Cross-sectional investigation of nosocomial infection in a tertiary general hospital and construction of a prediction model
10.3969/j.issn.1006-2483.2021.05.013
- VernacularTitle:某三级综合医院医院感染横断面调查及预测模型构建
- Author:
Meixia WANG
1
;
Hongfei MI
1
;
Xiaodong GAO
2
;
Bijie HU
2
,
3
;
Yu PAN
1
,
3
Author Information
1. Nomination Management Department , Xiamen Branch , Zhongshan Hospital , Fudan University , Xiamen , Fujian 361015 , China
2. Fudan University Zhongshan Hospital, Department of Healthcare-associated Infection Management, Shanghai 200032 , China
3. Fudan University Zhongshan Hospital, Department of Infectious Diseases, Shanghai 200032 , China
- Publication Type:Journal Article
- Keywords:
Nosocomial infection;
Prevalence rate;
Nomorgram
- From:
Journal of Public Health and Preventive Medicine
2021;32(5):56-60
- CountryChina
- Language:Chinese
-
Abstract:
Objective To understand the prevalence of nosocomial infection and its potential risk factors through a cross-sectional study, to construct a predictive model of the probability of nosocomial infection, and to provide a basis for nosocomial infection management. Methods The prevalence rate of nosocomial infection and potential risk factors of all inpatients in a tertiary general hospital were investigated on a certain day. The possible risk factors of nosocomial infection were analyzed, and a nomogram prediction model on the probability of nosocomial infection was established. The calibration curve and ROC curve were used to evaluate the predictive efficiency of the model. Results A total of 419 hospitalized patients were investigated, and the prevalence rate of nosocomial infection was 3.58%. The top three nosocomial infections were in ICU, neurosurgery, and cardiac surgery. The top three infection sites were surgical site infections, lower respiratory tract infections, and urinary tract infections. The results of univariate analysis showed that the length of hospital stay, surgery, antimicrobial use and underlying diseases were statistically related to the occurrence of nosocomial infections (all P<0.05). Logistic regression analysis showed that compared with the length of stay (LOS)＜14, the risk of nosocomial infection in patients with long LOS (≥14) was 5.48 (95% CI: 1.68-19.16). The risk of nosocomial infection in patients with two basic diseases was 7.61 times that (95%CI: 1.50-44.79) of patients without underlying diseases. The risk of nosocomial infection in patients with surgery was 4.88 times that of patients without surgery (95%CI: 1.47-19.6). According to the coefficients of the related risk factors calculated by logistic regression, a nomogram model of the occurrence probability of nosocomial infection was established. The C-index of the model was 0.839, and the area under the ROC curve for predictive efficiency was 0.809 (95%CI: 0.740-0.942). Conclusion Nosocomial infection control and management should be strengthened. Individual risk assessment of patients' nosocomial infection should consider about the age, underlying diseases, surgical status, glucocorticoid or immunosuppressive agents, and antimicrobial drug use. It is essential to identify the high-risk groups as soon as possible and take prevention and control measures to reduce the prevalence rate of nosocomial infection.
