Product Images Ramipril

View Photos of Packaging, Labels & Appearance

Product Label Images

The following 4 images provide visual information about the product associated with Ramipril NDC 71335-1057 by Bryant Ranch Prepack, 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 - lbl713351057

Label - lbl713351057

This is a description of a medication called Ramipril 5mg. It comes in the form of a red capsule and is stored at room temperature. It is similar to a drug called Altace 5mg Capsule. The medication is produced by a company called Rising Health LLC. The prescription comes in a bottle of 30 capsules and has an expiration date indicated by MM/YY. The National Drug Code number for this medication is 7133510671 01254301523487.*

Figure 1 - ramipril fig1

Figure 1 - ramipril fig1

This appears to be a chart or graph that shows the proportion of patients taking Ramipril over time (from 0 to 1500 days of follow-up) as well as a statistical significance (P-value) of 0.0001. However, without additional context or labels, it is difficult to provide a more specific description of the data presented.*

Figure 2 - ramipril fig2

Figure 2 - ramipril fig2

This text represents a table showing the incidence and relative risk of cardiovascular disease, diabetes, age, sex, hypertension, history of coronary artery disease, prior myocardial infraction, cerebrovascular disease, peripheral vascular disease, and microalbuminuria in different groups of patients. The table includes the number of patients in each group and the incidence of the composite outcome in the placebo group. The relative risk in the ramipril group with a 95% confidence interval is also included. No further information is available.*

Chemical Structure - ramipril str

Chemical Structure - ramipril str

* 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.