Product Images Maximum Strength Hemorrhoidal Relief

View Photos of Packaging, Labels & Appearance

Product Label Images

The following 2 images provide visual information about the product associated with Maximum Strength Hemorrhoidal Relief NDC 51316-226 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.

Inner Package02 - Inner Package02

Inner Package02 - Inner Package02

This is a description of a hemorrhoid relief cream that contains lidocaine (local anesthetic) for numbing relief. The cream helps to relieve pain, burning, itching, reduce swelling, and to shrink hemorrhoids. The cream is meant for external use only and should not be put in the rectum using fingers or any mechanical device. The package contains 1.06 oz (30 g) of the cream. The drug facts, active ingredients, directions, warnings, and other information about the product are provided on the package. This cream is distributed by CVS Pharmacy, Inc. If you have any questions, you can contact the manufacturer from weekdays 9 AM to 4 PM EST.*

Outer Package02 - Outer Package02

Outer Package02 - Outer Package02

This is a product for hemorrhoidal pain relief. It contains lidocaine 5% as a local anesthetic, vitamin E, and aloe oil. The product aims to shrink hemorrhoidal tissue and provides soothing relief from pain, burning, and itching, which are associated with hemorrhoids and other anorectal disorders. The product should not be used into the rectum or by fingers or any mechanical device. If pregnant or breastfeeding, ask a health professional before use. Keep out of reach of children. The product comes with a 100% money-back guarantee. The inactive ingredients include benzyl alcohol, carbomer 940, cholesterol, isopropyl myristate, mineral oil, polysorbate 80, propylene glycol, purified water, trolamine, and vitamin E.*

* 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.