Product Images Cvs Health Earwax Removal Kit

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Product Label Images

The following 4 images provide visual information about the product associated with Cvs Health Earwax Removal Kit NDC 51316-823 by Cvs Pharmacy, 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.

Box - Box

Box - Box

Component - Component

Component - Component

This is a drug facts label for a product comparable to Debrox® 1, containing 6.5% Carbamide peroxide for earwax removal. The product foams on contact with earwax due to the release of oxygen, with instructions to tilt head sideways and place 5 to 10 drops into the ear. It warns not to use if the safety seal is broken and provides directions for use in the ear only for adults and children over 12 years of age. The user is advised to keep the cap on the bottle when not in use, and if ear irritation or other complications arise, to consult a doctor.*

Component2 - Component2

Component2 - Component2

This is a description of an earwax removal aid product, which contains Peroxide 6.5%. It appears to be a soft and gentle solution for removing earwax buildup. The product comes in a 5 oz (15 ml) container. The text also includes some garbled characters and formatting issues.*

Kit - Kit

Kit - Kit

This text contains important information about an earwax removal kit with the active ingredient Carbamide Peroxide 6.5%. It provides detailed directions on how to use the product, including warnings and precautions. The kit is intended for occasional use to soften and remove excessive earwax. The text also advises users to consult a doctor before use in case of specific conditions and symptoms. The product is safe and gentle for adults and children over 12 years old, with specific instructions for use. It includes details on storage, inactive ingredients, and a customer service number for any questions.*

* 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.