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. 2023 Aug 3;43(4):243-253. doi: 10.5144/0256-4947.2023.243

Table 2.

Multivariable logistic regression analysis for predictors of acquiring secondary infections.

Predictors B P value OR 95% CI
Lower Upper
Female gender .40 .330 1.49 .67 3.37
Saudi nationality .79 .142 2.19 .77 6.26
Age in years .46 .266 1.58 .71 3.53
Admission age -.04 .143 .96 .90 1.01
BMI .00 .082 1.00 .99 1.00
Oxygen treatment -.20 .692 .82 .30 2.21
ICU admission .61 .231 1.83 .68 4.93
Invasive treatment procedures .58 .202 1.79 .73 4.40
Length of stay .00 .673 1.00 1.00 1.01
Co-morbidities
 Cardiovascular disease -.17 .729 .84 .31 2.24
 Diabetes mellitus .50 .242 1.64 .71 3.78
 Respiratory disease -.08 .887 .92 .29 2.90
 Chronic kidney disease .61 .221 1.85 .69 4.92
 Stroke .69 .284 1.99 .56 7.04
 Pregnancy -.88 .531 .41 .03 6.52
 Immunocompromised -.38 .787 .68 .04 10.87
 Others .16 .701 1.17 .53 2.59
 Overweight .27 .648 1.31 .41 4.25
 Obese 1.26 .036 3.54 1.09 11.51
 Extreme obesity .39 .548 1.48 .41 5.25

Model summary measures: Omnibus test, chi-square=101.986, P>.001; -2 likelihood= 185.951, Nagelkerke R square=.435