To some degree, these factors may reflect lack of literacy regarding clinical trials and/or acupuncture; however, in multivariate models adjusting for these barriers, education was still highly associated with minimal change in adjusted odds ratio.
METHODS: We compared presurgery symptoms and treatment outcomes between patients with and without diabetes using univariate and multivariate models, adjusting for demographics and comorbidities.
The multivariate model adjusting for potential confounding factors also included sex (male/female), age (10 13 years/14 18 years), as well as Saudi Arabian nationality (yes/no) as dichotomous variables.
In multivariate models adjusting for duration of diabetes, systolic blood pressure, cigarette smoking, serum glucose, Cerebrovascular Risk Factor Scale, Cumulative Illness Rating Scale, and retinopathy levels, this relationship remained significant for retinal arterioles (p =.02) but not for retinal venules (p =.10).
A multivariate model adjusting for age, sex and study centre confirmed these general trends in prevalence (Figure 1).
Footnote= 1.00 reference category for logistic regression analyses, # multivariate model adjusting for all variables.
In addition, the interaction of both polymorphisms remained statistically significant in multivariate models adjusting for clinical prognostic factors.
There was no significant trend in multivariate models adjusting for other covariates (p for trends > 0.53) (Table 5).
A multivariate model adjusting for age and gender of patients was also performed for selected genes and isoforms.
The comparisons were significant (p < 0.001) in a linear mixed multivariate model adjusting for a number of confounding factors.
