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We determined that ISS would serve as the best proxy of severity for final multivariable analysis due to the low percentage of missing values (1.4 %) compared to other potential variables and its common use as a severity indicator in the TBI literature (e.g. Reid et al. 2001; Gabella et al. 1997).
Caution should be used in interpretation of the multivariable analysis due to few TB cases.
Patients were excluded from multivariable analysis due to incompleteness of pathological data.
Twenty-eight participants could not be included in the multivariable analysis due to missing predictor variable data, leaving a sample of 659.
We were unable to examine this relationship in the multivariable analysis due to insufficient women with both shoulder dystocia and OASIS.
Although depression was not included in the multivariable analysis due to the multicollinearity problem, stress (p<0.001, OR 1.99; 95% CI 1.53 to 2.58) showed a strong association with dizziness.
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It should be noted that this variable didn't remain significant in our multivariable analysis, possibly due to low statistical power.
Similarly, highest qualification and age left full-time education were considered in the multivariable analysis independently due to collinearity.
No significant differences were found among tertiles group in multivariable analysis, probably due to the low number of progression events, with a consequent loss of statistical power.
The variables cardio-vascular disease, non-hematologic cancer, renal failure, and intensity of the contact with placental material had a p-value <0.20 in univariate analysis, but were not included in multivariable regression analysis due to the small numbers (Table 2).
However, in this case, only a univariable analysis was conducted as multivariable analysis was not possible due to the small number of infected herds participating in the study.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com