@InProceedings{lengerich2021time,
  title={Time-Varying Mortality Risk Suggests Increased Impact of Thrombosis in Hospitalized Covid-19 Patients},
  author={Lengerich, Benjamin J and Nunnally, Mark E and Aphinyanaphongs, Yin J and Caruana, Rich},
  booktitle={Machine Learning for Health},
  year={2022},
  url_preprint={https://www.medrxiv.org/content/10.1101/2021.12.11.21267259v1},
  abstract={Treatment protocols, treatment availability, disease understanding, and viral characteristics have changed over the course of the Covid-19 pandemic; as a result, the risks associated with patient comorbidities and biomarkers have also changed. We add to the ongoing conversation regarding inflammation, hemostasis and vascular function in Covid-19 by performing a time-varying observational analysis of over 4000 patients hospitalized for Covid-19 in a New York City hospital system from March 2020 to August 2021 to elucidate the changing impact of thrombosis, inflammation, and other risk factors on in-hospital mortality. We find that the predictive power of biomarkers of thrombosis risk have increased over time, suggesting an opportunity for improved care by identifying and targeting therapies for patients with elevated thrombophilic propensity.},
    keywords={Healthcare, Covid-19}
}

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