Preprint: Cytokine Hub Classification of PASC, ME-CFS and other PASC-like Conditions, Patterson et al, 2022

Discussion in 'Long Covid research' started by Kalliope, Apr 28, 2022.

  1. Kalliope

    Kalliope Senior Member (Voting Rights)

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    ABSTRACT

    Background: Post-acute sequelae of COVID-19 (PASC) is a growing healthcare and economic concern affecting as many as 10%-30% of those infected with COVID-19. Though the symptoms have been well-documented, they significantly overlap with other common chronic inflammatory conditions which could confound treatment and therapeutic trials.

    Methods: A total of 236 patients including 64 with post-acute sequelae of COVID-19 (PASC), 50 with myalgic encephalomyelitis-chronic fatigue syndrome (ME-CFS), 29 with post-treatment Lyme disease (PTLD), and 42 post-vaccine individuals with PASC- like symptoms (POVIP) were enrolled in the study. We performed a 14-plex cytokine/chemokine panel previously described to generate raw data that was normalized and run in a decision tree model using a Classification and Regression Tree (CART) algorithm. The algorithm was used to classify these conditions in distinct groups despite their similar symptoms.

    Results: PASC, ME-CSF, POVIP, and Acute COVID-19 disease categories were able to be classified by our cytokine hub based CART algorithm with an average F1 score of 0.61 and high specificity (94%).

    Conclusions: Proper classification of these inflammatory conditions with very similar symptoms is critical for proper diagnosis and treatment.

    https://static1.squarespace.com/sta...and+Other+PASC-like+Conditions+04-21-2022.pdf
     
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  2. Kalliope

    Kalliope Senior Member (Voting Rights)

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  3. alex3619

    alex3619 Senior Member (Voting Rights)

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    Potentially interesting but we need details, including cohort selection methods. Is there a link to the preprint, or just the abstract?
     
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  4. Kalliope

    Kalliope Senior Member (Voting Rights)

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    Sorry. I forgot to add the link :confused:
    have added it now
     
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  5. Kalliope

    Kalliope Senior Member (Voting Rights)

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  6. InitialConditions

    InitialConditions Senior Member (Voting Rights)

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    This guy seems like a real dud.
     
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  7. Trish

    Trish Moderator Staff Member

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    I think papers should show the patients' data, not just trees generated by computer algorithm.
    And prediction models are only any good if they are confirmed with an independent patient cohort.
     
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  8. josepdelafuente

    josepdelafuente Senior Member (Voting Rights)

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    I have a bit of a vague question on forum members thoughts / opinions on these guys - apologies as I know the question is vague!

    I'm having a bit of trouble working how if people feel like the IncellDX blood tests / science etc are basically nonsense, or if it's more that there's some scientific plausibility but not enough good data, or somewhere in between the two, or something else entirely?

    Any thoughts welcome!
     
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  9. InitialConditions

    InitialConditions Senior Member (Voting Rights)

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  10. alex3619

    alex3619 Senior Member (Voting Rights)

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    That still has potential confounds. Some systematic biases, including in patient selection, can distort the results. It is however a good place to start.
     
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  11. Jonathan Edwards

    Jonathan Edwards Senior Member (Voting Rights)

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    The conclusion in the abstract suggests that the authors have no real understanding of what it is they are trying to do.

    The more the lab results correlate with the clinical diagnosis, already made, the less use they are, since the simply give you the same diagnosis. Shifting to new lab based diagnoses might well be useful for choosing treatments but it might not.

    Cytokine assays are still as far as I know pretty useless in clinical medicine, except maybe for diagnosing Castleman's disease. This is not to me real clinical science.
     
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  12. Jonathan Edwards

    Jonathan Edwards Senior Member (Voting Rights)

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    The tweet about trolls is peculiar. Maybe these people have the same problem as the BPS crowd - some other people are on to them.
     
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  13. josepdelafuente

    josepdelafuente Senior Member (Voting Rights)

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    Thanks Jonathan!
     

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