Product Images Pregabalin Capsules, Cv
View Photos of Packaging, Labels & Appearance
Product Label Images
The following 15 images provide visual information about the product associated with Pregabalin Capsules, Cv NDC 50090-5938 by A-s Medication Solutions, 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 appears to be a formula used for estimating creatinine clearance (CL) in adults based on their age, weight, and serum creatinine levels. The formula includes a variable for gender (represented by a factor of 0.85 for females), which suggests that it may be used differently for male and female patients. However, without additional context it is difficult to provide a more specific description or explanation of its use.*
This document appears to be a graph of patient improvement percentages related to pain. The x-axis lists numerical values ranging from 210 to 290, while the y-axis displays percentages ranging from 0 to 100. The title of the graph is "Percent Improvement in Pain from Baseline," and it appears that patient improvement percentages are plotted in relationship to various values on the x-axis. However, the text in the middle of the graph is not readable and may be a result of an error in .*
This document appears to be a chart or graph displaying responder rates in a study. It shows a 60% responder rate and three additional percentages: 40.6%, 29.1%, and 226%. The chart also mentions a placebo and two dosage levels of medication, with percentages labeled as 2.5 and 10 mglkglday. It is unclear what the percentages labeled as "9" and "103 %" refer to.*
This is a chart that shows the percent of patients who improved from baseline pain levels for different doses of pregabalin and placebo. The chart includes values up to 100% improvement in pain and is not providing any additional information on the study or condition being treated.*
* 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.