Hypoferremia is Associated With Increased Hospitalization and Oxygen Demand in COVID‐19 Patients

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Abstract

Iron metabolism might play a crucial role in cytokine release syndrome in COVID‐19 patients. Therefore, we assessed iron metabolism markers in COVID‐19 patients for their ability to predict disease severity. COVID‐19 patients referred to the Heidelberg University Hospital were retrospectively analyzed. Patients were divided into outpatients (cohort A, n = 204), inpatients (cohort B, n = 81), and outpatients later admitted to hospital because of health deterioration (cohort C, n = 23). Iron metabolism parameters were severely altered in patients of cohort B and C compared to cohort A. In multivariate regression analysis including age, gender, CRP and iron‐related parameters only serum iron and ferritin were significantly associated with hospitalization. ROC analysis revealed an AUC for serum iron of 0.894 and an iron concentration <6 μmol/l as the best cutoff‐point predicting hospitalization with a sensitivity of 94.7% and a specificity of 67.9%. When stratifying inpatients in a low‐ and high oxygen demand group serum iron levels differed significantly between these two groups and showed a high negative correlation with the inflammatory parameters IL‐6, procalcitonin, and CRP. Unexpectedly, serum iron levels poorly correlate with hepcidin. We conclude that measurement of serum iron can help predicting the severity of COVID‐19. The differences in serum iron availability observed between the low and high oxygen demand group suggest that disturbed iron metabolism likely plays a causal role in the pathophysiology leading to lung injury.

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  1. SciScore for 10.1101/2020.06.26.20140525: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Data analysis was approved (number S-148/2020) by the Ethics Committee of the Medical Faculty Heidelberg.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Data collection and analyses were performed using SPSS 21 (IBM Corp. Armonk, NY, USA) or with GraphPad prism 8 (GraphPad Software, San Diego, CA, USA).
    SPSS
    suggested: (SPSS, RRID:SCR_002865)
    GraphPad
    suggested: (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: 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.
    • Thank you for including a protocol registration statement.

    About SciScore

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