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. 2023 Feb 22;12(3):431.
doi: 10.3390/antibiotics12030431.

Epidemiological Characteristics and Antimicrobial Resistance Changes of Carbapenem-Resistant Klebsiella pneumoniae and Acinetobacter baumannii under the COVID-19 Outbreak: An Interrupted Time Series Analysis in a Large Teaching Hospital

Xinyi Yang  1 , Xu Liu  2 , Weibin Li  1 , Lin Shi  1 , Yingchao Zeng  1 , Haohai Xia  1 , Qixian Huang  1 , Jia Li  3 , Xiaojie Li  4 , Bo Hu  4 , Lianping Yang  1
Affiliations

Epidemiological Characteristics and Antimicrobial Resistance Changes of Carbapenem-Resistant Klebsiella pneumoniae and Acinetobacter baumannii under the COVID-19 Outbreak: An Interrupted Time Series Analysis in a Large Teaching Hospital

Xinyi Yang et al. Antibiotics (Basel). .

Abstract

Background: To investigate the epidemiological characteristics and resistance changes of carbapenem-resistant organisms (CROs) under the COVID-19 outbreak to provide evidence for precise prevention and control measures against hospital-acquired infections during the pandemic.

Methods: The distribution characteristics of CROs (i.e., carbapenem-resistant Klebsiella pneumoniae and Acinetobacter baumannii) were analyzed by collecting the results of the antibiotic susceptibility tests of diagnostic isolates from all patients. Using interrupted time series analysis, we applied Poisson and linear segmented regression models to evaluate the effects of COVID-19 on the numbers and drug resistance of CROs. We also conducted a stratified analysis using the Cochran-Mantel-Haenszel test.

Results: The resistance rate of carbapenem-resistant Acinetobacter baumannii (CRAB) was 38.73% higher after the COVID-19 outbreak compared with before (p < 0.05). In addition, the long-term effect indicated that the prevalence of CRAB had a decreasing trend (p < 0.05). However, the overall resistance rate of Klebsiella pneumoniae did not significantly change after the COVID-19 outbreak. Stratified analysis revealed that the carbapenem-resistant Klebsiella pneumoniae (CRKP) rate increased in females (OR = 1.98, p < 0.05), those over 65 years old (OR = 1.49, p < 0.05), those with sputum samples (OR = 1.40, p < 0.05), and those in the neurology group (OR = 2.14, p < 0.05).

Conclusion: The COVID-19 pandemic has affected the change in nosocomial infections and resistance rates in CROs, highlighting the need for hospitals to closely monitor CROs, especially in high-risk populations and clinical departments. It is possible that lower adherence to infection control in crowded wards and staffing shortages may have contributed to this trend during the COVID-19 pandemic, which warrants further research.

Keywords: COVID-19; antimicrobial resistance; interrupted time series; multidrug-resistant organisms; nosocomial infection.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Time trends of pathogens and drug-resistant bacteria. Data were collected on a biweekly basis. The dark red dashed line indicates the COVID-19 outbreak. The yellow line represents the proportion of the pathogen or resistance rate of the drug-resistant bacteria. The blue bars show the number of pathogenic or drug-resistant bacteria.
Figure 2
Figure 2
The change in outcome indicators every two weeks before and after COVID-19 outbreak. The dark blue dots represent the number (or resistance rate) before COVID-19 outbreak. The blue dots represent the number (or resistance rate) after COVID-19 outbreak. The dark blue dashed line represents the regression line before COVID-19 outbreak. The blue line represents the regression line after COVID-19 outbreak. Dark red dashed lines indicate breakpoints in the time series.
Figure 3
Figure 3
The change in CROs before and after COVID-19 in different subgroups. The sample size of outpatients was too small to be included in the stratified analysis. Abbreviations: sp, sputum; ur, urine; bl, blood; icu, intensive care unit; reh, rehabilitation center; neu, neurology.
See this image and copyright information in PMC

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