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 50090-4255 by A-s Medication Solutions, 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.
This appears to be a comparison between two medication treatments, Atenolol and Losartan Potassium, in terms of their effect on the primary endpoint for a study period of 66 months. The adjusted risk reduction for Losartan Potassium was 13% with a p-value of 0.021. The text is accompanied by a graph displaying the study month intervals.*
This is a comparison study between two medications Atenolol and Losartan Potassium. The Adjusted Risk Reduction is 25% with a p-value of 0.001. The percentage of patients with fatal/non-fatal stroke is given over time intervals from 6 to 66 months.*
This is a table showing the results of a study comparing the efficacy of Losartan Potassium and Atenolol in reducing stroke risk in different subgroups of patients. The primary endpoint of the study was the composite of fatal and non-fatal stroke. The table presents the number of events, rates, hazard ratios, and confidence intervals for each subgroup, including age, gender, race, hypertension, diabetes, and history of cardiovascular disease. The symbols in the table are proportional to sample size, and the results show that Losartan Potassium is favored over Atenolol in reducing stroke risk in some subgroups. The analysis was adjusted for baseline Framingham risk score and level of electrocardiographic left ventricular hypertrophy.*
This is a graph showing the percentage of patients with an event for Losartan Potassium and Placebo over 48 months. It also indicates a risk reduction of 16.1% with a p-value of 0.022.*
* 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.