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There was no significant differences between the two groups in the concomitant medication (Table 1).
No correlation was observed between phenprocoumon concentrations and height (p = 0.517), nicotine habits and concomitant medication (Table 3).
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In both cases, the higher costs with generic were due to greater use of visits and concomitant medication (Tables 5 and 6).
Following propensity score matching, users and nonusers of statins were highly similar with respect to demographics, medical illnesses, and concomitant medications (Table 1).
Around 45%% of participants received concomitant medications (Table 4).
On the use of concomitant medications (Table 5) there were no consistent differences between the SGAs.
Patients in the placebo and bezafibrate groups were well balanced in terms of clinical and laboratory baseline characteristics and concomitant medications (Table 1, 2).
The changes in the costs were estimated using the DID approach by adjusting for patient characteristics and concomitant medications (Table 3).
The following clinical and biochemical data were recorded for 72 patients: age, sex, Ccr, risk factors (eg, diabetes, hypertension, hypercholesterolemia, smoking), and concomitant medications (Table 1).
Our results indicate that approximately 29% of our study population would have reduced activity of either CYP2D6 or CYP3A4/5 activity due to either pharmacogenomic variants or concomitant medications (Table 2).
This self-reported co-morbidity was supported by the concomitant medication used (Table 2).
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