ObjectiveTo evaluate the role of CD3+CD4+T cells in patients with nosocomial infection in ICU. MethodsOne-hundred and eleven patients who admitted in ICU and in respiratory department from March to December in 2014 were recruited in the study.There were 33 patients with community-acquired pneumonia (CAP group), 31 patients without nosocomial infection (NNI group), and 47 patients with hospital-acquired pneumonia (HAP group).The counts of T cells, B cells, CD3+CD4+ T cells, CD3+CD8+ T cells, and NK cells were compared among three groups. ResultsThe comparison among the groups had no statistical significance in sex and age(P > 0.05).The three groups had statistical significance in APACHEⅡscore, CD3+CD4+T cells, T cells and B cells, but had no statistical significance in CD3+CD8+T cells, CD3+CD4+/CD3+CD8+ T cells, NK cells, white blood cells, neutrophils, procalcitonin or C reactive protein.CD3+CD4+T cells of HAP group were less than other two groups.The area under the ROC curve (AUC) was 0.660, with a threshold of 29.96%, a sensitivity of 93.8%, and a specificity of 40.4%. ConclusionCD3+CD4+ T cell is an independent predictor for nosocomial infection.
ObjectiveTo understand the characteristics of and risk factors for nosocomial infection in a newly built branch of a university teaching hospital, in order to investigate the control measures for prevention and control of nosocomial infection. MethodsA total of 598 cases of nosocomial infection from April 2012 to June 2014 were enrolled in this study. We analyzed statistically such indexes as nosocomial infection rate, infection site, pathogen detection, and use of antibiotics. Meantime, infection point-prevalence survey was introduced by means of medical record checking and bedside visiting. ResultsAmong all the 44 085 discharged patients between April 2012 and June 2014, there were 598 cases of nosocomial infection with an infection rate of 1.36%. Departments with a high nosocomial infection rate included Intensive Care Unit (ICU) (9.79%), Department of Orthopedics (2.98%), Department of Geriatrics (2.62%), and Department of Hematology (1.64%). The top four nosocomial infection sites were lower respiratory tract (45.32%), urinary tract (13.21%), operative incision (8.86%), and blood stream (8.86%). The samples of 570 nosocomial infections were delivered for examination with a sample-delivering rate of 95.32%. The most common pathogens were acinetobacter Baumanii (17.02%), Klebsiella pneumoniae (14.21%), Escherichia coli (13.68%), Pseudomonas aeruginosa (11.93%), and Staphylococcus aureus (9.12%). And urinary tract intubation (42.81%), admission of ICU (28.60%), and application of corticosteroid and immunosuppressive agents (26.42%) were the top three independent risk factors for nosocomial infection. ConclusionGeneral and comprehensive monitoring is an effective method for the hospital to detect high-risk departments, factors and patients for nosocomial infection, providing a theoretical basis for prevention and control of nosocomial infection.
ObjectiveTo carry out targeted surveillance on ventilator-associated pneumonia (VAP) newly defined by the Centers for Disease Control and Prevention of the United States in 2013, and to understand its applicability and influence on the prognosis, and infection rate and risk factors of the disease. MethodsTargeted surveillance was carried out on all patients receiving mechanical ventilation in the general ICU of our hospital between January and December 2014. VAP infection rate was studied, and patients were divided into groups based on the development of the disease. SPSS 18.0 was used for statistical analysis of the prognostic indicators. ResultsA total of 885 patients received mechanical ventilation and were monitored, 31 of whom had VAP. The VAP case infection rate was 3.5% and its daily infection rate was 3.9‰. The results of multiple factors regression analysis showed that age (OR=1.025, P=0.025) and combining other types of hospital infection (OR=4.874, P<0.001) were independent risk factors for the development of VAP. VAP was the independent risk factor for both length of stay in the ICU and length of mechanical ventilation (P<0.001), but it was not the independent risk factor for mortality in the ICU (P=0.515). ConclusionThe applicability of the newly defined ventilator-associated pneumonia may be under restrictions in developing countries. It may influence the outcomes of patients by prolonging the length of stay in ICU and the length of mechanical ventilation.
Objective To investigate on the epidemiologic characteristics of nosocomial infection in surgery departments of general hospitals by analyzing the data collected from documents which were published in recent years, so as to provide references for the construction of precautionary system model. Methods Applying comprehensive search strategies, we searched various electronic databases as CBM (1978 to 2008), CNKI (1912 to 2008), VIP (2001 to 2009) and WanFang Data (2001 to 2009). MeSH terms and/or text words included: nosocomial infections, cross infection, hospital infection, prevent and control. Data from top and second grade hospital were included in this analysis. Results Sixty four articles and a total of 1 990 929 inpatients were included. Results showed: average nosocomial infection rate was 4.46%; the total rates of medicine department and surgery department were 23.28% and 17.33% respectively and no significant difference was found between the two departments; the infection rates of G– and G+ germ were 47.71% and 21.31% respectively; the rates of average antibiotics use was 60.59% and the rate of missing report was 12.42%. Noscomial infection was related to season change and the wave peak was from February to May. Conclusion Most of the included studies were retrospective studies and cross-sectional studies. The type of data was inconsistency and incomplete, causing weak strength of evidence. High missing rate of reports makes the precautionary model hard to build in future.
Objective To compare the epidemic status of nosocomial infections (NIs) among medical institutions at different levels. Methods The cross-sectional surveys on prevalence rates of NIs, distribution of NIs, and antimicrobial use were conducted through combination of bedside investigation and medical record reviewing among all in-patients of 20 medical institutions in Baoshan District, Shanghai from 00:01 to 24:00 on November 12th 2014, December 9th 2015, and November 30th 2016, respectively. Results A total of 18 762 patients were investigated, the prevalence rate of NIs in the first, second, and third class hospitals were 5.36%, 2.37%, 1.68%, respectively (χ2=88.497, P<0.05). The main NIs sites were lower respiratory tract, urinary tract, and upper respiratory tract in the first and second grade hospitals; while were other unclassified sites, respiratory tract, and upper respiratory tract in the third grade hospitals. The utilization rates for antimicrobial in the first, second, and third grade hospitals were 5.88%, 31.64%, and 42.11%, respectively (χ2=928.148, P<0.05); submission rates for specimen were 9.82%, 48.89%, and 82.39%, respectively (χ2=601.347, P<0.05). Four cases of pathogen were reported in the first grade hospitals, 94 in the second grade hospitals, and 96 in the third grade hospitals. The in-patients in different hospitals with different genders, ages, and departments had a statistical difference in prevalence rate of NIs (P<0.05) . Conclusion The first grade hospitals need to enhance the etiological examination; the third grade hospitals should severely restrict the antimicrobial utilization, and refine the prevention and control work for NIs.
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 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 investigate nosocomial infection rate in Intensive Care Unit (ICU), its risk factors and the pathogenic characteristics of multidrug-resistant bacteria through targeted monitoring, in order to provide scientific references for reducing nosocomial infection. Methods Targeted monitoring was performed on the patients who were admitted to the comprehensive ICU between July 2014 and June 2016. Results Nosocomial infection occurred in 312 of the 4 991 patients. The case infection rate was 6.25%, and case infection rate per day was 19.03‰. After the adjustment, the case infection rate per day was 6.77‰. The ventilator-associated pneumonia infection accounted for 30.78‰; catheter-related bloodstream infection occupied 0.30‰; and catheter-associated urinary tract infection accounted for 0.27‰. The respiratory tract was the major part of nosocomial infection, accounting for 90.38%. Gram-negative bacilli were the major bacteria accounting for 92.74%, in whichAcinetobacter baumannii accounted for 36.29%. Conclusions Through targeted monitoring to keep abreast of the current situation of nosocomial infection in ICU, management and interventions can be targeted. It is an important way to reduce nosocomial infection in ICU.
Objective To understand the effect of World Health Organization(WHO) multimodal hand hygiene improvement strategy on hand hygiene compliance among acupuncturists. Methods All the acupuncturists in departments (Department of Acupuncture, Department of Encephalopathy, Department of Orthopedics and Traumatology) with acupuncture programs in Xi’an Hospital of TCM were chosen in this study between September 2015 and August 2016. Based on the WHO multimodal hand hygiene improvement strategy, comprehensive measures were regulated among acupuncturists. Hand hygiene compliance and accuracy, and hand hygiene knowledge score were compared before and after the strategy intervention. Then, the effects of key strategies were evaluated. Results Overall hand hygiene compliance rate, accuracy and knowledge scores increased from 51.07%, 19.86% and 81.90±2.86 before intervention to 72.34%, 51.70%, and 98.62±2.92 after intervention (P<0.05). Hand hygiene compliance rates also increased in various occasions such as before contacting the patient, after contacting the patient, before acupuncture treatment, and before acupuncture needle manipulation (P<0.05). Conclusion Hand hygiene compliance in acupuncturists can be significantly improved by the implementation of WHO multimodal hand hygiene improvement strategy.
Objective To know the status quo of multidrug-resistant organism (MDRO) infection in primary general hospitals, analyze the differences among various intervention measures, and put forward guiding principles for MDRO infection control in primary general hospitals. Methods We investigated all patients (n=51 612) admitted into the hospital between January 2013 and December 2015, and found out 6 types of MDRO. Pre-interventional investigation was carried out between January 2013 and June 2014 (before intervention) during which no intervention measures were taken; Intervention was carried out between July 2014 and December 2015 (after intervention). All departments in the hospital (6 groups) were matched with intervention measures (6 groups) randomly. Then, we compared the MDRO detection rate, nosocomial infection case rate and intervention compliance rate among the groups. Results We detected altogether 611 MDRO cases (without duplication) out of the 51 612 cases. The total detection rate of MDRO was 1.18%. The detection rate of MDRO before and after intervention was 1.37% and 1.01%, respectively. The difference between the two was of statistical significance (P<0.05). After the intervention, the detection rate in groups 1, 5 and 6 was significantly lower than before (P<0.05); the differences in detection rate among groups 2, 3, and 4 were not significant (P> 0.05). Nosocomial infection rate decreased from 0.28% before intervention to 0.14% after intervention (P<0.05). After the intervention, MDRO nosocomial infection case rate of groups 1, 5 and 6 was significantly lower than before (P<0.05); the rate was lower in groups 3 and 4 than before without any significance (P>0.05); no MDRO cases were detected in group 2 and comparison was meaningless. The knowledge rates of medical workers and of nursing staff increased from 52.97% and 20.00% before intervention to 78.76% and 66.34% after intervention, respectively (χ2=30.670, 38.604;P<0.05). The compliance to all kinds of protection measures improved significantly (P<0.05) except compliances to equipment of hand antiseptic agent and patient transfer order (P> 0.05). Conclusion Promoting the compliance rate to hand hygiene and environmental cleaning and disinfection, primary general hospitals can decrease the detection rate and nosocomial infection case rate of MDRO.