Product Images Potassium Citrate
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Product Label Images
The following 3 images provide visual information about the product associated with Potassium Citrate NDC 72162-2120 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.
structure - Structure
Table 1. - Table 1.
Table 1 shows the effect of Potassium Citrate in patients with Calcium Oxalate Nephrolithiasis. The table presents the number of stones formed per year in different groups of patients. The groups are labeled as Group Baseline, Group I, Group II, Group III, and Group IV. The table also includes the baseline data, the data on treatment, the remission rate, and the percentage of any decrease in stone formation. The total number of patients included in the study is 89. Remission is defined as the percentage of patients remaining free of newly formed stones during treatment.*
Label - lbl721622120
This text appears to be a description of a medication called "Potassium Citrate Extended-Release Tablets, USP 10 mEq." The tablets are uncoated and are capsule-shaped, with a debossed imprint of "T400" on one side and a plain surface on the other side. The tablets are off white to tan yellowish in color. Each tablet contains 10 milliequivalents (mEq) or 1080 milligrams (mg) of potassium citrate. The tablets are labeled with the National Drug Code (NDC) 72162-2120-1. The medication should be stored at a temperature between 20 to 25 degrees Celsius (68 to 77 degrees Fahrenheit), with excursions allowed between 15 to 30 degrees Celsius (59 to 86 degrees Fahrenheit). It should be kept out of the reach of children and dispensed in a tightly closed container with a child-resistant closure. The medication is manufactured by Ascent Pharmaceuticals, Inc. and relabeled by Bryant Ranch Prepack, Inc. at their facility in Burbank, CA, USA.*
* 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.