Product Images Losartan Potassium
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Product Label Images
The following 7 images provide visual information about the product associated with Losartan Potassium NDC 51655-828 by Northwind Pharmaceuticals, 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.
Losartan Potassium Tablets (100mg) are Rx only medication sold in a pack of 90 tablets. The medication must be stored in its original container at a temperature between 20°- 25°C (68°-77°F). Keep the medication out of children's reach and the container tightly closed. The medication is repackaged by Northwind Pharmaceuticals and contains Indianopolis, IN 46203 in its composition. DOSAGE: See package insert, and the product should be protected from light. The product LOT number is 0000000000, with an expiration date of 00/00/0000, and a GTIN of 00351655828267.*
The given text is showing the results of a study where the adjusted risk reduction is 26% with a p-value of 0.001. The data seems to be presented across different study months and indicates the percentage of patients with first-line or fatal stroke.*
This appears to be a table or figure related to medical data and demographic subsets. It includes information on a primary endpoint composite stroke and fatal/non-fatal events within different demographic groups. The data seems to compare the effectiveness of two different treatments, Losartan and Atancll. However, the text is not very clear and contains a lot of mistakes, making it difficult to understand the specifics of the study. Therefore, a proper description cannot be generated.*
The text appears to be a table with headers "Risk Reduction", "% Patents with Event" and "Months". The table has a single row of data where Risk Reduction is "0022", % Patents with Event is "18.1%", and Months is not available.*
* 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.