Detecting, assessing and managing extreme epileptic events

• US 8,562,523 B2
• Filed: 03/04/2011
• Issued: 10/22/2013
• Est. Priority Date: 03/04/2011
• Status: Active Grant

• Current Assignee: Flint Hills Scientific, LLC
• Original Assignee: Flint Hills Scientific, LLC
• Inventors: Osorio, Ivan
• Primary Examiner(s): Gedeon, Brian T
• Application Number:
  US13/040,996
• Publication Number:
  US 20120226108A1
• Time in Patent Office: 963 Days
• Field of Search: 600/16, 600/17, 600/300, 600/483, 600/509, 600515-519, 607/45
• US Class Current: 600/300
• CPC Class Codes: A61B 5/01 Measuring temperature of body parts ; Diagnostic temperature sensing, e.g. for malignant or inflamed tissue clinical contact thermometers G01K13/20
• CPC Class Codes: A61B 5/021 Measuring pressure in heart or blood vessels A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/024 Detecting, measuring or recording pulse rate or heart rate A61B5/0205, A61B5/021 take precedence
• CPC Class Codes: A61B 5/02405 Determining heart rate variability
• CPC Class Codes: A61B 5/0816 Measuring devices for examining respiratory frequency measuring frequency of electric signals G01R23/00
• CPC Class Codes: A61B 5/318 Heart-related electrical modalities, e.g. electrocardiography [ECG]
• CPC Class Codes: A61B 5/4094 Diagnosing or monitoring seizure diseases, e.g. epilepsy
• CPC Class Codes: A61F 7/10 Cooling bags, e.g. ice-bags
• CPC Class Codes: A61N 1/36064 Epilepsy
• CPC Class Codes: A61N 1/36139 with automatic adjustment
• CPC Class Codes: A61N 1/37258 Alerting the patient
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment

Abstract

Methods and apparatus for identifying an extreme epileptic state/event in a patient are provided. One method includes determining at least one of an autonomic index, a neurologic index, a metabolic index, an endocrine index, or a tissue stress index, where at least one determined index is based upon body data. The method also includes identifying a seizure event based upon the at least one determined index and determining at least one seizure severity index (SSI) value indicative of the severity of the seizure event. The method further includes comparing the determined at least one SSI value to at least one reference value and identifying an occurrence of an extreme seizure event, based upon the comparison of the determined SSI value to the at least one reference value.

Claims

1. A method for identifying an extreme seizure event in a patient, comprising:

determining at least one of an autonomic index, a neurologic index, a metabolic index, an endocrine index, or a tissue stress index, said at least one determined index being based upon body data;

identifying a seizure event based upon said at least one determined index;

determining at least one seizure severity index (SSI) value indicative of the severity of said seizure event;

comparing said determined at least one SSI value to at least one reference value; and

identifying an occurrence of an extreme seizure event, based upon the comparison of said determined SSI value to said at least one reference value.

2. The method of claim 1, further comprising performing at least one action in response to identifying the occurrence of an extreme seizure event, said action comprising at least one of:

setting a first flag indicative of said extreme seizure event;

providing a first signal indicative of said extreme seizure event;

providing a therapy to treat said extreme seizure event;

issuing a warning in response to said identifying based upon at least one of;

said comparing of said determined at least one SSI value to said at least one of a reference value, comparing the determined at least one SSI value to at least one extreme reference value, and providing said first signal indicative of said extreme seizure event if said first signal is provided;

initiating a logging sequence of said extreme seizure event; and

initiating a reporting sequence for said extreme seizure event.

3. The method of claim 2, wherein said logging sequence further comprises at least one of:

storing at least one of said SSI value, a start time of said extreme seizure event, an end time of said extreme seizure event, a duration of said extreme seizure event, a time of providing said therapy, the type of said therapy, an outcome of said therapy and a time of issuing said warning into a memory of at least one of a medical device and a database operatively coupled to said medical device;

storing at least one of a ranking of the SSI value and a characterization of the SSI value compared to at least one SSI value for a prior seizure event; and

storing an activity signal indicative of the patient'"'"'s activity state during a time period proximate to said seizure event.

4. The method of claim 2, wherein providing a therapy comprises providing at least one of an electrical therapy, a chemical therapy, or a thermal therapy to treat said extreme seizure event, and a supportive treatment comprising at least one of providing fluids, intubation, body cooling, brain cooling, providing oxygen, or providing non-seizure drugs to said patient.

5. The method of claim 2, further comprising:

initiating an extreme seizure event confirmation of said identifying an occurrence of an extreme seizure event;

receiving a response to said initiating; and

performing at least one of;

providing a second signal adapted to confirm or negate the extreme seizure event determination;

setting a second flag confirming the extreme seizure event if the response to said requesting indicates that the patient is having an extreme seizure event;

or

deactivating the first flag if the response indicates that the patient is not having an extreme seizure event.

6. The method of claim 1 further comprising performing at least one of ranking the identified extreme seizure event in reference to at least one prior extreme event or determining the time elapsed since at least one of a plurality of prior extreme seizure events.

7. The method of claim 6 further comprising identifying a time spent in a state of an extreme seizure event over a time window, wherein the time window is at least one of a microscopic, a mesoscopic or a macroscopic time window.

8. The method of claim 1, wherein said at least one reference value is one of an extreme reference value and a non-extreme reference value;

and

wherein said at least one reference value is selected from the group consisting of a cardiac value, a respiratory value, a kinetic value, a responsiveness value or an awareness value.

9. The method of claim 8, wherein said at least one reference value is at least one of a measure of central tendency, a graphical analysis, a distribution analysis, or a statistical analysis, over at least one of a microscopic, a mesoscopic or a macroscopic time window.

10. The method of claim 8, wherein an extreme reference value is at least one of:

a value above the ninetieth percentile of a plurality of SSI values over a first time period; and

a value beyond 2.5 standard deviations to the right or left of the mean for a normal or a normalized distribution.

11. The method of claim 1, wherein said extreme seizure event comprises at least one of a status epilepticus event or a pathophysiological effect resulting from an extreme epileptic state, the pathophysiological effect being selected from the group consisting of:

damage to brain tissue resulting in permanent/serious motor/visual/sensory/cognitive skills;

respiratory failure, cardiac failure, pulmonary edema, cardiac arrhythmia, arterial blood acidosis, liver/renal failure, bed sores, bone fractures, abrasions, bruises, organ failure, multi-organ failure, arterial hypertension, tissue hypoxia and tissue acidosis.

12. The method of claim 1, further comprising:

determining if there is an elevated risk of sudden death in response to identifying an occurrence of said extreme seizure event; and

issuing a warning of an elevated risk of sudden death in response to said determining that there is a an elevated risk of sudden death.

13. The method of claim 12, further comprising determining at least one of a risk of or a presence of at least one of decreasing heart rate variability (HRV), ST complex elevation, QT elongation, multi-focal premature ventricular contraction (PVC), ventricular tachycardia, ventricular fibrillation, or respiratory failure.

14. The method of claim 1, wherein said at least one SSI value is based upon at least one data set of seizure metric data related to a seizure event, said seizure metric data relating to a time period, wherein said at least one data set of seizure metric data is based at least upon said body data.

15. The method of claim 1, further comprising:

determining at least one of a quality of life index or a physical fitness/integrity index;

identifying a seizure impact on a patient based upon at least one of the quality of life index or the physical fitness/integrity index; and

performing at least one of;

reporting the identified seizure impact;

logging the identified seizure impact; and

treating the patient based at least upon the identified seizure impact.

16. An apparatus, comprising:

a determination component adapted to;

determine at least one of an autonomic index, a neurologic index, a metabolic index, an endocrine index, or a tissue stress index, said at least one determined index being based upon body data;

identify a seizure event based upon said at least one determined index;

determine a seizure severity index (SSI) value indicative of the severity of said seizure event;

compare the determined SSI value to at least one reference value; and

identify an occurrence of an extreme epileptic event, based upon the comparison of said determined SSI value to said at least one reference value.

17. The apparatus of claim 16, wherein said determination component further comprises at least one of:

a controller, said controller being adapted to;

control one or more operations of said apparatus;

process at least one of internal data or external data, said at least one of internal data or external data being associated with identifying an occurrence of an extreme epileptic event;

store data, said data comprising at least one of internal data, external data or processed data;

set a flag indicative of said extreme epileptic event;

provide a signal indicative of said extreme epileptic event;

provide a therapy based upon said extreme epileptic event;

issue a warning based upon said signal indicative of said extreme epileptic event;

determine a ranking of said extreme epileptic event compared to one or more previous extreme epileptic events;

initiate at least one of a logging sequence and a reporting sequence related to said extreme epileptic event; and

transmit a stored portion of data related to said extreme epileptic event to at least one of an external device or an external entity;

a memory adapted to;

store said data, said data comprising at least one of internal data, external data or processed data;

store said warning;

store said ranking; and

store a value indicative of the time spent in an extreme epileptic event;

a seizure determination module for detecting a seizure and determining at least one characteristic of the detected seizure;

a seizure severity index (SSI) unit to determine a value of an SSI;

or

an extreme epileptic event unit adapted to perform at least one of determining the presence of an extreme epileptic event or quantifying a risk of an extreme epileptic event.

18. The apparatus of claim 17, wherein said extreme epileptic event comprises an extreme epileptic event selected from the group consisting of a present status epilepticus state, or an increased risk of a status epilepticus state.

19. The apparatus of claim 16, wherein said at least one SSI value is based upon at least one data set of seizure metric data related to a seizure event, said seizure dataset related to a time period, wherein said at least one data set of seizure metric data is based at least upon said body data.

20. A non-transitive, computer-readable storage device for storing instructions that, when executed by a processor, perform a method for identifying an extreme seizure event in a patient, comprising:

determining at least one of an autonomic index, a neurologic index, a metabolic index, an endocrine index, or a tissue stress index, said at least one determined index being based upon body data;

identifying a seizure event based upon said at least one determined index;

determining at least one seizure severity index (SSI) value indicative of the severity of said seizure event;

comparing said determined at least one SSI value to at least one reference value; and

identifying an occurrence of an extreme seizure event, based upon the comparison of said determined SSI value to said at least one reference value.

21. A non-transitive, computer-readable storage device for storing instructions that, when executed by a processor, perform the method as in claim 20 for identifying an extreme seizure event in a patient, wherein said at least one SSI value is based upon at least one data set of seizure metric data related to a seizure event, said seizure event occurring during a time period, wherein said at least one data set of seizure metric data is based at least upon said body data.

22. A method for identifying an extreme seizure event in a patient, comprising:

determining at least one of an autonomic index, a neurologic index, a metabolic index, an endocrine index, or a tissue stress index, said indices being based upon body data;

identifying at least two seizure events based upon said at least one determined index;

determining at least one seizure severity index (SSI) value related to at least one of said at least two seizure events;

determining at least one inter-seizure interval (ISI) value related to said at least two seizure events; and

identifying an occurrence of a state of status epilepticus in the patient, based upon said determined SSI value and said determined ISI value.

23. The method of claim 22, further comprising performing at least one action in response to identifying the occurrence of a state of status epilepticus, said action comprising at least one of:

setting a first flag indicative of said state of status epilepticus;

providing a signal indicative of said state of status epilepticus;

providing a therapy to treat said state of status epilepticus;

issuing a warning in response to said identifying based upon at least one of said determined SSI value and said ISI value, or in response to said signal indicative of said state of status epilepticus if said signal is provided;

initiating a logging sequence of said state of status epilepticus; and

initiating a reporting sequence for said state of status epilepticus.

24. The method of claim 23, wherein said logging sequence further comprises at least one of:

storing at least one of said SSI value, said ISI value, a start time of said state of status epilepticus, an end time of said state of status epilepticus, a duration of said state of status epilepticus, a time of providing said therapy, and a time of issuing said warning into a memory;

storing at least one of;

at least one of a ranking or a characterization of the SSI value compared to at least one SSI value for a prior seizure event;

or

at least one of a ranking or a characterization of the ISI value compared to at least one ISI value for a prior seizure event;

or

storing the time spent in a state of status epilepticus.

25. The method of claim 23, wherein providing a therapy comprises providing at least one of an electrical therapy, or a drug therapy, a drug to treat said extreme seizure event, and a supportive treatment comprising at least one of providing fluids, intubation, body cooling, brain cooling, providing oxygen, or providing non-seizure drugs to said patient.

26. The method of claim 23, further comprising:

initiating a status epilepticus state confirmation of said identifying an occurrence of a state of status epilepticus;

receiving a response to said initiating; and

performing at least one of;

providing a second signal adapted to confirm or negate the status epilepticus determination;

setting a second flag confirming the state of status epilepticus if the response to said requesting indicates that the patient is in a state of status epilepticus;

or

deactivating the first flag if the response indicates that the patient is not in a state of status epilepticus.

27. The method of claim 22 further comprising identifying at least one of a time spent in a state of status epilepticus over a time window and a duration of a state of status epilepticus, said duration being based on said start time of said state of status epilepticus and said end time of said state of status epilepticus.

28. The method of claim 25, further comprising:

determining a risk of death in response to identifying an occurrence of said state of status epilepticus;

issuing a warning of a risk of death in response to determining the risk of death; and

increasing said provided therapy in response to determining the risk of death.

29. The method of claim 25, wherein determining at least one of a risk of or a presence of at least one of decreasing heart rate variability (HRV), ST complex elevation, QT elongation, multi-focal premature ventricular contraction (PVC), ventricular tachycardia, ventricular fibrillation, pulmonary hypertension, or respiratory distress syndrome.