The significance of monitoring respiratory sample cultures and polymerase chain reaction tests for detecting bacterial pathogens in severely and critically ill patients with COVID-19 Article Swipe
YOU?
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· 2024
· Open Access
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· DOI: https://doi.org/10.7196/ajtccm.2024.v30i1.1293
Background. Bacterial superinfection is one of the most common and potentially lethal complications in severely and critically ill patients with COVID-19. Objectives. To determine the colonisation time frame and the spectrum of potential bacterial pathogens in respiratory samples from patients with severe and critical COVID-19, using routine culture and polymerase chain reaction (PCR) tests. Methods. A prospective observational study was conducted on patients aged ≥18 years with confirmed severe and critical COVID-19 who were admitted to or transferred to the intensive care unit (ICU). Respiratory samples were collected for microbial culture and PCR testing within the first 2 days after ICU admission/transfer, between days 3 and 6, and after 7 days of ICU stay. Results. A total of 82 patients, with a median (interquartile range) age of 74.5 (67.3 - 81.0) years and a median Charlson comorbidity index of 4 (3 - 5), were enrolled in the study. Colonisation with any pathogen was observed in 67% of patients, after a median of 4 (2 - 6) days in the ICU. On days 0 - 2 of the ICU stay, micro-organisms were detected in 18% of patients, with Klebsiella pneumoniae (without acquired antibiotic resistance) and methicillin-susceptible Staphylococcus aureus being most frequently identified. Later, Acinetobacter baumannii and carbapenem-resistant K. pneumoniae became the predominant micro-organisms, identified in nearly half of the patients. In 74% of the samples, the results of microbial culture and PCR tests were identical. In 17%, PCR revealed bacterial pathogens not identified by culture. Conclusion. Our study confirms that colonisation of the respiratory tract occurs early in the course of ICU stay. Superinfections are predominantly caused by multidrug-resistant Gram-negative bacteria.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.7196/ajtccm.2024.v30i1.1293
- https://samajournals.co.za/index.php/ajtccm/article/download/1293/840
- OA Status
- diamond
- References
- 24
- Related Works
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- OpenAlex ID
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4393987313Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.7196/ajtccm.2024.v30i1.1293Digital Object Identifier
- Title
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The significance of monitoring respiratory sample cultures and polymerase chain reaction tests for detecting bacterial pathogens in severely and critically ill patients with COVID-19Work title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
-
2024-04-04Full publication date if available
- Authors
-
Daria Strelkova, V.G. Kuleshov, E.N. Burmistrova, I. N. Sychev, Yu.A. Savochkina, DI Danilov, S. B. Yatsyshina, E.E. Glushchenko, M. A. Elkina, N. A. Ananicheva, A.S. Yasneva, S. V. Topolyanskaya, Svetlana RachinaList of authors in order
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https://doi.org/10.7196/ajtccm.2024.v30i1.1293Publisher landing page
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https://samajournals.co.za/index.php/ajtccm/article/download/1293/840Direct link to full text PDF
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YesWhether a free full text is available
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diamondOpen access status per OpenAlex
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https://samajournals.co.za/index.php/ajtccm/article/download/1293/840Direct OA link when available
- Concepts
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Interquartile range, Medicine, Acinetobacter baumannii, Intensive care unit, Internal medicine, Superinfection, Acinetobacter, Microbiological culture, Streptococcus pneumoniae, Intensive care, Microbiology, Antibiotics, Intensive care medicine, Biology, Pseudomonas aeruginosa, Virology, Bacteria, Virus, GeneticsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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24Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| citation_normalized_percentile.value | 0.05746644 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |