System and method for generating baseline data for automated management of edema

• US 20070083241A1
• Filed: 12/06/2006
• Published: 04/12/2007
• Est. Priority Date: 07/26/1999
• Status: Active Grant

• Current Assignee: Cardiac Pacemakers Incorporated (Boston Scientific Corporation)
• Original Assignee: Cardiac Pacemakers Incorporated (Boston Scientific Corporation)
• Inventors: Bardy, Gust
• Granted Patent: US 7,837,629 B2
• Time in Patent Office: Days
• US Class Current: 607/3
• CPC Class Codes: A61B 5/0002 Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network A61B5/07 takes precedence; transmission systems for measured values G08C; transmission H04B; transmission of digital information H04L; wireless communication networks H04W
• CPC Class Codes: A61B 5/0031 Implanted circuitry
• CPC Class Codes: A61B 5/4884 inducing physiological or psychological stress, e.g. applications for stress testing
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 20/17 delivered via infusion or injection
• CPC Class Codes: G16H 20/70 relating to mental therapies, e.g. psychological therapy or autogenous training
• CPC Class Codes: G16H 40/40 for the management of medical equipment or devices, e.g. scheduling maintenance or upgrades
• CPC Class Codes: G16H 40/60 for the operation of medical equipment or devices
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment
• CPC Class Codes: Y10S 128/92 Computer assisted medical diagnostics

Abstract

A system and method for generating baseline data for automated management of edema is disclosed. Collected device measures are accumulated to record raw physiometry for a patient, wherein the patient is regularly monitored by an implantable medical device, beginning with an initial observation period. Derived device measures are generated to provide derivative physiometry determined at least in part from the collected device measures. A patient status indicator is determined by analyzing the collected and derived device measures to diagnose a pathophysiology indicative of an absence, onset, progression, regression, and status quo of edema, wherein the collected and derived device measures and the patient status indicator originating from the initial observation period include baseline data.

Claims

1. Stored baseline data for automated management of edema, comprising:

collected device measures to record raw physiometry for a patient, wherein the patient is regularly monitored by an implantable medical device, beginning with an initial observation period;

derived device measures to provide derivative physiometry determined at least in part from the collected device measures; and

a patient status indicator determined through analysis of the collected and derived device measures to diagnose a pathophysiology indicative of an absence, onset, progression, regression, and status quo of edema,

wherein the collected and derived device measures and the patient status indicator originating from the initial observation period comprise baseline data.

2. Stored baseline data according to claim 1, further comprising:

processed data to reflect one or more of;

monitoring data comprising the collected and derived device measures and the patient status indicator for edema;

patient well being data monitored in conjunction with conditions selected from the group comprising heart failure, myocardial ischemia, and high blood pressure; and

programming data to effect therapy modification selected from the group comprising device parameters, drug infusion parameters, and neural stimulation parameters.

3. Stored baseline data according to claim 1, further comprising:

physiometric data processed in conjunction with monitoring of the patient, selected from the group comprising;

analytic data recorded, collected, and stored for edema evaluation;

alert data generated in response to significant events, wherein the alert data is selected from the group comprising absolute measures, long term average measures, and short term average measures; and

action data executed in response to indications selected from the group comprising the significant events, ECG signals, activity level, temperature, pressure, and oxygen saturation.

4. Stored baseline data according to claim 1, further comprising:

physiometric data sensed through one or more of transthoracic impedance, respiratory rate, diurnal cycles, posture, resting, heartbeat cycle, breathing, movement, ECG data, activity level, body position, temperature, heart rate, heart rate variability, heart events, respiration, blood oxygen levels, patient symptoms, and pulmonary or transthoracic edema and local edema-related impedance values.

5. Stored baseline data according to claim 1, further comprising:

programming parameters, comprising at least one of;

monitoring parameters to monitor the patient while asleep; and

exclusion parameters to exclude physiometric data when the patient exhibits an increased respiratory rate due to exercise or activity level.

6. Stored baseline data according to claim 1, further comprising:

trigger conditions with corresponding actions that are executed based upon the direct and derived device measures to cause activation of one or more of a therapy readout, alarm, or change in physiometric data measured,

wherein the trigger conditions are selected from the group comprising absolute measures, pattern matching, absolute differences between averaged measures, and comparisons of a current measure to another current measure or a previous measure.

7. A programmer for generating baseline data for automated management of edema, comprising:

a memory to store device measures received from an implantable medical device, comprising;

collected device measures to record raw physiometry for a patient regularly monitored by the implantable medical device, beginning with an initial observation period; and

derived device measures to provide derivative physiometry determined at least in part from the collected device measures; and

a processor to determine a patient status indicator through analysis of the collected and derived device measures to diagnose a pathophysiology indicative of an absence, onset, progression, regression, and status quo of edema,

wherein the collected and derived device measures and the patient status indicator originating from the initial observation period comprise baseline data.

8. A programmer according to claim 7, wherein the analysis comprises one or more of:

a monitor to accumulate collected device measures and to derive derived device measures for use in determining the patient status indicator for edema;

a patient well being analyzer to monitor patient well being in conjunction with conditions selected from the group comprising heart failure, myocardial ischemia, and high blood pressure; and

a programming interface to apply programming data to effect therapy modification selected from the group comprising device parameters, drug infusion parameters, and neural stimulation parameters.

9. A programmer according to claim 7, further comprising:

an evaluator to process physiometric data conjunction with monitoring of the patient, wherein the physiometric data is selected from the group comprising;

analytic data recorded, collected, and stored for edema evaluation;

alert data generated in response to significant events, wherein the alert data is selected from the group comprising absolute measures, long term average measures, and short term average measures; and

action data executed in response to indications selected from the group comprising the significant events, ECG signals, activity level, temperature, pressure, and oxygen saturation.

10. A programmer according to claim 7, further comprising:

physiometric data sensed through one or more of transthoracic impedance, respiratory rate, diurnal cycles, posture, resting, heartbeat cycle, breathing, movement, ECG data, activity level, body position, temperature, heart rate, heart rate variability, heart events, respiration, blood oxygen levels, patient symptoms, and pulmonary or transthoracic edema and local edema-related impedance values.

11. A programmer according to claim 7, further comprising:

programming parameters, comprising at least one of;

monitoring parameters to monitor the patient while asleep; and

exclusion parameters to exclude physiometric data when the patient exhibits an increased respiratory rate due to exercise or activity level.

12. A programmer according to claim 7, further comprising:

programmed trigger conditions with corresponding actions, wherein the actions are executed by the processor based upon the direct and derived device measures to cause activation of one or more of a therapy readout, alarm, or change in physiometric data measured,

wherein the trigger conditions are selected from the group comprising absolute measures, pattern matching, absolute differences between averaged measures, and comparisons of a current measure to another current measure or a previous measure.

13. An analysis system for generating baseline data for automated management of edema, comprising:

a structured database, comprising;

collected device measures to record raw physiometry for a patient, wherein the patient is regularly monitored by an implantable medical device, beginning with an initial observation period; and

derived device measures to provide derivative physiometry determined at least in part from the collected device measures;

an analyzer to determine a patient status indicator through analysis of the collected and derived device measures to diagnose a pathophysiology indicative of an absence, onset, progression, regression, and status quo of edema; and

a processor to designate the collected and derived device measures and the patient status indicator originating from the initial observation period as baseline data.

14. An analysis system according to claim 13, wherein the structured database organizes processed data to reflect one or more of:

monitoring data comprising collected and derived device measures and a patient status indicator for edema;

patient well being data monitored in conjunction with conditions selected from the group comprising heart failure, myocardial ischemia, and high blood pressure; and

programming data to effect therapy modification selected from the group comprising device parameters, drug infusion parameters, and neural stimulation parameters.

15. An analysis system according to claim 13, wherein the processor processes physiometric data in conjunction with monitoring of the patient, selected from the group comprising:

database management comprising physiometric data recording, collection, and storage for edema evaluation;

alert generation in response to significant events, wherein the alert data is selected from the group comprising absolute measures, long term average measures, and short term average measures; and

action execution in response to indications selected from the group comprising the significant events, ECG signals, activity level, temperature, pressure, and oxygen saturation.

16. An analysis system according to claim 13, further comprising:

physiometric data sensed through one or more of transthoracic impedance, respiratory rate, diurnal cycles, posture, resting, heartbeat cycle, breathing, movement, ECG data, activity level, body position, temperature, heart rate, heart rate variability, heart events, respiration, blood oxygen levels, patient symptoms, and pulmonary or transthoracic edema and local edema-related impedance values.

17. An analysis system according to claim 13, further comprising:

a programming interface to generate programming parameters, comprising at least one of;

monitoring parameters to monitor the patient while asleep; and

exclusion parameters to exclude physiometric data when the patient exhibits an increased respiratory rate due to exercise or activity level.

18. An analysis system according to claim 13, further comprising:

defined trigger conditions with corresponding actions that are executed based upon the direct and derived device measures to cause activation of one or more of a therapy readout, alarm, or change in physiometric data measured,

wherein the trigger conditions are selected from the group comprising absolute measures, pattern matching, absolute differences between averaged measures, and comparisons of a current measure to another current measure or a previous measure.

19. A method for generating baseline data for automated management of edema, comprising:

accumulating collected device measures to record raw physiometry for a patient, wherein the patient is regularly monitored by an implantable medical device, beginning with an initial observation period;

generating derived device measures to provide derivative physiometry determined at least in part from the collected device measures; and

determining a patient status indicator by analyzing the collected and derived device measures to diagnose a pathophysiology indicative of an absence, onset, progression, regression, and status quo of edema,

wherein the collected and derived device measures and the patient status indicator originating from the initial observation period comprise baseline data.

20. A method according to claim 19, further comprising:

processing data, comprising one or more of;

monitoring data comprising collected and derived device measures and a patient status indicator for edema;

monitoring patient well being in conjunction with conditions selected from the group comprising heart failure, myocardial ischemia, and high blood pressure; and

forming programming data to effect therapy modification selected from the group comprising device parameters, drug infusion parameters, and neural stimulation parameters.

21. A method according to claim 19, further comprising:

processing physiometric data in conjunction with monitoring of the patient, selected from the group comprising;

recording, collecting, and storing data for edema evaluation;

generating alerts in response to significant events, wherein the alert data is selected from the group comprising absolute measures, long term average measures, and short term average measures; and

executing actions in response to indications selected from the group comprising the significant events, ECG signals, activity level, temperature, pressure, and oxygen saturation.

22. A method according to claim 19, wherein physiometric data is sensed through one or more of transthoracic impedance, respiratory rate, diurnal cycles, posture, resting, heartbeat cycle, breathing, movement, ECG data, activity level, body position, temperature, heart rate, heart rate variability, heart events, respiration, blood oxygen levels, patient symptoms, and pulmonary or transthoracic edema and local edema-related impedance values.

23. A method according to claim 19, further comprising:

generating programming parameters, comprising at least one of;

defining monitoring parameters to monitor the patient while asleep; and

defining exclusion parameters to exclude physiometric data when the patient exhibits an increased respiratory rate due to exercise or activity level.

24. A method according to claim 19, further comprising:

executing trigger conditions with corresponding actions based upon the direct and derived device measures to cause activation of one or more of a therapy readout, alarm, or change in physiometric data measured,

wherein the trigger conditions are selected from the group comprising absolute measures, pattern matching, absolute differences between averaged measures, and comparisons of a current measure to another current measure or a previous measure.

25. A computer-readable storage medium holding code for performing the method according to claim 19.