Sentence examples for medication use model from inspiring English sources

Mediation of this relationship was assessed (24) when adjusting for glycemic control (Table 2, model 2), age and sex (model 3), blood pressure (model 4), and antihypertensive medication use (model 5).

As shown in Table 2, the association of decreased eGFRCKD-EPI or eGFRMDRD with the risk of mortality remained statistically significant after adjustment for age and sex (model 1) and also after additional adjustment for BMI, diabetes duration, smoking, A1C, LDL cholesterol, hypertension, and medication use (model 2).

With further adjustment of current smoking status, cognitive impairment, and supplementation as well as medication uses (Model 3), AECOPD (adjusted OR = 1.47, 95% CI = 1.01-2.13) and uses of muscle relaxants (AOR =2.94; 95% CI =1.29-6.69) were significantly associated with lower DF by the multiple logistic regression model (Table  2 and Additional file 1).

When the target of a health care organisation is the management of an individual's medication use, predictive models based on pharmacy data are particularly useful.

[ 16] A review of the use of the transtheoretical model in medication adherence revealed that the model has not been used extensively to investigate medication use, although the model has shown promise as a context for developing interventions to improve adherence.

Finally, we did not include medication use in our model.

All associations remained significant after further adjustments for antihypertensive and lipid-lowering medication use in the model.

We did examine for an effect of medication use in the model, assuming that powerful anti-rheumatic agents might slow progression of cartilage damage.

We initially adjusted for age and sex (model 1) and in addition for diabetes duration, A1C, SBP, BMI, use of diabetes medications, use of lipid-lowering medications, and insulin use (model 2).

Multimorbidity, cardiovascular disease, hypertension, and dyslipidemia were associated with medication use in univariate models but did not remain significant in adjusted models.

Accordingly, failure to include measures of medication use in prediction models represents a potential source of bias due to unmeasured confounding that could lead to erroneous conclusions [ 24].