Product Images Atorvastatin Calcium

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Product Label Images

The following 5 images provide visual information about the product associated with Atorvastatin Calcium NDC 43063-496 by Pd-rx Pharmaceuticals, Inc., 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.

43063496 Label - 43063496

43063496 Label - 43063496

This is a medication package of Atorvastatin Calcium tablets, USP equivalent to 20 mg of Atorvastatin. The package contains 30 tablets with an expiry date of 12/2020 and lot number J19E93. The dosage information for the medicine is not provided here and should be checked in the package insert. The package contains a warning to keep the medicine out of children's reach and a recommendation to contact a doctor in case of side effects. The medicine is marked with the identifier APD ATV 20 and belongs to GTIN: 00343063496305.*

Figure-01 - Figure 01

Figure-01 - Figure 01

Figure-02 - Figure 02

Figure-02 - Figure 02

The available text seems to be a part of some statistical analysis report related to medical treatment. Based on the text, the cumulative hazard percentage is given for two cases: "Placeho" (which can be understood as "Placebo" with some missing or -related errors) and "Atorvastatin". The value of Hazard Ratio (HR) is given as 0.53 (with a 95% confidence interval between 0.45 and 0.83) for the case of Atorvastatin. The time duration of four years is mentioned. However, the description and purpose of the analysis cannot be inferred clearly from the given text.*

Figure-03 - Figure 03

Figure-03 - Figure 03

The text appears to be a table with some numbers and medication names mentioned, along with a reference to some cardiovascular endpoint. Not much context is available to provide a useful description.*

chemical-structure - chemical structure

chemical-structure - chemical structure

* 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.