Product Images Rosuvastatin
View Photos of Packaging, Labels & Appearance
Product Label Images
The following 5 images provide visual information about the product associated with Rosuvastatin NDC 71335-2440 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.
Figure-01 - figure 1
This text provides statistical data on a medical study comparing the effectiveness of RSV treatment versus a placebo. It includes information such as the hazard ratio (HR) with corresponding confidence intervals, p-values, number at risk, and years of observation. The study involves a group of patients taking RSV and another group taking a placebo. The data allows for analysis and comparison of the outcomes between the two groups in terms of event occurrences over time.*
Figure-02 - figure 2
This text provides information on a medical study comparing the effects of Rosuva 20 mg and Placebo 20 mg on various endpoints in a group of 8901 individuals. The study analyzed primary endpoints such as Major Cardiovascular Events (MCE), Cardiovascular death, Nonfatal Stroke, Nonfatal MI, and Hospitalized unstable Angina, as well as Arterial revascularization. Results show hazard ratios, confidence intervals, and p-values for these outcomes, indicating the impact of the medications on each endpoint.*
Figure-02 - figure 3
Label - lbl713352440
This is a description of Rosuvastatin Calcium tablets, each containing 5 mg of the active ingredient. It is important to keep this medication out of reach of children and store it at a temperature of 20° to 25°C (68° to 77°F) to protect it from moisture. The tablets should be dispensed in a child-resistant container and the usual dosage instructions can be found in the package insert.QR codes are provided for prescribing and patient information.*
structural formula - rosuvastatin 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.
