Table 9.

Logistic regression analyses to assess the association between post-viral-clearance hospitalization and minimum hemoglobin, maximum BUN, or potential confounding variables during the pre-COVID and SARS-CoV-2⁺ phases

	Minimum hemoglobin	Maximum BUN	Sex	Age	Blood draw count during interval	ICU admission during interval
Pre-COVID Phase	β = −0.108 p = 0.578	β = 0.011 p = 0.560	β = 0.086 p = 1.00	β = 0.006 p = 0.982	β = −0.013 p = 0.878	NA
SARS-CoV-2+ Phase	β = −0.289 p = 4.2x10−5	β = 0.006 p = 0.852	β = −0.173 p = 0.986	β = −0.003 p = 1.00	β = −0.003 p = 0.948	β = 0.590 p = 0.188

Confounding variables considered include sex, age, the number of blood draws in the given interval, and ICU admission status during the given interval. For each regression (row), the coefficient (β) and associated Bonferroni-adjusted p value (p) are shown for each independent variable (column) assessed. The coefficient represents the log-odds ratio. p Values were calculated using the log likelihood ratio test and adjusted using the Bonferroni correction. An association between an independent variable and post-clearance hospitalization is considered significant if p < 0.05 (shown in bold). The association between post-viral-clearance hospitalization and ICU admission during the pre-COVID interval was not analyzed because this information was not available for our cohort prior to April 2020. Binary variables were assigned as follows: sex: 0 = female, 1 = male; ICU admission during interval: 0 = not admitted to ICU, 1 = admitted to ICU.