Changes in the clinical distribution and antibiotic resistance of Klebsiella pneumoniae in a tertiary hospital before and after the COVID-19 pandemic

Abstract Background The widespread use of broad-spectrum antibiotics and adjustments in hospital infection control measures during the COVID-19 pandemic may have reshaped the epidemiological characteristics and resistance patterns of Klebsiella pneumoniae (KP). Currently, there are limited longitudinal data on the distribution and the dynamic resistance profiles of KP in Chinese tertiary hospitals across different phases of the pandemic. Therefore, this study aimed to analyze these changes to advance antibiotic stewardship and hospital infection control. Methods KP strains isolated from clinical specimens at a tertiary hospital in Chongqing were analyzed for three periods: 2017–2019 (pre‑pandemic), 2020–2022 (mid‑pandemic), and 2023–2025 (post‑pandemic). We focused on the epidemiological profile and changes in the antibiotic resistance of KP. Data were analyzed using GraphPad Prism 10.1.2 and WHONET 5.6 software. Results In total, 883 KP strains were isolated, accounting for 20.8% of Gram-negative bacteria during the same period. The isolation rate of KP significantly increased in the post-pandemic phase (P < 0.05). The isolation rates of carbapenem-resistant KP (CRKP) were 3.0%, 12.2%, and 5.0% in the pre-pandemic, mid-pandemic, and post-pandemic periods, respectively, showing significant differences (P < 0.05). The isolation rates of extensively drug-resistant KP (XDR-KP) were 2.4%, 8.3%, and 4.7% in the pre-pandemic, mid-pandemic, and post-pandemic periods, respectively. The top three sources of specimens were sputum (75.5%), secretions (7.8%), and urine (6.6%). The age distribution of patients with CRKP and carbapenem-susceptible KP (CSKP) showed a significant difference (P < 0.05). The resistance rates of KP to various antibiotics increased during the mid-pandemic phase and declined in the post-pandemic phase. Compared to the pre-pandemic phase, the imipenem resistance rate increased more than threefold in the mid-pandemic phase, and then decreased in the post-pandemic phase. There were significant changes in the resistance rates of KP to ceftazidime, cefepime, ciprofloxacin, imipenem, and trimethoprim-sulfamethoxazole (P < 0.05). Conclusion The transition from the COVID-19 pandemic was closely associated with changes in the isolation rate and drug resistance of KP. Hospitals should continuously monitor high-risk populations and key prevention and control points to guide rational clinical drug use and the prevention and control of multidrug-resistant bacteria.

Authors

Institutions

Publication Details

Journal
BMC Infectious Diseases
Published
2026-08-20
DOI
https://doi.org/10.1186/s12879-026-14277-4
Primary Topic
Antibiotic Use and Resistance
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Changes in the clinical distribution and antibiotic resistance of Klebsiella pneumoniae in a tertiary hospital before and after the COVID-19 pandemic

Yan Yang, Chunyan Long, Ling Zhang, Guoqun Tan et al.
BMC Infectious Diseases
Antibiotic Use and Resistance
article

Changes in the clinical distribution and antibiotic resistance of Klebsiella pneumoniae in a tertiary hospital before and after the COVID-19 pandemic

Yan Yang, Chunyan Long, Ling Zhang, Guoqun Tan, Ye He, Tao Huang, Yang Liu, Zailiang Yang
article en

Abstract

Abstract Background The widespread use of broad-spectrum antibiotics and adjustments in hospital infection control measures during the COVID-19 pandemic may have reshaped the epidemiological characteristics and resistance patterns of Klebsiella pneumoniae (KP). Currently, there are limited longitudinal data on the distribution and the dynamic resistance profiles of KP in Chinese tertiary hospitals across different phases of the pandemic. Therefore, this study aimed to analyze these changes to advance antibiotic stewardship and hospital infection control. Methods KP strains isolated from clinical specimens at a tertiary hospital in Chongqing were analyzed for three periods: 2017–2019 (pre‑pandemic), 2020–2022 (mid‑pandemic), and 2023–2025 (post‑pandemic). We focused on the epidemiological profile and changes in the antibiotic resistance of KP. Data were analyzed using GraphPad Prism 10.1.2 and WHONET 5.6 software. Results In total, 883 KP strains were isolated, accounting for 20.8% of Gram-negative bacteria during the same period. The isolation rate of KP significantly increased in the post-pandemic phase (P < 0.05). The isolation rates of carbapenem-resistant KP (CRKP) were 3.0%, 12.2%, and 5.0% in the pre-pandemic, mid-pandemic, and post-pandemic periods, respectively, showing significant differences (P < 0.05). The isolation rates of extensively drug-resistant KP (XDR-KP) were 2.4%, 8.3%, and 4.7% in the pre-pandemic, mid-pandemic, and post-pandemic periods, respectively. The top three sources of specimens were sputum (75.5%), secretions (7.8%), and urine (6.6%). The age distribution of patients with CRKP and carbapenem-susceptible KP (CSKP) showed a significant difference (P < 0.05). The resistance rates of KP to various antibiotics increased during the mid-pandemic phase and declined in the post-pandemic phase. Compared to the pre-pandemic phase, the imipenem resistance rate increased more than threefold in the mid-pandemic phase, and then decreased in the post-pandemic phase. There were significant changes in the resistance rates of KP to ceftazidime, cefepime, ciprofloxacin, imipenem, and trimethoprim-sulfamethoxazole (P < 0.05). Conclusion The transition from the COVID-19 pandemic was closely associated with changes in the isolation rate and drug resistance of KP. Hospitals should continuously monitor high-risk populations and key prevention and control points to guide rational clinical drug use and the prevention and control of multidrug-resistant bacteria.

BMC Infectious Diseases
Taihe Hospital (CN), Fuling Center Hospital of Chongqing (CN)
Good health and well-being
Openalex Percentile: Top 9%
Antibiotic Use and Resistance
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.