Abstracts from the 15th EAI International Conference on Pervasive Computing Technologies for Healthcare, PervasiveHealth 2021, 6 December 2021, Tel Aviv, Israel

Research Article

Statistical power boost for broadly applicable host immune response-based tools

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  • @INPROCEEDINGS{10.4108/eai.6-12-2021.2314316,
    author={Niv Samuel Mastboim and Alon Angel and Oded Shaham and Tahel Ilan Ber and Roy Navon and Einav Simon and Michal Rosenberg and Yael Israeli and Mary Hainrichson and Noa Avni and Eran Reiner and Paul Feigin and Kfir Oved and Boaz Tadmor and Pierre Singer and Ilya Kagan and Shaul Lev and Dror Diker and Amir Jarjou’i and Ramzi Kurd and Eli Ben-Chetrit and Guy Danziger and Cihan Papan and Sergey Motov and Ma’anit Shapira and Michal Stein and Adi Klein and Tanya M Gottlieb and Eran Eden},
    title={Statistical power boost for broadly applicable host immune response-based tools},
    proceedings={Abstracts from the 15th EAI International Conference on Pervasive Computing Technologies for Healthcare, PervasiveHealth 2021, 6 December 2021, Tel Aviv, Israel},
    publisher={EAI},
    proceedings_a={PERVASIVEHEALTH - EAI},
    year={2022},
    month={3},
    keywords={statistical framework; disease severity; early prediction of disease progression; covid-19; host immune response},
    doi={10.4108/eai.6-12-2021.2314316}
}
  • Niv Samuel Mastboim
    Alon Angel
    Oded Shaham
    Tahel Ilan Ber
    Roy Navon
    Einav Simon
    Michal Rosenberg
    Yael Israeli
    Mary Hainrichson
    Noa Avni
    Eran Reiner
    Paul Feigin
    Kfir Oved
    Boaz Tadmor
    Pierre Singer
    Ilya Kagan
    Shaul Lev
    Dror Diker
    Amir Jarjou’i
    Ramzi Kurd
    Eli Ben-Chetrit
    Guy Danziger
    Cihan Papan
    Sergey Motov
    Ma’anit Shapira
    Michal Stein
    Adi Klein
    Tanya M Gottlieb
    Eran Eden
    Year: 2022
    Statistical power boost for broadly applicable host immune response-based tools
    PERVASIVEHEALTH - EAI
    EAI
    DOI: 10.4108/eai.6-12-2021.2314316
Niv Samuel Mastboim1, Alon Angel1, Oded Shaham1, Tahel Ilan Ber1, Roy Navon1, Einav Simon1, Michal Rosenberg1, Yael Israeli1, Mary Hainrichson1, Noa Avni1, Eran Reiner1, Paul Feigin2, Kfir Oved3, Boaz Tadmor4, Pierre Singer4, Ilya Kagan4, Shaul Lev4, Dror Diker4, Amir Jarjou’i5, Ramzi Kurd5, Eli Ben-Chetrit5, Guy Danziger6, Cihan Papan6, Sergey Motov7, Ma’anit Shapira8, Michal Stein8, Adi Klein8, Tanya M Gottlieb1,*, Eran Eden1
  • 1: MeMed, Israel
  • 2: Technion-Israel Institute of Technology, Israel
  • 3: MeMed, Israel; Canopy Immuno-therapeutics
  • 4: Rabin Medical Center, Israel
  • 5: Shaare Zedek Medical Center, Hebrew University School of Medicine, Israel
  • 6: Saarland University Hospital, Germany
  • 7: Maimonides Medical Center, US
  • 8: Hillel Yaffe Medical Center, Israel; Technion-Israel Institute of Technology, Israel
*Contact email: tanya.gottlieb@me-med.com

Abstract

COVID-19 is a diversely manifested and potentially deadly disease. This is challenging for patient management and development of evidence-based tools, especially considering SARS-CoV-2 evolution and variable pandemic mitigation strategies. Early detection of COVID-19 progression aids in resource allocation and enables timely escalation of care. MeMed has developed a severity prediction test based on an algorithm combining measurements of three immune proteins, creating a technology-human biology synergy that leverages the immune response. Establishing health system comparability is essential when combining data from multiple COVID-19 sub-cohorts, which separately provide low statistical power. To address this, a framework was constructed assessing two dimensions of poolability: respiratory status and therapeutic management.

Keywords
statistical framework; disease severity; early prediction of disease progression; covid-19; host immune response
Published
2022-03-03
Publisher
EAI
http://dx.doi.org/10.4108/eai.6-12-2021.2314316
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