Product Images Cyonanz
View Photos of Packaging, Labels & Appearance
Product Label Images
The following 10 images provide visual information about the product associated with Cyonanz NDC 65862-899 by Aurobindo Pharma Limited, 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.
The text describes a figure depicting Circulatory Disease Mortality Rates per 100,000 Women-Years by Age, Smoking Status, and Oral Contraceptive Use. The figure shows four groups - ZZZever-users who are non-smokers with Synthetic-controls who are smokers, Ever-users who are smokers with EIcontrls who are non-smokers. The mortality rates are represented on the Y-axis, while the age groups (15-24, 25-34, 35-44, 45-54) are represented on the X-axis. The adapted figure is from PM. Layde and V. Beral, ref. #12.*
This is a list of different studies conducted using various cohorts to evaluate the effects of contraceptives on the subjects. The studies have measured the risk ratio (RR) or odds ratio (OR) for ever use or current use of contraceptives in relation to certain health outcomes. The text does not provide any detailed findings or conclusions of the studies.*
Cyonanz™ is an oral contraceptive tablet intended to prevent pregnancy. It contains Norethindrone and Ethinyl Estradiol Tablets, USP at a dosage of 0.5 mg/0.035 mg. It is important to note that the product does not protect against HIV infection (AIDS) and other sexually transmitted diseases. The usual dosage is one tablet daily as prescribed. Keep the product at 20° to 25°C (68° to 77°F) and out of reach of children. Each pouch contains a Summary Patient Pa. Code: TS/DRUGS/22/2009. Made in India.*
The text appears to be a chemical formula of Norethindrone Ethinyl estradiol. Norethindrone Ethinyl estradiol is a medication used as a birth control pill to prevent pregnancy.*
* 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.