Abstract
Background
We previously reported and validated a risk prediction tool based on COVID-19 hospitalizations prior to June 2020. Here, we report performance of that model on subsequent data from 6 hospitals and among individual patient subgroups.
Method
We included individuals age 18 or older hospitalized at one of 2 academic medical centers and 4 community hospitals from 6/7/2020 through 1/22/2021 with positive PCR test for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) within 5 days of admission. Coefficients from our previously reported least absolute shrinkage and selection operator (Lasso) risk models were applied to estimate probability of a mortality, as well as a composite severe illness outcome, including admission to the ICU, mechanical ventilation or mortality.
Results
Overall model performance for mortality included AUC of 0.83 (95% CI:0.80-0.87) for mortality, with a PPV 0.55 and NPV of 0.95 when using a cutoff corresponding to the highest 20% of predicted risk derived in the training set. For all adverse outcomes, AUC was 0.79 (95% CI:0.75-0.81) and PPV 0.48 and NPV 0.98 in the top 20% risk group. Model discrimination was generally similar between genders and race/ethnicity groups, but markedly poorer for younger age groups.
Conclusion
Although the population of individuals hospitalized for COVID-19 has shifted and outcomes have improved overall, prediction models derived earlier in the pandemic may maintain utility.
Full Text Availability
The license terms selected by the author(s) for this preprint version do not permit archiving in PMC. The full text is available from the preprint server.