Table 2

Unbiased multivariate logistic regression analysis of 37 regressors (variables) against the primary outcome of death/ICU admission within 30 days of COVID-19 diagnosis (n=719 patients)

RegressorEstimateSEP valueMarginal effect (%)
Male gender0.5530.2560.0319.3
Ethnicity: South Asian−0.3210.4410.466−5.4
Ethnicity: black−0.2960.3600.411−5.0
Ethnicity: white−0.1790.2720.510−3.0
Diabetes mellitus0.0990.2650.7091.7
Ischemic heart disease0.5960.3640.10210.1
Heart failure0.0460.4080.9100.8
Chronic obstructive pulmonary disease−0.0510.3840.893−0.9
Active cancer−0.1350.4280.752−2.3
ACE inhibitor0.3510.3290.2855.9
Angiotensin II receptor blocker0.1450.3660.6912.5
Antiplatelet drug−0.6160.3190.05310.4
Clinical Frailty Scale score0.1830.0780.0193.1
White cell count0.0310.0850.7200.5
Platelet count−0.0040.0010.0010.1
Serum sodium0.0720.0230.002*1.2
Serum potassium0.2020.1940.3003.4
eGFR on diagnosis−0.0060.0050.287−0.1
C reactive protein0.0020.0010.1320.0
Respiratory rate0.0340.0210.1030.6
Heart rate0.0060.0080.4530.1
Systolic blood pressure0.0100.0060.0880.2
Diastolic blood pressure−0.0020.0100.8310.0
National Early Warning Score−0.0150.0550.790−0.2
Inspired oxygen delivered on diagnosis−0.0120.0060.0460.2
Oxygen saturations on diagnosis−0.0320.0180.079−0.5
Maximum inspired oxygen required during admission0.0680.007<0.00011.2
  • This is an unselected multivariate logistic (logit) analysis of all variables that were collected for patients admitted with swab-positive COVID-19. 719 patients are included with 37 variables, with the only exclusions being those patients/variables for which ≥5% data points were unknown. For categorical variables, a positive ‘estimate’ indicates an increased risk of the primary outcome (death or ICU admission) with that variable present, and a negative estimate indicates a reduced risk of the primary outcome if that variable is present. The p value is a measure of the confidence of that given variable being an independent predictor of the primary outcome corrected for all of the other regressors listed. For continuous variables, a positive ‘estimate’ indicates an increasing risk of the primary outcome as the variable increases. Since in logistic regressions estimated coefficients cannot be interpreted as a measure of the contribution of the effect, we have also calculated marginal effects. A positive marginal effect indicates that an increase in that variable is associated with a fully adjusted increased risk of the primary outcome. The converse applies for negative marginal effects. For categorical variables, the marginal effect indicates the percentage increased risk of the primary outcome, if that variable exists. So, for example, all other variables being equal, men have a 9.3% increased risk of death or ICU admission than women.

  • Statistically significant P values are shown in bold.

  • *The effect of serum sodium was skewed by patients with serum sodium >145 mmol/L.

  • eGFR, estimated glomerular filtration rate; ICU, intensive care unit.