Method and apparatus for personalized physiologic parameters
First Claim
1. A system for predicting a cardiac event of a patient, the system comprising:
- an adherent device attachable to a patient to electronically measure impedance data from the patient;
an input mechanism for receiving patient descriptive data indicating at least one descriptive characteristic of the patient; and
a processor and a tangible memory readable by the processor;
wherein the memory stores instructions that, when executed by the processor, cause the system to;
receive the impedance data;
establish at least one personalized value for the patient based on the impedance data;
receive patient descriptive data indicating at least one descriptive characteristic of the patient;
establish a predicted impedance specific to the patient, based at least in part on the patient descriptive data; and
generate, based at least in part on the impedance data, the predicted impedance, and the at least one personalized value, a patient event prediction output predictive of a patient cardiac event.
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Accused Products
Abstract
Methods and apparatus combine patient measurement data with demographic or physiological data of the patient to determine an output that can be used to diagnose and treat the patient. A customized output can be determined based the demographics of the patient, physiological data of the patient, and data of a population of patients. In another aspect, patient measurement data is used to predict an impending cardiac event, such as acute decompensated heart failure. At least one personalized value is determined for the patient, and a patient event prediction output is generated based at least in part on the personalized value and the measurement data. For example, bioimpedance data may be used to establish a baseline impedance specific to the patient, and the patient event prediction output generated based in part on the relationship of ongoing impedance measurements to the baseline impedance. Multivariate prediction models may enhance prediction accuracy.
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Citations
19 Claims
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1. A system for predicting a cardiac event of a patient, the system comprising:
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an adherent device attachable to a patient to electronically measure impedance data from the patient; an input mechanism for receiving patient descriptive data indicating at least one descriptive characteristic of the patient; and a processor and a tangible memory readable by the processor; wherein the memory stores instructions that, when executed by the processor, cause the system to; receive the impedance data; establish at least one personalized value for the patient based on the impedance data; receive patient descriptive data indicating at least one descriptive characteristic of the patient; establish a predicted impedance specific to the patient, based at least in part on the patient descriptive data; and generate, based at least in part on the impedance data, the predicted impedance, and the at least one personalized value, a patient event prediction output predictive of a patient cardiac event. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18)
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19. A system for predicting a cardiac event of a patient, the system comprising;
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an adherent device attachable to a patient to electronically measure impedance data from the patient; an input mechanism for receiving patient descriptive data indicating at least one descriptive characteristic of the patient; and a processor and a tangible memory readable by the processor; wherein the memory stores instructions that, when executed by the processor, cause the system to; receive the impedance data; receive patient descriptive data indicating at least one descriptive characteristic of the patient; establish a predicted impedance specific to the patient, based at least in part on the patient descriptive data; establish from the impedance data a baseline impedance specific to the patient; compute an impedance index indicative of a change in the impedance relative to the baseline impedance over time; compare the impedance index with a preselected impedance index threshold; compute an amount of time for which the impedance index has exceeded the impedance index threshold; and generate, based at least in part on the impedance index and the predicted impedance, a patient event prediction output predictive of a patient cardiac event, only if the impedance index has exceeded the impedance index threshold for at least a preselected time.
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Specification