Product Images Medi-first Extra Strength Non Aspirin
View Photos of Packaging, Labels & Appearance
Product Label Images
The following 3 images provide visual information about the product associated with Medi-first Extra Strength Non Aspirin NDC 47682-173 by Unifirst First Aid Corporation, 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.
175R MFP Non - 175R MFP Non AspirinXS 90433 rev 2 14 23 Label
This is a drug facts label for a medication containing acetaminophen 500 mg, which is a pain reliever and fever reducer. The label includes directions for use, warnings, and precautions. The medication is not intended for use by young children. The user is advised to consult a doctor or pharmacist before use if they have any medical conditions or are taking any other medications. The label also includes information about the active ingredient compared to Extra Strength Tylenol and lists inactive ingredients.*
175R Medi-First - 175R Medi First Non AspirinXS 80448 rev 2 14 23 Label
MEDI-FIRST Extra Strength is a pain reliever/fever reducer that comes in tamper-evident unit dose packets containing 500 mg of acetaminophen. The package is labeled with drug facts and information in Spanish. The medicine is packaged specially for households without young children. It also has instructions for use, warnings, and other information about the product in both English and Spanish. The product appears to contain 250 tablets (125x2). Contact numbers for the manufacturer are also included.*
175R Medique - 175R Medique APAPXS 17513 2 14 23 Label
This is a description of Acetaminophen 500mg, a pain reliever/fever reducer medication that comes in tablet form and is packaged in tamper-evident unit dose packets. The text also includes information about the medication and its usage, but the quality is poor and difficult to fully interpret.*
* 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.