Exclusion of bacterial co-infection in COVID-19 using baseline inflammatory markers and their response to antibiotics
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Abstract
Background
COVID-19 is infrequently complicated by bacterial co-infection, but antibiotic prescriptions are common. We used community-acquired pneumonia (CAP) as a benchmark to define the processes that occur in bacterial pulmonary infections, testing the hypothesis that baseline inflammatory markers and their response to antibiotic therapy could distinguish bacterial co-infection from COVID-19.
Methods
Retrospective cohort study of CAP (lobar consolidation on chest radiograph) and COVID-19 (PCR detection of SARS-CoV-2) patients admitted to Royal Free Hospital (RFH) and Barnet Hospital (BH), serving as independent discovery and validation cohorts. All CAP and >90% COVID-19 patients received antibiotics on hospital admission.
Results
We identified 106 CAP and 619 COVID-19 patients at RFH. Compared with COVID-19, CAP was characterized by elevated baseline white cell count (WCC) [median 12.48 (IQR 8.2–15.3) versus 6.78 (IQR 5.2–9.5) ×106 cells/mL, P < 0.0001], C-reactive protein (CRP) [median 133.5 (IQR 65–221) versus 86.0 (IQR 42–160) mg/L, P < 0.0001], and greater reduction in CRP 48–72 h into admission [median ΔCRP −33 (IQR −112 to +3.5) versus +14 (IQR −15.5 to +70.5) mg/L, P < 0.0001]. These observations were recapitulated in the independent validation cohort at BH (169 CAP and 181 COVID-19 patients). A multivariate logistic regression model incorporating WCC and ΔCRP discriminated CAP from COVID-19 with AUC 0.88 (95% CI 0.83–0.94). Baseline WCC >8.2 × 106 cells/mL or falling CRP identified 94% of CAP cases, and excluded bacterial co-infection in 46% of COVID-19 patients.
Conclusions
We propose that in COVID-19, absence of both elevated baseline WCC and antibiotic-related decrease in CRP can exclude bacterial co-infection and facilitate antibiotic stewardship efforts.
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SciScore for 10.1101/2020.10.09.20199778: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
Software and Algorithms Sentences Resources All analyses were performed using Microsoft Excel and GraphPad Prism version 8. Microsoft Excelsuggested: (Microsoft Excel, RRID:SCR_016137)GraphPad Prismsuggested: (GraphPad Prism, RRID:SCR_002798)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: We detected the following sentences addressing limitations in the study:Our study has …
SciScore for 10.1101/2020.10.09.20199778: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
Software and Algorithms Sentences Resources All analyses were performed using Microsoft Excel and GraphPad Prism version 8. Microsoft Excelsuggested: (Microsoft Excel, RRID:SCR_016137)GraphPad Prismsuggested: (GraphPad Prism, RRID:SCR_002798)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: We detected the following sentences addressing limitations in the study:Our study has some notable limitations. First, the populations were identified at non-overlapping times, due to the disproportionate prevalence of COVID-19 cases in 2020. We attempted to mitigate for the enforced use of historical pneumonia and influenza comparator groups by identifying these patients over the same months of 2019 as COVID-19 cases in 2020. We also did not collect clinical severity or outcome data for the patients, and thus we cannot measure a direct impact on prognosis. Second, we used a radiological, but not microbiological, definition of pneumonia, and although standardised, it is possible that some pneumonia cases had non-bacterial aetiology. Third, we inferred that bacterial co-infection in COVID-19 shares pathophysiology and inflammatory marker responses with CAP in the absence of COVID-19. This hypothesis remains untested but is supported by the divergent inflammatory marker responses observed between most COVID-19 and CAP patients. Fourth, we did not include suspected COVID-19 patients with negative SARS-CoV-2 results, therefore our findings may not be applicable to this cohort. Finally, we focused on patient assessments made within 72 hours of admission, and thus our decision-making tools are not applicable to patients discharged before this time or those with prolonged hospital admissions. In conclusion, we demonstrate that routine clinical parameters, admission WCC and changes in CRP following antibiotic administration, can be translated into a set ...
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.
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