From predictions to prescriptions: A data-driven response to COVID-19

  1. Dimitris Bertsimas
  2. Leonard Boussioux
  3. Ryan Cory-Wright
  4. Arthur Delarue
  5. Vassilis Digalakis
  6. Alexandre Jacquillat
  7. Driss Lahlou Kitane
  8. Galit Lukin
  9. Michael Li
  10. Luca Mingardi
  11. Omid Nohadani
  12. Agni Orfanoudaki
  13. Theodore Papalexopoulos
  14. Ivan Paskov
  15. Jean Pauphilet
  16. Omar Skali Lami
  17. Bartolomeo Stellato
  18. Hamza Tazi Bouardi
  19. Kimberly Villalobos Carballo
  20. Holly Wiberg
  21. Cynthia Zeng

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Abstract

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  1. Version published to 10.1007/s10729-020-09542-0
  2. ScreenIT

    SciScore for 10.1101/2020.06.26.20141127: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    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:
    A limitation of the current mortality model is that it does not take into account medication and treatments during hospitalization. We intend to incorporate these in future research to make these models more actionable. Furthermore, these models aim to reveal associations between risks and patient characteristics but are not designed to establish causality. Overall, we have developed data-driven calculators that allow physicians and patients to assess mortality and infection risks in order to guide care management—especially with scarce healthcare resources. These calculators are being used by several hospitals within the ASST Cremona system to support triage and treatment decisions—alleviating the toll of the pandemic. Our infection calculator also supports safety protocols for Banco de Credito del Peru, the largest bank in Peru, to determine how employees can return to work.

    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.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2020.06.26.20141127 on medRxiv