Can Cycle Threshold Value of RT-PCR for SARS-CoV-2 Predict Secondary Bacterial Infections in Patients with Coronavirus Disease?

Objectives: This study aims to investigate the relationship between cycle threshold (Ct) values of RT-PCR for SARS-CoV-2, as a marker of viral load, and the occurrence of secondary bacterial infections in hospitalized COVID-19 patients. Methods: A cross-sectional study was conducted among 141 COVID-19 patients at Sukraraj Tropical and Infectious Disease Hospital, Nepal, between July 2022 and June 2023. Bacterial cultures were performed for hospitalized patients. Ct values for SARS-CoV-2 N and Orf 1ab genes were compared between patients with and without secondary bacterial infections. Results: Out of 32 hospitalized patients, 11 (34.37%) had secondary bacterial infections. The median Ct values of the N gene were slightly lower in patients with secondary bacterial infections (19.5) compared to those without (19.0), though this difference was not statistically significant (p = 0.2113). Similar trends were observed for the Orf1ab gene (20.5 vs. 19.5; p = 0.3125). The most frequently isolated bacterial pathogen was Klebsiella pneumoniae, while Acinetobacter baumanii and E. coli were associated with the lowest Ct values. Conclusion: While patients with secondary bacterial infections tended to have lower Ct values, no statistically significant relationship was observed between Ct values and the occurrence of secondary bacterial infections. However, Ct values might still provide supplementary insights into disease severity and the risk of secondary infections.

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Publication Details

Journal
Tribhuvan University Journal of Microbiology
Published
2024-12-31
DOI
https://doi.org/10.3126/tujm.v11i1.81364
Primary Topic
COVID-19 diagnosis using AI
Type
article
Field-Weighted Citation Impact
0.00

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article

Can Cycle Threshold Value of RT-PCR for SARS-CoV-2 Predict Secondary Bacterial Infections in Patients with Coronavirus Disease?

Bimal Sharma Chalise, Komal Raj Rijal, Suprina Sharma, Sunil Regmi et al.
Tribhuvan University Journal of Microbiology
COVID-19 diagnosis using AI
article

Can Cycle Threshold Value of RT-PCR for SARS-CoV-2 Predict Secondary Bacterial Infections in Patients with Coronavirus Disease?

Bimal Sharma Chalise, Komal Raj Rijal, Suprina Sharma, Sunil Regmi, Krishna Gurung, Ramesh Prasad Sapkota, Jiwan Thapa, Supriya Sharma, Sanjib Adhikari, Shreedhar Aryal, Prakash Ghimire, Pramod Poudel
article en

Abstract

Objectives: This study aims to investigate the relationship between cycle threshold (Ct) values of RT-PCR for SARS-CoV-2, as a marker of viral load, and the occurrence of secondary bacterial infections in hospitalized COVID-19 patients. Methods: A cross-sectional study was conducted among 141 COVID-19 patients at Sukraraj Tropical and Infectious Disease Hospital, Nepal, between July 2022 and June 2023. Bacterial cultures were performed for hospitalized patients. Ct values for SARS-CoV-2 N and Orf 1ab genes were compared between patients with and without secondary bacterial infections. Results: Out of 32 hospitalized patients, 11 (34.37%) had secondary bacterial infections. The median Ct values of the N gene were slightly lower in patients with secondary bacterial infections (19.5) compared to those without (19.0), though this difference was not statistically significant (p = 0.2113). Similar trends were observed for the Orf1ab gene (20.5 vs. 19.5; p = 0.3125). The most frequently isolated bacterial pathogen was Klebsiella pneumoniae, while Acinetobacter baumanii and E. coli were associated with the lowest Ct values. Conclusion: While patients with secondary bacterial infections tended to have lower Ct values, no statistically significant relationship was observed between Ct values and the occurrence of secondary bacterial infections. However, Ct values might still provide supplementary insights into disease severity and the risk of secondary infections.

Tribhuvan University Journal of MicrobiologyVol. 11(1)
Tribhuvan University (NP), Western Regional Hospital (NP), Sukraraj Tropical & Infectious Disease Hospital (NP), Bhaktapur Cancer Hospital (NP)
University Grants Commission
Openalex Percentile: Top 55%
COVID-19 diagnosis using AI
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