Product Images Eliquis
View Photos of Packaging, Labels & Appearance
Product Label Images
The following 9 images provide visual information about the product associated with Eliquis NDC 82982-054 by Pharmasource Meds, Llc, such as packaging, labeling, and the appearance of the drug itself. This resource could be helpful for medical professionals, pharmacists, and patients seeking to verify medication information and ensure they have the correct product.
The text appears to be a fragment of a label or packaging information for a medication called "Eliquis" with the active ingredient "apixaban" in tablet form. The meaning behind "Pl", "sz", and "DTG" cannot be determined.*
This is a table with various subgroups of patients comparing the clinical outcomes of Apixaban and Warfarin for stroke prevention in atrial fibrillation. The table records the number of patients, percentage per year, and Hazard Ratio (with the respective 95% CI) for each subgroup. The subgroups are distinguished by their demographics, comorbidities, and randomized treatment assignment. The Hazard Ratios for Apixaban vs. Warfarin are represented graphically ("Apixaban Better" or "Warfarin Better").*
This is a table showing the fold change and 90% confidence interval of drug interactions with combined P-gp and strong CYP3A4 inhibitors, other CYP3A4 and P-gp inhibitors, and combined P-gp and strong CYP3A4 inducer. The table includes information on the drugs and their corresponding AUC values. There is also information on the change in AUC relative to reference values for each drug.*
This is a medication or drug information sheet providing recommendations for dosage adjustment based on patient characteristics such as age, weight, hepatic or renal impairment, and disease status. The table includes fold changes and their corresponding 90% confidence intervals. The text suggests that for some conditions or characteristics no dose adjustment is needed, while for others specific dosing recommendations are provided.*
* The product label images have been analyzed using a combination of traditional computing and machine learning techniques. It should be noted that the descriptions provided may not be entirely accurate as they are experimental in nature. Use the information in this page at your own discretion and risk.