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Variables were taken forward for multivariable analysis when significant at p < 0.2 [ 13].
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First, variables were tested variable-by-variable. Variables showing an association at a significance level of P < 0.2 were arbitrarily selected for multivariable analysis (forward and backward selection procedures).
Variables significantly prognostic in univariate analysis were selected for multivariable analysis using the forward stepwise method.
A forward stepwise (Likelihood Ratio) procedure was used for multivariable analysis.
Univariate data comprise only patients eligible for multivariable analysis.
Linear regression and Cox proportional hazard models were used for multivariable analysis.
In total, 3902 (85.9%) had records for each adjustment variable and were valid for multivariable analysis (Fig. 1).
The level of significance of p≤0.05 was set for multivariable analysis.
Linear regression was used for multivariable analysis.
For multivariable analysis, a complete case analysis was undertaken.
Cox proportional hazards model was used for multivariable analysis.
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