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In backward logistic regression analysis only the duration of nCPAP treatment [p = 0.001; odds ratio 1.059; 95% CI, 1.024 1.095] predicted DFWC statistically significantly.
Backward logistic regression analysis was next performed.
Backward logistic regression analysis was performed.
For identification of independent predictors of 90-day mortality we performed a multivariate backward logistic regression analysis.
A backward logistic regression analysis included all signs and symptoms, duration of symptoms and categorized laboratory values.
Subsequently, we performed a backward logistic regression analysis in which we simultaneously included the four peaks (continuous).
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A multivariable model was constructed using manual stepwise backward logistic-regression analysis, where variables not significant in the model were re-entered whenever a new variable became significant, or a variable was removed.
All parameters which were under the significance threshold of <0.05 were entered into a stepwise, backward multivariate logistic regression analysis for mortality at 12 months.
Variables found associated with a p value <0.20 in univariate analysis were entered into a multivariate backward stepwise logistic regression analysis in order to identify the factors independently associated with a definite diagnosis of NOMI.
Stepwise backward multiple logistic regression analysis was then used to identify those predictors that were independently associated with HIV/HPV infection.
Backward deletion logistic regression analysis.
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