This is table 4 from the linked paper:
Table 4. Univariate mixed-effects logistic regression model for the associations between independent variables and surgical site infections (patients: level 1* and hospitals: level 2**).
Variables Surgical site infection after total hip arthroplasty
Odds ratio 95% confidence interval p-value
Elective procedure* (reference: non-elective) 0.40 0.24, 0.67 p < 0.001
Age group* 1.04 1.02, 1.07 p < 0.001
Staffing adequacy** 0.97 0.95, 0.99 p = 0.009
Overall survival** 0.81 0.46, 1.43 p = 0.476
Nurses' reports on the quality system** 0.99 0.95, 1.05 p = 0.938
Patient safety management** 1.00 0.96, 1.04 p = 0.980
Nurse-physician relationship** 0.99 0.95, 1.05 p = 0.935
Quality of nursing** 1.00 0.96, 1.04 p = 0.984
Note how the odds ratios (even the significant ones) are mostly close to 1. These table is the uni-variate (that is, with only one predictor) (logistic) regressions, all with the same response surgical site infections.
Then the multi-predictor (logistic) regression:
Table 5. Mixed-effects logistic regression model for the associations
between independent variables and surgical site infections including
the interaction between staffing adequacy and procedure type (n =
2724) (patients: level 1* and hospital: level 2**).
Variables Surgical site infection after total hip arthroplasty
Odds ratio 95% confidence interval p-value
Staffing adequacy 1.00 0.96, 1.02 0.670
Age group 1.03 1.01, 1.06 0.008
Non-elective procedure 1 – –
Elective procedure 5.4 1.34, 21.7 0.017
Interaction: elective procedure × staffing adequacy 0.94 0.91, 0.97 0.001
No other model validation is reported. I'm not sure this looks very convincing, looks like a pilot study.