Note: This order does NOT come with a consult. Go to "services" to order consultation time if you want one of our experts to discuss your results.
Important: Please send your date of birth to firstname.lastname@example.org so we can enter your lab order as required by the lab company.
The Chronic Disease Temperature (CDT) is a panel of 55 biomarkers. It was developed by a team at Harvard Medical School and MIT. It uses a sophisticated Artificial Intelligence algorithm (patented) to assess your chronic state of health and health risks. Every biomarker in the CDT is a reflection of your early mortality potential and every lab value may be improved through health revival coaching or professional consultation.
Your Chronic Disease Temperature is and important objective step in the discovery of the root-causes of chronic diseases or risks. This panel reveals multiple biomarkers of inflammation and disease. This package includes the CDT labs and a 30 minute consultation with a physician or medical scientist to discuss your results from a chronic disease risk perspective.
An order for your labs at LabCorp will be provided to you after you place your order. Then you go to www.labcorp.com and make an appointment for a blood draw at the time and location of your choosing.
We will receive you lab results within 3 business days. At that time, we will generate our comprehensive Chronic Disease Temperature report and contact you to set up a time for a detailed dive into the health story your blood reveals.
Comprehensive Biomarker Panel - Chronic Disease Temperature -Labs Only
- 55 biometric panel of labs for chronic disease risk and health assessment
- Order a consult separately
- Your “Chronic Disease Temperature” which is a single value that best explains you chronic state of health.
- A detailed, simplified, color-coded lab report that explains how each biomarker identifies major disease categories like Cancer, heart disease, diabetes and neurodegenerative diseases.
- Summary explaining each biomarker
- Chart that shows your values compared to optimal values