Product Images Doxazosin
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Product Label Images
The following 4 images provide visual information about the product associated with Doxazosin NDC 71205-690 by Proficient Rx Lp, 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.
This is the packaging information for Doxazosin tablets, with a strength of 4mg, and a quantity of 30 tablets in each package. The tablets are round, uncoated, and are of a cream to yellow color. Each tablet is debossed with "C4" on one side and has a break line on the other side. The product is packaged and distributed by Proficient Rx in Thousand Oaks, CA. The manufacturer of the tablets is Intas Pharmaceuticals in India. The tablets should be stored at a temperature between 20°-25°C and should be kept out of reach of children. The lot number is 00000 and the expiration date is 000000.*
The text describes a summary table presenting effectiveness data from placebo-controlled trials. The table includes information on maximum flow rate, symptom score, baseline change, and the number of participants in each study. There are three different studies included in the table, each with different dosages of medication and varying lengths of time. Study 2 used a fixed dose for 14 weeks and collected data using a Modified Boyarsiy Questionnaire. The text also notes that the endpoint changed and provides information on the 8 mg dosage of doxazosin. Not enough information is available to determine the specifics of the medication being studied or any results of the trials.*
The text provides data on mean increase in maximum urinary flow rate and mean change in total symptom score from baseline. The treatment duration is indicated in weeks. The data includes placebo and Doxazosin Titration for a maximum of 8 mg. The text also shows statistical significance comparisons between the results and the baseline or placebo.*
* 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.