Product Images Losartan Potassium

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Product Label Images

The following 6 images provide visual information about the product associated with Losartan Potassium NDC 71335-1235 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 - lbl713351235

Label - lbl713351235

This is a medication label for Losartan Potassium 100mg tablets produced by Aurobindo Pharma Limited. Losartan is an FDA-approved medication to treat hypertension, commonly marketed under the brand name Cozaar. The tablets are oval-shaped and green with the imprint of "E47." The label provides instructions to store the medication at a room temperature of 20-25°C (68°-77°F) and keep it out of the reach of children. It also includes information on the quantity of tablets and the expiration date.*

Figure1 - losartan fig1

Figure1 - losartan fig1

This appears to be a partial graph or figure, with labels for two medications, Atenolol and Losartan Potassium, followed by the text "Adjusted Risk Reduction: 13%, p=" and a series of numbers indicating months. Without more context or information, it's not clear what the graph or figure is representing or what the significance of the data is.*

Figure2 - losartan fig2

Figure2 - losartan fig2

Figure 3 - losartan fig3

Figure 3 - losartan fig3

Figure 3 shows the primary endpoint events within different demographic subgroups. However, due to the poor quality of the text, it's difficult to interpret specific details.*

Figure-4 - losartan fig4

Figure-4 - losartan fig4

This appears to be a table showing the percentage of patients with an event for two groups (Losttan Potassium and Placebo), along with the Risk Reduction and p-value. It is unclear what the event is, but the Risk Reduction is given as 16.1% with a p-value of 0.022.*

Chemical Structure - losartan str

Chemical Structure - losartan 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.