Product Images Burkhart

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Product Label Images

The following 2 images provide visual information about the product associated with Burkhart NDC 43498-200 by Burkhart Dental Supply 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.

BX.Burkhart .63 Stann Fl Rinse.jpg - BX.Burkhart .63 Stann Fl Rinse

BX.Burkhart .63 Stann Fl Rinse.jpg - BX.Burkhart .63 Stann Fl Rinse

This is a description of a home care fluoride rinse that comes in two flavors: mint and raspberry. The rinse has a 0.63% concentration of stannous fluoride in a concentrated solution that is alcohol-free. The proper use directions should be read prior to use. The product has a net weight of 10 ounces (284g) and is manufactured in the USA for Burkhart Dental Supply. The reorder numbers for each flavor are 72721432 for mint and 72721433 for raspberry.*

LB.Burkhart .63 Stann Fl Rinse_mint.jpg - LB.Burkhart .63 Stann Fl Rinse mint

LB.Burkhart .63 Stann Fl Rinse_mint.jpg - LB.Burkhart .63 Stann Fl Rinse mint

This is a description of an alcohol-free mouth rinse that contains 0.12% w/v fluoride ion (0.63% stannous fluoride concentrate). It is intended to help prevent dental decay (cavity prevention), and control plaque bacteria while increasing protection against tooth sensitivity. It is also aimed at preventing gingivitis. There are warnings pertaining to keeping the rinse out of reach of children and not swallowing it. It is recommended to use the product under the supervision of a dentist and to not eat or drink within 30 minutes after rinsing. The directions give explicit instructions on how to use the product, including mixing it with water, vigorously swishing it between the teeth for 1 minute, and spitting it out. The rinse may cause surface staining of the teeth, but it's not harmful or permanent and may be removed by the dentist.*

* 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.