Gout and the risk of COVID-19 diagnosis and death in the UK Biobank: a population-based study

  1. Ruth K Topless
  2. Angelo Gaffo
  3. Lisa K Stamp
  4. Philip C Robinson
  5. Nicola Dalbeth
  6. Tony R Merriman

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Abstract

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  1. Version published to 10.1016/s2665-9913(21)00401-x
  2. ScreenIT

    SciScore for 10.1101/2021.09.28.21264270: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variableAn additional model consisting of Model 1 plus eight gout-related metabolic comorbidities (hypertension, dyslipidaemia, type 2 diabetes, chronic kidney disease, obesity, coronary heart disease, cerebrovascular disease, heart failure) was used to investigate the hypothesis that women with gout are at increased risk of death related to COVID-19 owing to a metabolic co-morbidity burden, with obesity defined as BMI > 30 kg/m2.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Cell Line AuthenticationAuthentication: Gout was ascertained in the UK Biobank using the following criteria: self-reported gout (visits 0-2); taking allopurinol or sulphinpyrazone therapy either by self-report or from linked general practice scripts (excluding those who also had hospital diagnosed lymphoma or leukemia ICD10 C81 - C96); or hospital-diagnosed gout (ICD-10 code M10)7, this case definition has been validated.7,8 The gout cohort consisted of 15,560 cases (826 diagnosed with COVID-19).

    Table 2: Resources

    No key resources detected.

    Results from OddPub: Thank you for sharing your data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    We have identified nine limitations to our analyses. One, these analyses pertain to the population from which the UK Biobank was derived, predominantly the white European middle-aged ethnic group of the United Kingdom, and are not necessarily generalisable to other ethnic groups or other white European ethnic groups. Two, there is also no available information on recovery status so there is the possibility of additional unidentified deaths in the COVID-19 diagnosed group in Analysis B. In addition to this COVID-19 outcomes will have been influenced over the time period of this study (March 2020-April 2021) as clinical treatments evolved. We were able to account for this only in Analysis B. Limited testing outside of the hospital setting means that the full extent of SARS-CoV-2 infection is not known in this population. Thus, it is not possible to accurately compare asymptomatic or mild COVID-19 to those with more severe disease. Three, the UK Biobank dataset is also limited to those aged 49 to 86 as of 2020, a demographic with a higher case fatality ratio.20 This will have contributed to the inflated infection fatality ratio in the UK Biobank cohort of 6.6%, well above general population estimates of 0.5 to 1.5% (e.g. ref21). Therefore our findings cannot be generalised to those under 50 years of age. Four, there is the potential in Analysis B for index event (collider) bias resulting from conditioning the sample set on COVID-19 diagnosis which would serve to bias towards the...

    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.

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  3. Version published to 10.1101/2021.09.28.21264270v1 on medRxiv