Increased Serum Thromboxane A2 and Prostacyclin but Lower Complement C3 and C4 Levels in COVID-19: Associations with Chest CT Scan Anomalies and Lowered Peripheral Oxygen Saturation

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Abstract

COVID-19 patients suffer from hypercoagulation and activated immune-inflammatory pathways. The current study examined the relationship between specific complements and coagulation abnormalities associated with chest CT scan anomalies (CCTAs) and peripheral oxygen saturation (SpO2) in COVID-19 patients. Serum levels of complement C3 and C4, and thromboxane A2 (TxA2) and prostacyclin (PGI2) were measured using an ELISA and albumin, calcium, and magnesium by using the spectrophotometric method in 60 COVID-19 patients and 30 controls. C3 and C4 were significantly decreased (p < 0.001), and TxA2 and PGI2 significantly increased (p < 0.001) in the COVID-19 patients compared with the controls with the highest levels in the CCTA patients’ group. Neural networks showed that a combination of C3, albumin, and TxA2 yielded a predictive accuracy of 100% in detecting COVID-19 patients. SpO2 was significantly decreased in the COVID-19 patients and was inversely associated with TxA2 and PGI2, and positively with C3, C4, albumin, and calcium. Patients with positive IgG results show significantly higher SpO2, TxA2, PGI2, and C4 levels than IgG-negative patients. CCTAs were accompanied by lower SpO2 and albumin and increased PGI2 and TxA2 levels, suggesting that interactions between immune-inflammatory pathways and platelet hyperactivity participate in the pathophysiology of COVID-19 and, consequently, may play a role in an enhanced risk of hypercoagulability and venous thromboembolism. These mechanisms are aggravated by lowered calcium and magnesium levels.

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  1. SciScore for 10.1101/2021.04.10.21255240: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: All controls and patients gave written informed consent before participation in this study.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    IBM SPSS windows version 25, 2017 was used for all statistical analysis.
    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.

    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.