Product Images Gabapentin
View Photos of Packaging, Labels & Appearance
Product Label Images
The following 7 images provide visual information about the product associated with Gabapentin NDC 58118-3224 by Clinical Solutions Wholesale, Llc, 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.
Gabapentin 400mg Capsules 30ct blister card - gabapentin 100mg 100cap
gabapentin-equation - gabapentin equation
This text provides a formula for estimating creatinine clearance. It involves multiplying the weight in kilograms by the serum creatinine level. For female patients, the calculated value should be further multiplied by 0.85.*
Structure - gabapentin fig 5
gabapentin-fig1 - gabapentin fig1
This text provides information about a study involving a mean pain score, a 4-week dose titration period, and a 4-week fixed dose period. It includes details comparing the placebo group with the group taking Gabapentin at a dosage of 3600 mg/day. The data is related to pain assessments at baseline.*
gabapentin-fig2 - gabapentin fig2
This text provides information on the Mean Pain Score in a study involving different doses of Gabapentin and a placebo over the course of several weeks. The study appears to have a Dose Titration Period and a Fixed Dose Period for each group. The Gabapentin doses mentioned are 1800 mg/day and 2400 mg/day.*
gabapentin-fig3 - gabapentin fig3
This text provides information on the proportion of responders in controlled studies on postherpetic neuralgia (PHN) treated with different doses of GBP (Gabapentin) compared to placebo (PBO). The results suggest that a higher dose of GBP (3600) had a response rate of 29%, compared to only 12% for a lower dose of 1800 and 14% for 2400. The statistical significance of these findings is also indicated (#p<0.001).*
gabapentin-fig4.jpg - gabapentin fig4
* 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.
