Cardiovascular disease risk assessment systems and uses thereof
AssigneeUniversity of Connecticut
InventorsBeiyan Zhou, Chuan Li
Life of this patent
Estimating the term…
Abstract
Disclosed herein are systems and methods for effectively predicting cardiovascular disease risk in people with normal lipid profiles and/or in people undergoing lipid management therapy. Genetic information obtained from a patient may be characterized. A logistic regression model may be applied to the characterized genetic information to estimate a probability of a cardiovascular event by the patient.
Claims25
A method of predicting metabolic risk of a patient, comprising:
- characterizing, based on an expression pattern associated with inflammatory foaming macrophage activity of the patient, genetic information obtained from sequencing data of monocytes of the patient;
- determining, based on an application of a predictive model to the characterized genetic information, a probability of a metabolic event by the patient;
- and
- causing, based on the sequencing data and the probability of the metabolic event by the patient, a treatment of the patient.
(canceled)
(canceled)
A computer system for predicting a metabolic risk of a patient, comprising:
- a data source configured to provide sequencing data of monocytes obtained from the patient;
- and
- a processor in communication with the data source, wherein the processor is configured to:
- characterize genetic information obtained from the sequencing data based an expression pattern associated with inflammatory foaming macrophage activity of the patient;
- determine a probability of a metabolic event by the patient based on an application of a predictive model to the characterized genetic information;
- and
- cause a treatment of the patient based on the sequencing data and the probability of the metabolic event by the patient.
(canceled)
(canceled)
(canceled)
An apparatus for predicting a metabolic risk of a patient, comprising:
- one or more processors;
- and
- a memory storing processor-executable instructions that, when executed by the one or more processors, cause the apparatus to:
- characterize, based on an expression pattern associated with inflammatory foaming macrophage activity of the patient, genetic information obtained from sequencing data of monocytes of the patient;
- determine, based on an application of a predictive model to the characterized genetic information, a probability of a metabolic event by the patient;
- and
- cause, based on the sequencing data and the probability of the metabolic event by the patient, a treatment of the patient.
Dependencies are inferred from the claim text.