Product Images Duloxetine
View Photos of Packaging, Labels & Appearance
Product Label Images
The following 11 images provide visual information about the product associated with Duloxetine NDC 60760-951 by St. Mary's Medical Park Pharmacy, 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.
This text appears to be a chart or table showing the percentage of patients improved in relation to different treatments. It mentions the medications "Duloxetine 60 mg BID" and "Duloxetine 60 mg QD" as well as a placebo. The chart also shows different levels of pain improvement from baseline, ranging from 10% to 100%. Overall, it seems to be evaluating the effectiveness of different treatments in improving patients' pain levels.*
This text appears to be a description of a clinical study evaluating the effectiveness of different doses of Duloxetine in reducing pain. The study compares three different doses of Duloxetine (120 mg, 60 mg, and 20 mg) taken once daily to a placebo. The text also mentions the percentage of patients who experienced improvement in pain and provides a graphical representation of the percent improvement in pain from baseline. The graph shows that as the dose of Duloxetine increases, the percentage improvement in pain also increases.*
Percentage of Patients Improved: This text appears to show a chart or graph displaying the percentage of patients who experienced improvement in their condition. The data is represented using numbers, with the range of improvement shown as 0 to 100. It seems that there are two different treatment groups being compared - a placebo group and a group taking a medication called Duloxetine at different dosages (60/120 mg once). The chart does not provide specific details about the type of condition being treated or the time frame over which the improvement was measured.*
* 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.