A Model Predicting Mortality of Hospitalized Covid-19 Patients Four Days After Admission: Development, Internal and Temporal-External Validation

  1. Stefan Heber
  2. David Pereyra
  3. Waltraud C. Schrottmaier
  4. Kerstin Kammerer
  5. Jonas Santol
  6. Benedikt Rumpf
  7. Erich Pawelka
  8. Markus Hanna
  9. Alexander Scholz
  10. Markus Liu
  11. Agnes Hell
  12. Klara Heiplik
  13. Benno Lickefett
  14. Sebastian Havervall
  15. Marianna T. Traugott
  16. Matthias J. Neuböck
  17. Christian Schörgenhofer
  18. Tamara Seitz
  19. Christa Firbas
  20. Mario Karolyi
  21. Günter Weiss
  22. Bernd Jilma
  23. Charlotte Thålin
  24. Rosa Bellmann-Weiler
  25. Helmut J. F. Salzer
  26. Gero Szepannek
  27. Michael J. M. Fischer
  28. Alexander Zoufaly
  29. Andreas Gleiss
  30. Alice Assinger

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Abstract

To develop and validate a prognostic model for in-hospital mortality after four days based on age, fever at admission and five haematological parameters routinely measured in hospitalized Covid-19 patients during the first four days after admission.

Methods

Haematological parameters measured during the first 4 days after admission were subjected to a linear mixed model to obtain patient-specific intercepts and slopes for each parameter. A prediction model was built using logistic regression with variable selection and shrinkage factor estimation supported by bootstrapping. Model development was based on 481 survivors and 97 non-survivors, hospitalized before the occurrence of mutations. Internal validation was done by 10-fold cross-validation. The model was temporally-externally validated in 299 survivors and 42 non-survivors hospitalized when the Alpha variant (B.1.1.7) was prevalent.

Results

The final model included age, fever on admission as well as the slope or intercept of lactate dehydrogenase, platelet count, C-reactive protein, and creatinine. Tenfold cross validation resulted in a mean area under the receiver operating characteristic curve (AUROC) of 0.92, a mean calibration slope of 1.0023 and a Brier score of 0.076. At temporal-external validation, application of the previously developed model showed an AUROC of 0.88, a calibration slope of 0.95 and a Brier score of 0.073. Regarding the relative importance of the variables, the (apparent) variation in mortality explained by the six variables deduced from the haematological parameters measured during the first four days is higher (explained variation 0.295) than that of age (0.210).

Conclusions

The presented model requires only variables routinely acquired in hospitals, which allows immediate and wide-spread use as a decision support for earlier discharge of low-risk patients to reduce the burden on the health care system.

Clinical Trial Registration

Austrian Coronavirus Adaptive Clinical Trial (ACOVACT); ClinicalTrials.gov, identifier NCT04351724.

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  1. Version published to 10.3389/fcimb.2021.795026
  2. ScreenIT

    SciScore for 10.1101/2020.12.20.20248563: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Of note, the recovery of data at the Clinic Favoriten in Vienna is part of the ACOVACT study (ClinicalTrials.gov NCT04351724) approved by the local ethics committee (EK1315/2020), which aims to compare the effect of different antiviral and adjunctive treatments on outcome of hospitalized Covid-19 patients.
    Randomizationnot detected.
    BlindingBlinding: The individuals accessing the medical records to extract variables were not blinded to the outcome.
    Power Analysisnot detected.
    Sex as a biological variablenot 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:
    Limitations: The most important limitation is the uncertainty whether the model performs adequately in other geographical regions than Austria. Validation in a relatively small Swedish cohort showed a significantly worse model performance than in two Austrian cohorts. However, we have to state that there are substantial differences between the Austrian and the Swedish cohorts, which could explain the discrepancy in the performance. First, admission criteria differed between Austria and Sweden when the patients included in this analysis were hospitalized. While Swedish patients were only admitted if they needed additional oxygen, the indication for hospitalization was far more permissive in Austria. Consequently, patients in Sweden were hospitalized at a later stage of the disease, as evidenced by the significantly higher number of days with symptoms before admission in the Swedish cohort compared to the Austrian ones. Further, the peak of the first wave of the pandemic hit Sweden far stronger than Austria, which also affected clinical care differently. For instance, few patients from nursing homes were admitted to Swedish hospitals at that time, explaining why the Austrian cohorts show a wider age distribution compared to the Swedish cohort. Of note, while in general mortality rates during spring were much higher in Sweden compared to Austria, the percentage of in hospital mortalities was much lower in this cohort compared to Austria (12.5% in Stockholm versus 22.4% in Vienna...

    Results from TrialIdentifier: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT04351724RecruitingAustrian CoronaVirus Adaptive Clinical Trial (COVID-19)

    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.

    About SciScore

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  3. Version published to 10.1101/2020.12.20.20248563v1 on medRxiv