COVID-19 mortality in Italy varies by patient age, sex and pandemic wave

  1. Francesca Minnai
  2. Gianluca De Bellis
  3. Tommaso A. Dragani
  4. Francesca Colombo

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Abstract

SARS-CoV-2 has caused a worldwide epidemic of enormous proportions, which resulted in different mortality rates in different countries for unknown reasons. We analyzed factors associated with mortality using data from the Italian national database of more than 4 million SARS-CoV-2-positive cases diagnosed between January 2020 and July 2021, including > 415 thousand hospitalized for coronavirus disease-19 (COVID-19) and > 127 thousand deceased. For patients for whom age, sex and date of infection detection were available, we determined the impact of these variables on mortality 30 days after the date of diagnosis or hospitalization. Multivariable weighted Cox analysis showed that each of the analyzed variables independently affected COVID-19 mortality. Specifically, in the overall series, age was the main risk factor for mortality, with HR > 100 in the age groups older than 65 years compared with a reference group of 15–44 years. Male sex presented a two-fold higher risk of death than female sex. Patients infected after the first pandemic wave (i.e. after 30 June 2020) had an approximately threefold lower risk of death than those infected during the first wave. Thus, in a series of all confirmed SARS-CoV-2-infected cases in an entire European nation, elderly age was by far the most significant risk factor for COVID-19 mortality, confirming that protecting the elderly should be a priority in pandemic management. Male sex and being infected during the first wave were additional risk factors associated with COVID-19 mortality.

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  1. Version published to 10.1038/s41598-022-08573-7
  2. Version published to 10.21203/rs.3.rs-970641/v1 on Research Square
  3. ScreenIT

    SciScore for 10.1101/2021.10.01.21264359: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    No key resources detected.

    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:
    A limitation of our study is the lack of data about COVID-19 patients’ comorbidities, which are important risk factors for outcome [8]. This lack of information prevented us from analyzing other risk factors for death. Moreover, the reasons why some hospitalized patients were classified as asymptomatic are not known, but their hospitalization may have been due to reasons other than COVID-19. For example, in 5,432 cases, the date of SARS-CoV-2 infection detection was after the date of hospitalization and in 13,144 patients the diagnosis was on the same day. Overall, this study confirms that age and male sex are independent risk factors for COVID-19 mortality for both hospitalized and not-hospitalized patients. Because age was found to be the most impactful negative prognostic factor, it should be considered in pandemic management, by giving priority to strategies aimed at protecting elderly people. Additionally, this is the first country-wide study to demonstrate a high risk of mortality during the first pandemic wave than later. Similar nation-wide studies in different countries, to the best of our knowledge, have not been published. Thus, we cannot compare our study with those from other nations with different mortality rates, and we cannot exclude that such differences are due to unequal pandemic management in the first wave, considering that Italy was the first Western nation to be affected. Our study also suggests that the medical research that started with the pandemic o...

    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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  4. Version published to 10.1101/2021.10.01.21264359v1 on medRxiv