Evolution of COVID-19 mortality over time: results from the Swiss hospital surveillance system (CH-SUR)

  1. Maroussia Roelens
  2. Alexis Martin
  3. Brian Friker
  4. Filipe Maximiano Sousa
  5. Amaury Thiabaud
  6. Beatriz Vidondo
  7. Valentin Buchter
  8. Céline Gardiol
  9. Jasmin Vonlanthen
  10. Carlo Balmelli
  11. Manuel Battegay
  12. Christoph Berger
  13. Michael Buettcher
  14. Alexia Cusini
  15. Domenica Flury
  16. Ulrich Heininger
  17. Anita Niederer-Loher
  18. Thomas Riedel
  19. Peter W. Schreiber
  20. Rami Sommerstein
  21. Nicolas Troillet
  22. Sarah Tschudin-Sutter
  23. Pauline Vetter
  24. Sara Bernhard-Stirnemann
  25. Natascia Corti
  26. Roman Gaudenz
  27. Jonas Marschall
  28. Yvonne Nussbaumer-Ochsner
  29. Laurence Senn
  30. Danielle Vuichard-Gysin
  31. Petra Zimmermann
  32. Franziska Zucol
  33. Anne Iten
  34. Olivia Keiser

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Abstract

BACKGROUND: When  the periods of time during and after the first wave of the ongoing SARS-CoV-2/COVID-19 pandemic in Europe are compared, the associated COVID-19 mortality seems to have decreased substantially. Various factors could explain this trend, including changes in demographic characteristics of infected persons and the improvement of case management. To date, no study has been performed to investigate the evolution of COVID-19 in-hospital mortality in Switzerland, while also accounting for risk factors. METHODS: We investigated the trends in COVID-19-related mortality (in-hospital and in-intermediate/intensive-care) over time in Switzerland, from February 2020 to June 2021, comparing in particular the first and the second wave. We used data from the COVID-19 Hospital-based Surveillance (CH-SUR) database. We performed survival analyses adjusting for well-known risk factors of COVID-19 mortality (age, sex and comorbidities) and accounting for competing risk. RESULTS: Our analysis included 16,984 patients recorded in CH-SUR, with 2201 reported deaths due to COVID-19 (13.0%). We found that overall in-hospital mortality was lower during the second wave of COVID-19 than in the first wave (hazard ratio [HR] 0.70, 95% confidence interval [CI] 0.63– 0.78; p <0.001), a decrease apparently not explained by changes in demographic characteristics of patients. In contrast, mortality in intermediate and intensive care significantly increased in the second wave compared with the first wave (HR 1.25, 95% CI 1.05–1.49; p = 0.029), with significant changes in the course of hospitalisation between the first and the second wave. CONCLUSION: We found that, in Switzerland, COVID-19 mortality decreased among hospitalised persons, whereas it increased among patients admitted to intermediate or intensive care, when comparing the second wave to the first wave. We put our findings in perspective with changes over time in case management, treatment strategy, hospital burden and non-pharmaceutical interventions. Further analyses of the potential effect of virus variants and of vaccination on mortality would be crucial to have a complete overview of COVID-19 mortality trends throughout the different phases of the pandemic.

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  1. Version published to 10.4414/smw.2021.w30105
  2. ScreenIT

    SciScore for 10.1101/2021.09.14.21263153: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variableWe used univariable and multivariable Fine and Gray models [15] to determine risk factors of mortality, adjusting for sex (male, female), age (as a continuous variable with restricted cubic splines [16]), time period of COVID-19 diagnosis (first wave, intermediate phase, second wave, last period), obesity (no, yes), smoking (no, yes), chronic respiratory disease (no, yes), cardiovascular disease (no, yes), renal disease (no, yes), oncological pathologies (no, yes), dementia (no, yes), immunosuppression (no, yes).
    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: 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.
    • No funding statement was detected.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

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  3. Version published to 10.1101/2021.09.14.21263153v1 on medRxiv