Product Images Maximum Strength Mucus Relief Dm

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Product Label Images

The following 2 images provide visual information about the product associated with Maximum Strength Mucus Relief Dm NDC 49035-956 by Wal-mart Stores, 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.

PACKAGE LABEL-PRINCIPAL DISPLAY PANEL - 1200 mg/60 mg (14 Tablet Carton Label) - guaidextro fig1

PACKAGE LABEL-PRINCIPAL DISPLAY PANEL - 1200 mg/60 mg (14 Tablet Carton Label) - guaidextro fig1

The Equate Mucus Relief DM Extended-Release Tablets contain Guaifenesin and Dextromethorphan Hydrobromide to relieve cough and reduce phlegm. They are intended for adults and children who are 12 years and older. The recommended dose is one tablet every 12 hours, and not more than two tablets in 24 hours. The tablets should not be crushed, chewed, or broken and should be taken with a full glass of water. It is not available whether the tablets are gluten-free or not. The product information also includes warnings, directions, and other information that should be considered before using.*

PACKAGE LABEL-PRINCIPAL DISPLAY PANEL - 1200 mg/60 mg (14 Tablet bottle) - guaidextro fig2

PACKAGE LABEL-PRINCIPAL DISPLAY PANEL - 1200 mg/60 mg (14 Tablet bottle) - guaidextro fig2

This is a drug product called "Mucus Relief" which is an expectorant/cough suppressant. It helps to relieve cough due to minor throat and bronchial irritation as might occur with the common cold or inhaled irritants. Each extended-release tablet contains Dextromethorphan Hycdrobromide USP 60 mg (cough suppressant) and Guaifenesin USP 1200 g (expectorant). The drug should be taken as per the directions noted on the package. The product is distributed by Walmart Inc. and originated from India. For questions or comments, customers can call the number 1-888-287-1915.*

* 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.