Genomic Opioid Optimization of Dosing and Selections (GOODS) Study
Status: | Recruiting |
---|---|
Conditions: | Hospital |
Therapuetic Areas: | Other |
Healthy: | No |
Age Range: | 18 - 80 |
Updated: | 11/8/2018 |
Start Date: | October 12, 2018 |
End Date: | May 2019 |
Contact: | Carrie King |
Email: | King.Carrie1@mayo.edu |
Phone: | 480-342-6236 |
The researchers are conducting this study to see if pharmacogenomic testing before surgery
helps the doctor to choose which medications will work best for the patient.
helps the doctor to choose which medications will work best for the patient.
Participants, undergoing total knee replacements, will be randomized into two groups. Both
groups will receive pharmacogenomics (PGx) testing preoperatively. The PGx guided group will
have their results reviewed by the clinicians during their treatment and the results may
guide clinical decisions. The control group results will be sealed until completion of
treatment and clinicians will not have access to this information. These participants will
undergo standard treatment dosing and medication selection.
groups will receive pharmacogenomics (PGx) testing preoperatively. The PGx guided group will
have their results reviewed by the clinicians during their treatment and the results may
guide clinical decisions. The control group results will be sealed until completion of
treatment and clinicians will not have access to this information. These participants will
undergo standard treatment dosing and medication selection.
Inclusion Criteria:
- Patients undergoing primary total knee arthroplasty
- Patients must understand and provide written informed consent and HIPAA authorization
prior to initiation of any study-specific procedures.
Exclusion Criteria:
- Patients with a current diagnosis of chronic pain
- Patients requiring narcotics for greater than one week prior to surgery
- Patients with chronic kidney disease with a pre-op creatinine greater than 1.5
- Patient preference or need for spinal anesthesia rather than general anesthesia
- Patient planned for robotic surgical approach
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