ObjectiveTo identify the risk factors of Intensive Care Unit (ICU) nosocomial infection in ICU ward in a first-class hospital in Wuxi, and discuss the effective control measures, in order to provide evidence for making strategies in preventing and controlling nosocomial infection. MethodsAccording to the principle of random sampling and with the use of case-control study, a sample of 100 nosocomial infection patients were selected randomly from January 2012 to December 2014 as survey group, and another 100 patients without nosocomial infection as control group. The data were input using EpiData 2.0, and SPSS 13.0 was used for statistical analysis; t-test and χ2 test were conducted, and the risk factors were analyzed using multi-variate logistic regression model. The significant level of P-value was 0.05. ResultsBased on the results of univariate analysis, there were 13 risk factors for ICU nosocomial infection, including diabetes mellitus, hypoproteinemia, being bedridden, surgical operation, immunosuppression, glucocorticoids, organ transplantation, tracheal intubation, length of hospitalization, length of mechanical ventilation, length of central venous catheter, length of urinary catheter, and length of nasogastric tube indwelling. Multi-variate logistic analysis indicated that hospitalization of 7 days or longer[OR=1.106, 95%CI (1.025, 1.096), P=0.001], diabetes mellitus[OR=2.770, 95%CI (1.068, 7.186), P=0.036], surgical operation[OR=7.524, 95%CI (2.352, 24.063), P=0.001], mechanical ventilation of 7 days or longer[OR=1.222, 95%CI (1.116, 1.339), P<0.001], and nasogastric tube indwelling of 7 days or longer[OR=1.110, 95%CI (1.035, 1.190), P=0.003] were considered as independent risk factors for ICU nosocomial infection. ConclusionHospitalization of 7 days or longer, diabetes mellitus, surgical operation, tracheal intubation of 7 days or longer, and gastric intubation of 7 days or longer are the major risk factors for nosocomial infection in ICU ward. Advanced intervention and comprehensive prevention measures are helpful to reduce the nosocomial infection rate and ensure the safety of medical treatment.
Objective To understand the current situation of nosocomial infection management quality control centers at the municipal and county levels in Guizhou, so as to provide measures for promoting the construction of nosocomial infections management quality control centers at all levels in Guizhou. Methods From September 26th to October 12th 2023, based on the mobile network platform survey questionnaire of the infection prevention and control workshop, a survey was conducted on the establishment, personnel, information technology level, management, and quality control work of the nosocomial infection management quality control centers at the municipal and county levels in Guizhou. Results Nine prefecture-level cities/autonomous prefectures in Guizhou had established municipal-level nosocomial infection management quality control centers. The professional background of the staff at the municipal and county-level quality control centers was mainly nursing (accounting for 36.4% and 58.4%, respectively), and their educational background was mainly undergraduate (accounting for 70.5% and 83.3%, respectively). No quality control center at the municipal or county level had established an information-based quality control platform for nosocomial infection management within the region. Most county-level quality control centers did not have special funds (87.5%), and there were still 16 (25.0%) county-level quality control centers that had not established relevant systems for work and management. The main forms of quality control work carried out by each center were organizing training, on-site inspections, guidance and evaluation, and most of them were conducted irregularly. Conclusions Guizhou has basically formed a quality control system for nosocomial infection management at the provincial, municipal, and county levels. However, the nosocomial infection management quality control network has not fully covered all districts, and policies, funding support, and personnel allocation are still insufficient. Health administrative departments and quality control centers at all levels need to unify monitoring standards and quality control norms, strengthen supervision, improve quality control capabilities, and improve training systems to achieve standardization and normalization of quality control work throughout the province and improve quality control efficiency.
Objective To establish the control range of monthly nosocomial infection incidences in different departments and put them into practice, to provide a scientific and effective method for nosocomial infection control. Methods The surveillance data about nosocomial infection cases in Nanchong Central Hospital from January 2016 to December 2018 were used to set the warning limits and control limits in different departments based on the theory of medical reference range. From January 2019, the clinical departments would be alerted if their nosocomial infection incidences were beyond the warning limits, and investigated and intervened if the incidences were beyond the control limits. Results The control range of monthly nosocomial infection incidences in different departments had been made. For identifying risk events, the sensitivity was 83.3%, the specificity was 96.2%, the positive predictive value was 29.4%, the negative predictive value was 99.7%, the coincidence rate was 96.0%, and the consistency was medium (kappa=0.419, P<0.001). The effective rate of the initial alert intervention was 83.3%, and the effective rate of the field intervention was 100.0%. Conclusion The establishment and application of the control range of monthly nosocomial infection incidences in different departments can identify potential risk events and realize precise nosocomial infection control.
ObjectiveTo analyze the trend of hospital infection, so as to provide a scientific basis for hospital infection prevention and control. MethodsFrom 2011 to 2013, according to the criteria of diagnosis of nosocomial infections set up by the Ministry of Health, the prevalence rates of nosocomial infections in patients who were hospitalized on the survey day were investigated by the combination of bedside investigation and medical records checking. ResultsThe incidence rates of nosocomial infections from 2011 to 2013 were 2.99%, 2.31% and 1.95%, respectively, presenting a downward trend. The rate of hospital infection was the highest in comprehensive Intensive Care Unit, and the main infection site was the lower respiratory tract. Gram-negative bacteria were the main pathogens causing hospital infections, including Klebliella pnermoniae, Pseudomonas aeruginosa, Staphylococcus aureus, Acinetobacter baumannii and Escherichia coli. The utilization rates of antibacterial agents in these three years were respectively 39.84%, 34.58% and 34.22%. ConclusionTargeted surveillance and management of key departments and sites should be strengthened. It is necessary to strengthen the surveillance and management of antibiotics, raise the submission rate of pathogens, and use antibiotics appropriately.
ObjectiveTo find out the major isolates distribution, drug resistance changes of multidrug-resistant organisms (MDRO) in 2013 for rational use of antibiotics and hospital infection control. MethodsA total of 32 566 cultured bacteria samples from the patients diagnosed between January 1st and December 31st 2013 were collected, using conventional tube biochemical assays and semi-automatic automicrobic (AMS) for bacteria identification; and antimicrobial susceptibility testing, major drug resistance mechanism detection were performed according to CLSI documents. MDRO definition was made according to the 2011 international consensus from European Center for Disease Control and Prevention (CDC), American CDC, Clinical and Laboratory Standards Institute (CLSI), and Food and Drug Administration. The data was analyzed by WHOnet 5.6 software. ResultsWe got 3 684 strains isolates, G- accounted for 76.08%, G+ 16.80%, fungi 7.11%, and fastidious bacteria 17.29%. The top ten isolates in order were:E.coli, A.baumannii, Ps.aeruginosa, H.influenzae, K.pneumoniae, S.aureus, S.pneumoniae, A.fumigatus, M.catarrhalis and C.freundii. From the first quarter 2012 to the fourth quarter 2013, the extended spectrum β lactamases (ESBL)-producing E.coli increased from 40.23% to 53.54%, ESBL-producing K.pneumonia increased from 14.28% to 34.78%, XDR-A.baumannii increased from 62.38% to 99.25%, metalloenzyme-producing Ps.aeruginosa increased from 7.37% to 25.37%, methicillin resistant staphylococcus aureus increased from 23.81% to 58.70%, and VRE increased from 0.00% to 28.12%. ConclusionIn the isolates, the percentage of G- was the highest, and the rate of MDRO are all unremittingly raising, which suggests us should pay more attention to microbiology analysis, rational use of antibiotics, strengthening hospital infection control, reducing the bacterial resistance, and strengthening MDRO surveillance.
ObjectiveTo explore the risk factors for surgical patients associated with postoperative nosocomial infection through monitoring the infection conditions of the patients, in order to provide a scientific basis for the development of hospital infection control measures in a second-grade class-A hospital in Chengdu City. MethodsWe conducted the survey with cluster sampling as the sampling method and the uniform questionnaire in the departments of orthopedic, neural and thoracic surgery from July 2011 to June 2012. The main parameters we observed were the patients'general and surgical conditions, antibiotics usage and hospital infection situation. Data were analyzed using the National Nosocomial Infection Surveillance Network software and chi-square test of single factors. ResultsIn this survey, we monitored 50 cases of postoperative hospital infection. The infection rate was 7.73% and the highest infection rate was in the Neurosurgery Department. The main site of infection was lower respiratory tract, followed by surgical site. The different usage time of antimicrobial drug in perioperative period resulted in different infection rates, and the difference was statistically significant (χ2=601.50, P<0.005). The rate of adjusted postoperative hospital infection was higher than pre-adjusted rate except that of the neurosurgery doctor 4. The risk factors associated with hospital postoperative infection in our hospital were:patients'conditions including underlying disease, emergency surgery, type of anesthesia, operative duration, hospital stay and postoperative drainage. Most of the hospital infection cases were caused by bacteria of the gram-negative bacilli, and the major pathogens were Klebsiella pneumoniae, Pseudomonas aeruginosa and Acinetobacter baumannii in our hospital. ConclusionThe hospital should particularly strengthen the prevention and control of hospital infection in patients after neurosurgical operations. For patients with basic diseases, we should actively improve the patients'physical conditions before operation and control the primary lesion. Targeted control measures should be taken for different factors related to surgery. Reasonable selection of antimicrobial agents should be based on the epidemic strains in our hospital.
Objective To investigate nosocomial non-fermented bacterial infection in lower respiratory tract and the risk factors for multi-drug resistant bacterial infection. Methods 229 patients with nosocomial nonfermented bacterial infection in lower respiratory tract from January to December in 2007 in Xiangya Hospital were analyzed retrospectively. The distribution and drug sensitivity of pathogens were recorded. Of those 229 patients,183 cases were infected by non-fermented multi-drug resistant bacteria( MDRB) . The risk factors for non-fermented MDRB infection in lower respiratory tract were analyzed by multi-factor logistic multiple regression analysis.Results The top four non-fermented bacteria isolated were Pseudomonas aeruginosa( 47.6%) , Acinetobacter baumannii( 36. 3% ) , Acinetobacter spp( 8. 6% ) , and Stenotrophomonas maltophilia( 5. 1%) . Higher isolatated rate was found in neurosurgery ( 25. 7% ) and central ICU( 22. 9% ) . The isolated non-fermented bacteria except Stenotrophomonas maltophilia were resistant to all antibiotics except cefoperazone-sulbactam and meropenem. ICU stay( P lt; 0. 001) , tracheotomy or tracheal intubation( P = 0. 001) , and previous use of carbapenemantibiotics( P =0. 032) were independent risk factors for non-fermented MDRB infection. Conclusion Non-fermented bacillus were important pathogens of nosocomial infection in lower respiratory tract with high rates of antibiotic resistance. It is important to prevent non-fermented MDRB infection by strict limitation on the indication of ICU stay,tracheotomy and use of carbapenem.
ObjectiveTo enhance the management of occupational exposure, improve post-exposure reporting, promote post-exposure follow-up, reduce blood-borne infections caused by exposure, and ensure occupational safety among medical staff by using comprehensive measures based on nosocomial infection management system.MethodsAll the reported cases of occupational exposure were retrospectively collected from August 2012 to July 2018. The cases were divided into the control group (from August 2012 to July 2015) in which the data were reported in paper, and the observation group (from August 2015 to July 2018) in which the data were reported by nosocomial infection management system. The report and follow up results of occupational exposure in the two groups were compared and analyzed.ResultsAfter three years application of nosocomial infection management system, the occupational exposure report increased 95.8% (increased from 16.7 cases per year to 32.7 cases per year); the follow-up ratio of occupational exposure after one month,3 months and 6 months increased from 65.0% to 93.3% (χ2=15.184, P<0.001), 45.0% to 73.3% (χ2=9.033, P=0.003), and 25.0% to 53.3% (χ2=8.522, P=0.004), respectively.ConclusionApplication of nosocomial infection management system can increase the report of occupational exposure and the follow-up ratio of occupational exposure significantly.
Objective To investigate the application of risk assessment in the control of nosocomial infections in surgical departments of infectious disease hospitals so as to provide references for the regulation of prevention and control measures. Methods Nosocomial infection risks in surgical departments of infectious disease hospitals were identified by the method of brainstorming. Based on risk assessment and planning of American children's national medical center in Washington for epidemic and infectious diseases control, the matrix method was used for risk assessment. The three highest risks were controlled, and then we compared the incidence of nosocomial infections before and after the risk assessment. Results The major risk factors in surgical departments existed in the process of diagnosis and treatment. By matrix scoring, excluding high readiness items, we found that the top three risks were airborne diseases, prevention and nursing of hematogenous infections and air disinfection. Nosocomial infection rate in the surgical departments dropped to 2.03% after carrying out risk assessment and taking correspondent measures (χ2=5.480,P=0.019). Conclusion Evaluation of nosocomial infection risk in surgical departments of infectious disease hospitals can discover major potential risks and reduce the incidence of nosocomial infections, which can provide references for management and control of nosocomial infections.
ObjectiveTo explore the distribution of multidrug resistant organism in neonates admitted to the hospital through various ways, and analyze the risk factors in order to avoid cross infection of multidrug resistant organism in neonatology department. MethodsA total of 2 124 neonates were monitored from January 2012 to July 2013, among which 1 119 were admitted from outpatient department (outpatient group), 782 were transferred from other departments (other department group), and 223 were from other hospitals (other hospital group). We analyzed their hospital stays, weight, average length of stay, and drug-resistant strains, and their relationship with nosocomial infection. ResultsAmong the 105 drug-resistant strains, there were 57 from the outpatient group, 27 from the other department group, and 21 from the other hospital group. The positive rate in the patients transferred from other hospitals was the highest (9.42%). Neonates with the hospital stay of more than 14 days and weighing 1 500 g or less were the high-risk groups of drug-resistant strains in nosocomial infection. Drug-resistant strains of nosocomial infection detected in the patients admitted through different ways were basically identical. ConclusionWe should strengthen screening, isolation, prevention and control work in the outpatient neonate. At the same time, we can't ignore the prevention and control of the infection in neonates from other departments or hospitals, especially the prevention and control work in neonates with the hospital stay of more than 14 days and weighing 1 500 g or less to reduce the occurrence of multiple drug-resistant strains cross infection.