Table 2.
Predictors | Odds ratio | 95%CI |
---|---|---|
(Age/100)2 Age in yearsa | 14.339 | 10.054, 20.532 |
Cardiovascular disease | 1.372 | 1.195, 1.573 |
Severe chronic kidney disease | 1.797 | 1.433, 2.252 |
Dyspnoea | 1.655 | 1.451, 1.891 |
1/(SBP/100)2 SBP in mmHga | 2.326 | 1.837, 2.951 |
Tachypnoea (>20 breaths/min) | 2.487 | 2.192, 2.824 |
SpO2 ≤93% or oxygen requirement | 3.320 | 2.889, 3.819 |
Confusion | 1.976 | 1.642, 2.380 |
Dependency (moderate or severe) | 1.178 | 0.989, 1.404 |
Predictors in the PRIORITY model retained after LASSO feature selection. Model coefficients were derived from a multivariate logistic regression, and presented as odds ratios (ORs) and 95% confidence intervals (95%CIs). Variables entered into the LASSO feature selection process were: age as a squared term, sex, ethnicity, smoking history, obesity, hypertension, diabetes mellitus, cardiovascular disease, pulmonary diseases, severe chronic kidney disease, malignancy, immunocompromised status, dependency, fever, dyspnoea, systolic blood pressure (SBP) as the inverse of a quadratic term, heart rate (HR) as a cubic term, tachypnoea, peripheral oxygen saturation (SpO2) ≤93% on room air or oxygen requirement at presentation, pulmonary rales, and confusion. All predictors were coded as binary variables (1 when present and 0 when absent) except for age (years), SBP (mmHg) and HR (bpm).
Continuous predictors modelled as fractional polynomial terms, including rescaling when the range of values of the predictor was reasonably large. As interpretability of the effect of non-linear continuous predictors can be difficult, linear local approximations of ORs for 10-unit variations are provided at selected values. ORs for age (10-year increments): OR (50/40) = 1.271; OR (70/60) = 1.414; OR (90/80) = 1.573. ORs for SBP (10-mmHg decreases): OR (110/120) = 1.118; OR (90/100) = 1.219; OR (70/80) = 1.497. Approximated ORs are provided for illustrative purposes only and were not used for making predictions.