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Multidrug-resistant organisms in intensive care units and logistic analysis of risk factors.
Han, Ying; Zhang, Jin; Zhang, Hong-Ze; Zhang, Xin-Ying; Wang, Ya-Mei.
Afiliación
  • Han Y; Infection Control Office, Affiliated Hospital of Hebei University, Baoding 071000, Hebei Province, China.
  • Zhang J; Infection Control Office, Affiliated Hospital of Hebei University, Baoding 071000, Hebei Province, China. hanyingsci@126.com.
  • Zhang HZ; Infection Control Office, Affiliated Hospital of Hebei University, Baoding 071000, Hebei Province, China.
  • Zhang XY; Infection Control Office, Affiliated Hospital of Hebei University, Baoding 071000, Hebei Province, China.
  • Wang YM; Infection Control Office, Affiliated Hospital of Hebei University, Baoding 071000, Hebei Province, China.
World J Clin Cases ; 10(6): 1795-1805, 2022 Feb 26.
Article en En | MEDLINE | ID: mdl-35317164
BACKGROUND: Intensive care unit (ICU) patients are critically ill and have low immunity. They will undergo various trauma medical procedures during diagnosis and treatment. The use of high-dose hormones and broad-spectrum antibiotics will increase the incidence of nosocomial infection in ICU patients. Therefore, it is necessary to explore the causes of nosocomial infection in ICU and provide basis for the prevention and control of nosocomial infection in ICU. AIM: To explore major pathogens of nosocomial infection in ICUs, methods of detection and drug resistance trends. METHODS: Risk factors of multidrug-resistant infection were analyzed to provide a basis for clinical rational use of antimicrobial drugs in the ICU. These findings were used to standardize rational use of antimicrobial agents. BD PhoenixTM100 automatic bacterial identification analyzer was used to for cell identification in specimens collected from the ICU between January 2016 and December 2019. Drug sensitivity tests were carried out and drug resistance trends were analyzed using the optical disc diffusion method. Odds ratios and corresponding 95%CI of independent variables were calculated using a logistic regression model. Backward elimination (trend = 0.1) was used as an inclusion criterion for multivariate analysis. All data were analyzed using SPSS version 22.0, and P < 0.05 was considered statistically significant. RESULTS: We collected 2070 samples from ICU patients between January 2016 and December 2019. Sample types comprised sputum (1139 strains, 55.02%), blood (521 strains, 25.17%), and drainage fluid (117 strains, 5.65%). A total of 1051 strains of major pathogens, including Acinetobacter baumannii, Escherichia coli (E. coli), Pseudomonas aeruginosa (P. aeruginosa), Klebsiella pneumoniae (K. pneumoniae) and Staphylococcus aureus, were detected, with a detection rate of 35.97% (378/1051). Most of these strains were resistant to antibiotics. Detection rate of E. coli was 21.79% (229/1051), and it was generally sensitive to many antimicrobial drugs. Detection rate of P. aeruginosa was 24.74% (260/1051), and showed low sensitivity to most antibiotics. Detection rate of K. pneumoniae was 9.42% (99/1051), which was generally resistant to multiple antimicrobial drugs and resistant forms. K. pneumoniae was resistant to imipenem for approximate 4 years, and showed a 19.9% (19/99) and 20.20% (20/99) rate of meropenem resistance. Logistic analysis showed that mechanical ventilation and ureteral intubation were risk factors for multidrug-resistant bacterial infections. CONCLUSION: This study showed a high incidence of ICU infections. Mechanical ventilation and urine tube intubation were risk factors for infection with multidrug-resistant bacteria.
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Texto completo: 1 Base de datos: MEDLINE Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: World J Clin Cases Año: 2022 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Base de datos: MEDLINE Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: World J Clin Cases Año: 2022 Tipo del documento: Article País de afiliación: China