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Table 3 Clinical outcome prediction using multivariate logistic regression

From: Reverse shock index multiplied by simplified motor score as a predictor of clinical outcomes for patients with COVID-19

Scoring systems

aOR of death

aOR of admission

aOR of ICU admission

aOR

95% CI

p–Value

aOR

95% CI

p–Value

aOR

95% CI

p–Value

SI

1.68

0.35–8.07

0.517

5.37

2.81–10.3

< 0.001

2.00

0.54–7.61

0.291

mSI

1.17

0.35–3.87

0.802

2.98

1.88–4.72

< 0.001

1.51

0.56–4.12

0.417

rSI-GCS

0.90

0.84–0.96

0.002

0.95

0.93–0.97

< 0.001

0.99

0.96–1.03

0.730

rSI-GCSM

0.81

0.69–0.95

0.008

0.88

0.84–0.93

< 0.001

0.99

0.92–1.08

0.918

rSI-sMS

0.67

0.50–0.89

0.006

0.76

0.69–0.84

< 0.001

1.01

0.89–1.15

0.862

  1. The covariables used in the multivariate logistic regression included age, sex, cardiovascular disease, central nervous system disease, chronic kidney disease, diabetes mellitus, systemic inflammatory response syndrome (SIRS) score, Quick Sequential Organ Failure Assessment (qSOFA) score, and Sequential Organ Failure Assessment (SOFA) score
  2. Each scoring system was separately evaluated using multivariable logistic regression because of their strong collinearity
  3. aOR adjusted odds ratio, CI confidence interval, SI shock index, mSI modified shock index, aOR adjusted odds ratio, rSI-GCS reverse shock index combined with the Glasgow Coma Scale, rSI-GCSM reverse shock index combined with the Glasgow Coma Scale motor subscale, rSI-sMS reverse shock index combined with the simplified motor score