 strains were gram-positive bacteria,and 78.2％were gram-negative bacteria.Majority(90.9％)of the strains were isolated from inpatients.About 42.9％of the strains were isolated from respiratory specimens,and 22.9％were isolated from urine.More than half(60.7％)of the strains were isolated from male patients,and 39.3％isolated from females.About 51.1％of the strains were isolated from patients aged 65-＜75 years.The prevalence of methicillin-resistant strains(MRSA)was 38.8％in 32 190 strains of Staphylococcus aureus.No vancomycin-or linezolid-resistant strains were found.The resistance rate of E.faecalis to most antibiotics was significantly lower than that of Enterococcus faecium,but a few vancomycin-resistant strains(0.2％,1.5％)and linezolid-resistant strains(3.4％,0.3％)were found in E.faecalis and E.faecium.The prevalence of penicillin-susceptible S.pneumoniae(PSSP),penicillin-intermediate S.pneumoniae(PISP),and penicillin-resistant S.pneumoniae(PRSP)was 94.3％,4.0％,and 1.7％in nonmeningitis S.pneumoniae isolates.The resistance rates of Klebsiella spp.(Klebsiella pneumoniae 93.2％)to imipenem and meropenem were 20.9％and 22.3％,respectively.Other Enterobacterales species were highly sensitive to carbapenem antibiotics.Only 1.7％-7.8％of other Enterobacterales strains were resistant to carbapenems.The resistance rates of Acinetobacter spp.(Acinetobacter baumannii 90.6％)to imipenem and meropenem were 68.4％and 70.6％respectively,while 28.5％and 24.3％of P.aeruginosa strains were resistant to imipenem and meropenem,respectively.Conclusions The number of clinical isolates from elderly patients is increasing year by year,especially in the 65-＜75 age group.Respiratory tract isolates were more prevalent in male elderly patients,and urinary tract isolates were more prevalent in female elderly patients.Klebsiella isolates were increasingly resistant to multiple antimicrobial agents,especially carbapenems.Antimicrobial resistance surveillance is helpful for accurate empirical antimicrobial therapy in elderly patients.

With the increasing aging population in China and rising incidence rates of diseases such as cancer and cardiovascular conditions, the demand for palliative care services continues to grow. In recent years, the integration of artificial intelligence and medical disciplines has advanced significantly, with machine learning research and applications in the palliative care field progressing steadily. This paper reviews the overview of machine learning, its applications in palliative care, and effectiveness evaluations. It also discusses existing limitations in current research and provides recommendations for future studies. The aim is to assist healthcare professionals in improving palliative care services and offer valuable insights for the development of palliative care in China.

Objective:To summarize the current status of the application of automated interactive voice response systems (AIVRS) in post-diagnosis management of chronic disease patients.Methods:A computer search was conducted in PubMed, Embase, Web of Science, CINAHL, Cochrane Library, China National Knowledge Infrastructure, Wanfang Data, China Biology Medicine disc, and VIP, covering the literature from establishing these databases to May 25, 2024. Two researchers screened the literature and extracted data based on inclusion and exclusion criteria.Results:A total of 16 articles were included. The content of AIVRS in post-diagnosis management of chronic disease patients mainly includes self-care guidance, medication management, and decision support. The outcome indicators primarily focus on feasibility evaluation and effect evaluation.Conclusions:AIVRS is feasible in post-diagnosis management of chronic disease patients. However, there are still shortcomings, such as technical limitations, performance issues, and the use of unimodal data to assess patient outcome indicators. Future research could strengthen the theoretical foundation of AIVRS in post-diagnosis management interventions, appropriately add interactive modules, and provide real-time guidance to improve the effectiveness of AIVRS in post-diagnosis management.