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  5. Product Images: Atorvastatin Calcium

Product Images Atorvastatin Calcium

View Photos of Packaging, Labels & Appearance

Product Label Images

The following 6 images provide visual information about the product associated with Atorvastatin Calcium NDC 43353-280 by Aphena Pharma Solutions - Tennessee, Llc, 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.

Bottle Label 40 mg - 43353 280 15

Bottle Label 40 mg - 43353 280 15

This is a product description for 15 tablets of Atorvastatin Calcium, with a strength of 40mg. The product code is NOC# 43353028015. No further information is available.*

Aphena Pharma Solutions - TN - Aphena

Aphena Pharma Solutions - TN - Aphena

Chemical Structure - atorvastatin 01

Chemical Structure - atorvastatin 01

Figure 1 - atorvastatin 02

Figure 1 - atorvastatin 02

The text appears to show a graph or chart displaying the cumulative incidence of a certain event over a period of 35 years. The cumulative incidence percentages are listed as 404, 30, and 15. Additionally, there is a HR (hazard ratio) of 0.64 with a confidence interval of 0.50-0.83 and a p-value of 0.0005. Beyond this, the chart also includes a scale ranging from 20-35 years.*

Figure 2 - atorvastatin 03

Figure 2 - atorvastatin 03

This is a statistical analysis report that shows the cumulative hazard percentage over a period of four years. It also includes hazard ratios for the first primary endpoint and their statistical significance. The graph indicates the time to the first primary endpoint over five intervals.*

Figure 3 - atorvastatin 04

Figure 3 - atorvastatin 04

This is a clinical trial result table showing the percentage of subjects who experienced an event while taking either Atorvastatin 10mg or 80mg, along with the hazard ratio and time to the first major cardiovascular endpoint in years.*

* 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.