Bacterial coinfections in COVID: Prevalence, antibiotic sensitivity patterns and clinical outcomes from a tertiary institute of Northern India

  1. Chinmoy Sahu
  2. Sweta Singh
  3. Ashutosh Pathak
  4. Sanjay Singh
  5. Sangram Singh Patel
  6. Ujjala Ghoshal
  7. Atul Garg

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Abstract

Bacterial coinfections are a leading cause of morbidity and mortality during viral infections including corona virus disease (COVID-19). The COVID-19 pandemic has highlighted the need to comprehend the complex connection between bacterial and viral infections. During the current pandemic, systematic testing of the COVID-19 patients having bacterial coinfections is essential to choose the correct antibiotics for treatment and prevent the spread of antimicrobial resistance (AMR). This study was planned to study the prevalence, demographic parameters, comorbidities, antibiotic sensitivity patterns, and outcomes in hospitalized COVID-19 patients with bacterial coinfections.

Material and Methods:

The COVID-19 patients having bacterial coinfections were selected for the study and analyzed for the prevalence, antibiotic sensitivities, comorbidities, and clinical outcomes. The bacterial isolates were identified and the antibiotic susceptibility testing was performed according to the Clinical and Laboratory Standards Institute (CLSI) guidelines.

Results:

Of the total 1,019 COVID-19 patients screened, 5.2% ( n = 53) demonstrated clinical signs of bacterial coinfection. Escherichia coli were the most common isolate followed by Pseudomonas aeruginosa and Klebsiella spp . among the gram-negative bacterial infections. Coagulase-negative Staphylococcus species (CONS) and Staphylococcus aureus were most common among the gram-positive bacterial infections. The antibiotic sensitivity profiling revealed that colistin (99%), imipenem (78%), and fosfomycin (95%) were the most effective drugs against the gram-negative isolates while vancomycin (100%), teicoplanin (99%), and doxycycline (71%) were most potent against the gram-positive isolates. The analysis of the clinical parameters and outcomes revealed that among the COVID-19 patients with bacterial coinfections, the mortality rate was higher (39%) than the control group (17%) ( P -value < 0.001).

Conclusion:

This study reveals the significantly increased rates of bacterial coinfections among COVID-19 patients which may lead to an increase in mortality. This study will guide the physicians at the primary level on the rational and correct usage of antibiotics in such COVID cases. Hence, systematic testing of COVID-19 patients with bacterial coinfections is the need of the hour to decrease the mortality rate and limit the spread of AMR.

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  1. Version published to 10.4103/jfmpc.jfmpc_41_22
  2. ScreenIT

    SciScore for 10.1101/2021.08.06.21261695: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Statistical Analysis: The results were analyzed using the SPSS version 22 software (SPSS Inc., Chicago, IL, USA).
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2021.08.06.21261695v1 on medRxiv