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1.
Chinese Journal of Practical Nursing ; (36): 2775-2779, 2016.
Article in Chinese | WPRIM | ID: wpr-509013

ABSTRACT

Objective To understand the status of implementation of invasive ventilator circuit changes in ICU nurses at the 3A general hospitals in Shanxi Province, and mastering and demand of related knowledge of ICU nurses, and by this discuss the possible causes of execution inconsistency in invasive ventilator circuit changes interval so as to provide a clear basis for the specification and circuit changes. Methods After a review of relevant literature at home and abroad as well as expert consultation, a self-designed questionnaire was established, take two ways of on-site issuance and mailing, ICU nurses from 13 hospitals were selected randomly to investigate about the invasive circuit changes interval in Shanxi Province. Results A total of 724 nurses from 34 ICU of 13 hospitals were surveyed. A unified circuit changes interval of ICU accounted for 73.5% (527/717). ICU nurses currently provisions and practical implementation of invasive ventilator circuit changes interval tend to 7 d. Different ICU provisions and ICU nurses actual implementation of circuit change were significantly different (χ2=24.839, 35.760, P < 0.01). Conclusions Hospitals should choose the right way to strengthen the ICU nurses invasive ventilator circuit changes training interval and knowledge, to develop the term for their own security environment, thereby reduce the workload of nurses, reduce medical costs and improve care service quality.

2.
Chinese Journal of Infection Control ; (4): 939-941, 2016.
Article in Chinese | WPRIM | ID: wpr-508567

ABSTRACT

Objective To explore characteristics and risk factors for surgical site infection(SSI)in patients in the department of neurosurgery,so as to provide theoretical basis for prevention and control of SSI.Methods Clinical data of patients who were admitted to a department of neurosurgery from January to December 2015 were collected with retrospective survey method,SSI and risk factors in patients were analyzed.Results Among 715 patients un-dergoing neurosurgery,40(5.59% )had SSI. SSI mainly occurred in patients following cerebral vascular surgery, accounting for 7 .69% ,followed by patients following intracranial tumor surgery(5 .94% ). 40 patients were all with organ space/intracranial infection. Difference in SSI in patients with different types of operation,duration of opera-tion,length of hospital stay,and National Nosocomial Infections Surveillance (NNIS)scores were all significant(all P<0.05).Conclusion Incidence of SSI in patients in the department of neurosurgery are related with operation type,duration of operation,length of hospital stay,and operation risk index,preventive measures should be taken to reduce the incidence of SSI.

3.
Chinese Journal of Infection Control ; (4): 730-734, 2016.
Article in Chinese | WPRIM | ID: wpr-503092

ABSTRACT

Objective To construct the risk model for healthcare-associated infection (HAI)with multidrug-re-sistant organisms(MDROs)in intensive care unit (ICU).Methods 836 patients who were admitted to ICU for more than 48 hours between October 2012 and September 2015 were analyzed retrospectively,logistic regression model of HAI was constructed,the model was conducted goodness of fit tests and the area under ROC curve analysis. Results Among 836 patients,incidence of HAI with MDROs was 14.23%(n=119).15 variables that were statis-tically significant in univariate analysis were included in logistic multivariate analysis,the results showed that the following variables entered into logistic regression equation:length of ICU stay (OR,2.493 [95%CI ,1 .816 -3.494]),underlying diseases (OR,1 .536 [95%CI ,1 .243 - 1 .898 ]),hypoproteinemia (OR,87.211 [95%CI , 36.165-210.304]),ventilator days (OR,1 .723 [95%CI ,1 .399-2.121 ]),fever(OR,20.639 [95%CI ,3.462 -123.043]),and primary pulmonary infection (OR,0.295 [95%CI ,0.133 -0.664]).Evaluation of model effect:sensitivity 95%,specificity 87.9%,the area under ROC curve 0.973.Conclusion Logistic regression model has a high goodness of fit in predicting HAI among ICU patients.

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