Product Images Amlodipine Besylate
View Photos of Packaging, Labels & Appearance
Product Label Images
The following 4 images provide visual information about the product associated with Amlodipine Besylate NDC 53808-1029 by State Of Florida Doh Central 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.
Label Image for 5mg - Qualitest
This is a description of a medication called Amlodipine Besylate which comes in 5mg tablets. The quantity is 30 and it is only available with a prescription. It has a lot number of LOTT010D138 and a package number of 0210201463. Its expiration date is 08-10-2014 and it was packaged by DOH Central Pharmacy in Tallahassee, FL 32304. It also has a UPC number of 306032100288.*
This is an image of the structural formula for Amlodipine Besylate. - amlodusp 1
Figure 1 - Kaplan-Meier Analysis of Composite Clinical Outcomes for Amlodipine versus Placebo - amlodusp 2
This appears to be a table or graph displaying the event rate, p-value, hazard ratio, and confidence interval for a drug called Amlodipine. It also shows a time frame in months. It is not clear what kind of event is being measured or what the numbers represent without additional context.*
Figure 2 - Effects on Primary Endpoint of Amlodipine versus Placebo across Sub-Groups - amlodusp 3
This text appears to show the results of a study comparing the effects of Amlodipine against a placebo in patients with various characteristics such as age, gender, and baseline blood pressure. Other characteristics such as the presence of vessel disease or stenosis are also mentioned. The text contains various tables and statistics related to the study results, including hazard ratios with confidence intervals. Overall, it seems to be a clinical report or research paper, but without further context, it is difficult to say more.*
* 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.