Table 3.
Adjusted associations of OUD and OUD treatment with hospitalization, maximum LOS, invasive ventilator dependence, and death among COVID-19 positive patients.
| Variables | Hospitalization | Maximum LOS | Invasive Ventilator Dependence | Death |
|---|---|---|---|---|
| aOR1 (95% CI) | 2 (95% CI) | aOR1 (95% CI) | aOR1 (95% CI) | |
| Main Analysis3: OUD status | ||||
| No | 1 [Reference] | 1 [Reference] | 1 [Reference] | 1 [Reference] |
| Yes | 3.44 (2.81, 4.21) | 1.16 (1.09, 1.22) | 1.26 (1.06, 1.49) | 1.15 (0.94, 1.41) |
| AUC | 0.85 | – | 0.78 | 0.85 |
| R2 | – | 0.12 | – | – |
| Sensitivity Analysis3: OUD Treatment status | ||||
| No OUD | 1 [Reference] | 1 [Reference] | 1 [Reference] | 1 [Reference] |
| OUD without treatment | 4.05 (3.32, 4.98) | 1.14 (1.08, 1.21) | 1.25 (1.04, 1.50) | 1.31 (1.07, 1.61) |
| OUD with naltrexone | 32.19 (4.29, 4119.83) | 1.59 (1.06, 2.38) | 3.15 (1.04, 9.51) | 1.87 (0.39, 8.91) |
| OUD with OAT | 5.14 (2.75, 10.60) | 1.22 (1.01, 1.48) | 1.04 (0.54, 2.00) | 0.52 (0.19, 1.46) |
| OUD without treatment | 1 [Reference] | 1 [Reference] | 1 [Reference] | 1 [Reference] |
| OUD with naltrexone | 7.95 (1.05, 1019.45) | 1.39 (0.93, 2.09) | 2.52 (0.82, 7.71) | 1.43 (0.30, 6.90) |
| OUD with OAT | 1.27 (0.66, 2.68) | 1.07 (0.88, 1.31) | 0.83 (0.42, 1.64) | 0.40 (0.14, 1.13) |
| OUD with naltrexone | 1 [Reference] | 1 [Reference] | 1 [Reference] | 1 [Reference] |
| OUD with OAT | 0.16 (0.01, 1.39) | 0.77 (0.49, 1.20) | 0.33 (0.09, 1.19) | 0.28 (0.04, 1.81) |
| AUC | 0.85 | – | 0.78 | 0.83 |
| R2 | – | 0.12 | – | – |
Adjusted odds ratio from logistic regression model;.
Adjusted exponentiated coefficient (exponential regression model) relating to change in the ratio of expected maximum LOS (i.e., “OUD with OAT” coefficient is the ratio of the expected maximum LOS for those with an OUD on OAT over expected maximum LOS for those without an OUD, so maximum LOS is 22% greater for patients with an OUD on OAT compared to patients without an OUD);.
Models of sufficient sample sizes adjusted for age, gender, race/ethnicity, insurance, region, Diabetes mellitus (DM), asthma, hypertension, hydroxychloroquine, Remdesivir, Decadron or Prednisone, aspirin and Plavix; models of insufficient sample sizes had medications and disease histories removed to avoid overfitting.