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Development and Validation of a Survival Calculator for Hospitalized Patients with COVID-19

Todd J Levy, Safiya Richardson, Kevin Coppa

    Medrxiv : the Preprint Server for Health Sciences
    |June 9, 2020
    PubMed

    Insights

    A new calculator predicts 7-day survival in hospitalized coronavirus disease 2019 (COVID-19) patients using six routine factors. The NOCOS Calculator (Northwell COVID-19 Survival) aids in assessing patient outcomes.

    Area of Science:

    • Critical Care Medicine
    • Infectious Diseases
    • Biostatistics

    Background:

    • Predicting severe coronavirus disease 2019 (COVID-19) outcomes is crucial for patient management.
    • Existing survival calculators lack generalizability and simplicity, particularly for US patient populations.
    • A need exists for a validated clinical tool to estimate short-term survival in hospitalized COVID-19 patients.

    Approach:

    • A retrospective and prospective cohort study was conducted across thirteen acute care hospitals in the New York City area.
    • Data from 11,095 adult patients hospitalized with confirmed COVID-19 between March and May 2020 were analyzed.
    • Least Absolute Shrinkage and Selection Operator (LASSO) regression identified optimal predictors from demographic, laboratory, and clinical data.

    Key Points:

    • The NOCOS Calculator identifies six key predictors of 7-day survival: serum blood urea nitrogen, age, absolute neutrophil count, red cell distribution width, oxygen saturation, and serum sodium.
    • The calculator demonstrated strong performance with area under the curve (AUC) values of 0.86 for internal validation, 0.82 for prospective validation, and 0.82 for external validation.
    • Routine factors available at hospital admission are utilized, simplifying clinical application.

    Conclusions:

    • The NOCOS Calculator provides a simple and generalizable tool for predicting 7-day survival in hospitalized COVID-19 patients.
    • The calculator is publicly accessible, facilitating its use in clinical practice and research.
    • This tool can aid clinicians in risk stratification and management decisions for COVID-19 patients.
    Abstract

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