Abstract
Context: For the prevention and management of thromboembolic complications, warfarin is the most extensively recommended anticoagulant. It is categorized as a drug with a narrow therapeutic window. Therefore, warfarin prescription requires special at- tention related to therapeutic drug monitoring. Evidence Acquisition: By categorizing the clinical implications of warfarin, this manuscript aims to provide a comprehensive (albeit somewhat brief) conclusion associated with its pharmacotherapy. The key words relevant to the topic were searched. Con- sequently, articles relevant to the pharmacotherapeutic management of warfarin were selected and reviewed in their entirety. Results: To obtain a reasonable level of stability between the required antithrombotic treatment and the risk of bleeding, an anal- ysis of the literature revealed that the prothrombin time in terms of the international normalized ratio (INR) was found for each individual. The best model for stable warfarin dosage prediction was found to be based on multiple linear regression. Genotype- guided procedures were established to: 1, improve the time in the therapeutic range; 2, reduce time to the first therapeutic INR; and 3, reduce the time for the stable doses. Vitamin K epoxide reductase is an enzyme with an important role in vitamin K metabolism, and warfarin is metabolized in hepatocytes via a monooxygenase, cytochrome P450 2C9. In patients carrying 2C9*1/*2 and 2C9*2/*2 or 2C9*1/*3 alleles, the dose is recommended to be reduced by 18% - 40% and 21% - 49%, respectively. Conclusions: Race, age, body surface area, chronic kidney disease, CYP2C9*3 level, and VKORC1 variants could aect the dose of warfarin. To administer the proper doses of warfarin, patients and physicians might achieve the best results with the pharmacol- ogist proficient anticoagulation database and recommended continuation program. Owing to its' unpredictability, caution must be taken when prescribing warfarin. More advanced warfarin pharmacotherapy studies are recommended based on a linear regres- sion model specifically in the Iranian population.
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