Fig 1.
Cycle threshold values from SARS-CoV-2-specific RT-PCR tests among patients presenting to the emergency department with COVID-19 over time, separated by type of SARS-CoV-2 assay.
Shaded areas represent 95% prediction intervals and lines are best-fit curves from a Gamma regression model. The ratio of expected CT values for each assay type on consecutive days was 1.004 (95% CI: 1.0036–1.0046).
Fig 2.
Proportions of patients presenting to the emergency department with high, medium, and low SARS-CoV-2 viral loads over time.
Fig 3.
Proportion of hospitalized patients with COVID-19 who died in the hospital over time.
Davies’ test for logistic regression shows that the increase then decrease in the mortality proportion over time is statistically significant (P<10−10).
Fig 4.
Number of hospitalized patients who died during their hospitalization by day of ED presentation.
Black lines represent the actual number of deaths. Red lines represent predicted number of deaths based on the multivariable logistic regression model. Blue lines represent the predicted number of deaths if the proportions of patients with high, medium, and low viral loads had stayed the same as that observed on March 15, 2020. The Hosmer-Lemeshow test had a P value of 0.084 for testing general calibration and an across-time variant had a P value of 0.21. An additional graph in the top-right corner demonstrates the number of patients admitted with COVID-19 to study hospitals during each day of the study.
Fig 5.
Proportion of hospitalized patients who died during their hospitalization by day of ED presentation.
Black lines represent the actual number of deaths. Red lines represent predicted number of deaths based on the multivariable logistic regression model. Blue lines represent the predicted number of deaths if the proportions of patients with high, medium, and low viral loads had stayed the same as that observed on March 15, 2020.
Table 1.
Logistic regression model of factors associated with in-hospital mortality among patients admitted with COVID-19.