Product Images Amlodipine Besylate
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Product Label Images
The following 6 images provide visual information about the product associated with Amlodipine Besylate NDC 68071-1924 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.
The text is a label of a medication named Amlodipine Besylate 10mg produced by NuCare Pharmaceuticals, Inc. The medication is packed in a bottle with 90 tablets, and each white or off-white tablet bears the marking "sl 00.00" on one side and "243" on the other. The medication is used to treat high blood pressure, angina (chest pain), and other heart-related conditions. The label contains information about lot number, expiration, manufacturer details, and warnings about the use and storage of the medicine.*
This is a statistical output for an event rate analysis, with a p-value of 0.003 and a hazard ratio of 0.691. The confidence interval is also provided with a range of 95%, which is equal to (0.054, 0.088). There is additional information related to time in months and the medication Amiodipine, but it is not clear how it is related to the statistical output.*
This appears to be a table or chart displaying various patient parameters and their corresponding numbers for a study comparing the effects of Amlodipine versus a Placebo. The parameters include age, gender, baseline sitting SBP, baseline vessel disease, baseline vessels with stenosis, and whether or not the patient received PCI-stent treatment. The Hazard Ratios are also displayed. The description does not contain enough information to determine the context of the study or its results.*
The text provided is not sufficient to generate a useful description. It only contains the name of a company, which is not enough information to provide any insight or understanding about what the company does or offers.*
* 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.