Therapeutic decisions systems and method using stochastic techniques

• US 7,351,203 B2
• Filed: 01/18/2005
• Issued: 04/01/2008
• Est. Priority Date: 06/19/2001
• Status: Expired due to Fees

• Current Assignee: University of Southern California
• Original Assignee: University of Southern California
• Inventors: Jelliffe, Roger, Botnen, Andreas, Shoemaker, William, Bayard, David
• Primary Examiner(s): Marmor, II; Charles A.
• Assistant Examiner(s): Mallari; Patricia C.
• Application Number:
  US11/038,828
• Publication Number:
  US 20050143633A1
• Time in Patent Office: 1,169 Days
• Field of Search: 128/923, 128/924
• US Class Current: 600/301
• CPC Class Codes: A61B 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• CPC Class Codes: A61B 5/021 Measuring pressure in heart or blood vessels A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/0537 Measuring body composition by impedance, e.g. tissue hydration or fat content
• CPC Class Codes: A61B 5/1455 using optical sensors, e.g. spectral photometrical oximeters
• CPC Class Codes: A61B 5/1468 using chemical or electrochemical methods, e.g. by polarographic means A61B5/1486 takes precedence
• CPC Class Codes: A61B 5/318 Heart-related electrical modalities, e.g. electrocardiography [ECG]
• CPC Class Codes: A61B 5/412 Detecting or monitoring sepsis
• CPC Class Codes: A61B 5/7275 Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 20/30 relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• CPC Class Codes: G16H 40/67 for remote operation
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients
• CPC Class Codes: Y10S 128/923 by comparison of patient data to other data
• CPC Class Codes: Y10S 128/924 using artificial intelligence

Abstract

Patients are evaluated in terms of various physiological parameters such as hemodynamic parameters. Covariate information indicative of the patient'"'"'s individual characteristics may also be determined. A state variable indicative of the patient'"'"'s characteristics is determined. This state variable is used to compare the patient to other patients in the database. The other patients in the database are evaluated in terms of similar parameters and their probability of survival as well as different treatments and the probability of survival based on those different treatments. The patient may be simply evaluated based on the database or a proper course of treatments may be determined based on the database.

Claims

1. A system comprising:

a monitoring device monitoring a plurality of physiological signals of a current patient;

a database, which stores records indicative of a plurality of patients including at least some of said physiological signals for said plurality of patients and prognosis information for said plurality of patients; and

a processor, that compares said physiological signals of the current patient to said stored records in the database, determines mathematically patients in the database which are most similar to a current patient and selects a treatment from said database which showed a maximum probability of survival for mathematically similar patients to the current patient.

2. A system as in claim 1, wherein said physiological signals include hemodynamic information.

3. A system as in claim 2, wherein said hemodynamic information includes bio impedance information.

4. A system as in claim 2, wherein said hemodynamic information includes temporal patterns within the hemodynamic information.

5. A system as in claim 2, wherein said hemodynamic information includes at least cardiac index, blood pressure, pulse oximetry information, and transcutaneous gas tension.

6. A method, comprising:

monitoring a plurality of physiological signals of a current patient;

comparing said physiological signals of the current patient to stored physiological signals for previous patients stored in a database;

determining patients in said database who are most similar to the current patient; and

selecting a treatment from said database which has a maximum probability of survival for mathematically similar patients.

7. A method as in claim 6, wherein said physiological signals include signals indicative of hemodynamic information.

8. A method as in claim 7, wherein said signals indicative of hemodynamic information include at least cardiac index, blood pressure, pulse oximetry information and transcutaneous gas tension.

9. A method as in claim 6, further comprising obtaining covariate information indicative of a patient'"'"'s individual characteristics, and said determining most similar patients and said determining information is also based on said covariate information.

10. A method as in claim 7, wherein said hemodynamic information includes bio impedance information.

11. A method as in claim 9, wherein said comparing and determining most similar patients includes comparing temporal patterns within the physiological information.

12. A system comprising:

a monitoring device monitoring a plurality of physiological signals of a current patient;

a database, which stores records indicative of a plurality of patients including at least some of said physiological signals for said plurality of patients and prognosis information for said plurality of patients; and

a processor, that compares said physiological signals of the current patient to said stored records in the database, determines mathematically patients in the database which are most similar to a current patient and selects a treatment from said database which showed a maximum probability of survival for mathematically similar patients to the current patient, wherein said processor forms a state vector that includes at least a plurality of times t, with values associated with said times, wherein said values are at least one of said physiological signals and/or at least one treatment carried out at said times, and wherein said state vector is used to select the treatment that maximizes probability of survival based on other patients with similar state vectors.

13. A system as in claim 12, wherein said state vectors include at least one hemodynamic measurement and at least one covariant physiological signal other than said hemodynamic measurement.

14. A system as in claim 12, wherein said processor compares said state vector with values from the database that include times.

15. A system as in claim 12, wherein said processor includes at least one derivative of said values as part of said state vectors.

16. A method, comprising:

monitoring a plurality of physiological signals of a current patient;

comparing said physiological signals of the current patient to stored physiological signals for previous patients stored in a database;

determining patients in said database who are most similar to the current patient; and

selecting a treatment from said database which has a maximum probability of survival for mathematically similar patients, wherein said selecting comprises forming a state vector that includes at least physiological signals, and treatments, as a function of time, and comparing said state vector to comparable information in the database.

17. A method as in claim 16, wherein said state vector also includes derivatives of at least one physiological signal, and further comprising comparing said derivatives to information in the database.