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 68071-4932 by Nucare 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.

PDP - 68071 4932 9

PDP - 68071 4932 9

This medicine is NuCare P, contains Losartan Potassium 50mg, and comes in a container of 90 tablets. The manufacturer's label should be checked for a full list of ingredients. It requires a prescription and the product number is R1435090. The lot number is 000000 and the expiration date is 00-00. Keep this medicine out of reach of children and store it at a controlled temperature between 59-86°F. Side effects should be reported to the FDA at 1-800-FDA-1088.*

Figure1 - losartan fig1

Figure1 - losartan fig1

Figure2 - losartan fig2

Figure2 - losartan fig2

Figure 3 - losartan fig3

Figure 3 - losartan fig3

This appears to be a table or chart showing results of a study with demographic subgroups and their primary endpoint events. The subgroups include age, gender, race, and history of VD. However, there is no clear information regarding what the primary endpoint events were or what the study was about.*

Figure-4 - losartan fig4

Figure-4 - losartan fig4

This seems to be a part of a clinical trial report comparing the effectiveness of a medication called "Losttan Potassium" with a placebo in reducing the risk of an event in patients. The text provides information on the percentage of patients with the event and the risk reduction observed with Losttan Potassium compared to the placebo. It also includes the p-value of the comparison. Not enough information is provided to infer the specific nature of the event or the study population.*

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.