Integrated pulmonary index for weaning from mechanical ventilation

• US 9,533,113 B2
• Filed: 12/23/2011
• Issued: 01/03/2017
• Est. Priority Date: 01/04/2007
• Status: Active Grant

• Current Assignee: Oridion Medical 1987 Limited (Medtronic Plc)
• Original Assignee: Oridion Medical 1987 Limited (Medtronic Plc)
• Inventors: Lain, David, Colman, Joshua Lewis, Ronen, Michal, Einav, Sharon
• Primary Examiner(s): Mallari, Patricia
• Assistant Examiner(s): TOTH, KAREN E
• Application Number:
  US13/336,652
• Publication Number:
  US 20120145152A1
• Time in Patent Office: 1,838 Days
• Field of Search: None
• US Class Current: 1/1
• CPC Class Codes: A61B 5/08 Detecting, measuring or recording devices for evaluating the respiratory organs A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/0836 Measuring rate of CO2 production
• CPC Class Codes: A61M 16/0051 with alarm devices
• CPC Class Codes: A61M 16/026 specially adapted for predicting, e.g. for determining an information representative of a flow limitation during a ventilation cycle by using a root square technique or a regression analysis
• CPC Class Codes: A61M 2016/0036 in the breathing tube and used in both inspiratory and expiratory phase
• CPC Class Codes: A61M 2205/505 Touch-screens; Virtual keyboard or keypads; Virtual buttons; Soft keys; Mouse touches
• CPC Class Codes: A61M 2205/584 having a color code
• CPC Class Codes: A61M 2230/06 Heartbeat rate only
• CPC Class Codes: A61M 2230/10 Electroencephalographic signals
• CPC Class Codes: A61M 2230/205 partial oxygen pressure (P-O2)
• CPC Class Codes: A61M 2230/30 Blood pressure A61M2230/04 takes precedence
• CPC Class Codes: A61M 2230/432 partial CO2 pressure (P-CO2)
• CPC Class Codes: G16H 20/30 relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment

Abstract

There is provided herein a system for weaning a patient from mechanical ventilation (MV), the system comprising a ventilation device and a controller comprising an interface module configured to receive two or more measured patient parameters, wherein at least one measured patient parameters parameter comprise a CO₂ related parameter, wherein said controller is further configured to compute an Integrated Pulmonary Index (IPI) value based on the two or more measured patient parameters and to provide a signal to the ventilation device, based on the computed IPI value, wherein said signal adjusts one or more weaning related parameters in said ventilation device.

Claims

1. A system for weaning a patient from mechanical ventilation (MV), the system comprising:

a ventilation device; and

a controller comprising an interface module configured to receive two or more measured patient parameters, wherein at least one of the two or more measured patient parameters comprises a CO₂ related parameter, wherein said controller is further configured to compute an Integrated Pulmonary Index (IPI) value based on the two or more measured patient parameters and to provide a signal to said ventilation device, based on the computed IPI value, wherein said signal adjusts one or more weaning related parameters in said ventilation device;

wherein the IPI is computed by;

(a) characterizing a first measured patient parameter of the two or more measured patient parameters based on a comparison of the first measured patient parameter against a first reference value;

(b) characterizing a second measured patient parameter of the two or more measured patient parameters based on a comparison of the second measured patient parameter against a second reference value; and

(c) computing the IPI value based on values associated with each of the characterized first and second measured patient parameters, wherein a weighting factor applied to the value associated with the second characterized measured patient parameter is influenced by the characterization of the first measured patient parameter.

2. The system according to claim 1, wherein the one or more weaning related parameters comprise:

ventilation volume, ventilation pressure, supplemental oxygen, positive end expiratory pressure (PEEP) or any combination thereof.

3. The system according to claim 1, wherein adjusting one or more weaning related parameters in said ventilation device includes reducing or stopping the mechanical ventilation if the IPI value is at or above a predetermined value or continuing or increasing the support of the mechanical ventilation if the IPI value is below the predetermined value.

4. The system according to claim 1, wherein adjusting one or more weaning related parameters in said ventilation device includes reducing or stopping supplemental oxygenation if the IPI value is at or above a predetermined value or continuing or increasing the supplemental oxygenation if the IPI value is below the predetermined value.

5. The system according to claim 1, wherein adjusting one or more weaning related parameters in said ventilation device includes reducing or stopping positive end expiratory pressure (PEEP) if the IPI value is at or above a predetermined value or continuing or adding PEEP if the IPI value is below the predetermined value.

6. The system according to claim 1, wherein the IPI is in the range of 1 to 10, wherein the higher the IPI value, the better the patient condition is.

7. The system according to claim 1, wherein an increase in the IPI value is indicative of a better chance a patient has for a successful weaning.

8. The system according to claim 1, wherein an increase in the IPI value or stabilization thereof is indicative of a successful weaning process.

9. The system according to claim 1, wherein a decrease in the IPI value is indicative of a deterioration of a patient'"'"'s condition.

10. The system according to claim 1, wherein the controller is further configured to compute a trend of the IPI value and to provide a signal to said ventilation device, based on the trend of the IPI value, wherein said signal adjusts one or more weaning related parameters in said ventilation device.

11. The system according to claim 1, wherein the controller is further configured to compute a reliability index of the [index-value] IPI value.

12. The system according to claim 1, wherein the controller is further configured to provide a medical recommendation regarding weaning from the ventilation machine.

13. The system according to claim 12, further comprising a graphical display configured to display at least one of the IPI value or the recommendation regarding weaning from the ventilation machine.

14. The system according to claim 1, wherein computing the IPI comprises applying a fuzzy logic, a Bayesian network, a decision tree, a neural network, a radial base function, a linear regression model, a non-linear regression model, an expert system, or any combination thereof.

15. The system according to claim 1, wherein computing the IPI comprises averaging the first measured patient parameter[s] over a first period of time and averaging the second measured patient parameter over a second period of time.

16. The system according to claim 15, wherein the period of time is determined based on one or more patient characteristics, on the stability of one or more of the two or more measured patient parameters or both.

17. The system according to claim 1, wherein the two or more measured patient parameters comprise a CO₂ related parameter and one or more measured patient parameters selected from the group consisting of:

another CO₂ related parameter, respiration rate (RR), an O₂ related parameter, heart rate (HR), an electrocardiogram (ECG), an encephalogram (EEG), blood pressure, and spirometry.

18. The system according to claim 1, wherein the CO₂ related parameter comprises a CO₂ waveform related parameter, an expired air CO₂ concentration, respiratory rate or any combination thereof.

19. The system according to claim 18, wherein the CO₂ waveform related parameter comprises EtCO₂, changes in EtCO₂, a slope of the increase in the CO₂ concentration, a change in a slope of the increase in the CO₂ concentration, time to rise to a predetermined percentage of a maximum value of CO₂ concentration, a change in time to rise to a predetermined percentage of a maximum value of CO₂ concentration, an angle of rise to a predetermined percentage of a maximum value of CO₂ concentration, a change in an angle of rise to a predetermined percentage of a maximum value of CO₂ concentration, breath to breath correlation, breath to breath correlation, a CO₂ duty cycle, a change in CO₂ duty cycle or any combination thereof.

20. The system according to claim 1, wherein computing comprises applying a learning process, wherein the learning process increases reliability of the index value.

21. The system according to claim 20, wherein the learning process comprises neural network methods, a support vector machine (SVM), genetic algorithms, simulated annealing, expectation-maximization (EM), case based reasoning, or any combination thereof.

22. The system according to claim 1, wherein computing the IPI is based on the two or more measured patient parameters and on one or more patient characteristics.

23. The system according to claim 22, wherein the one or more patient characteristics comprises age, weight, gender, medical condition, medication, ventilation, oxygen supply, lab tests results, blood pressure, medical history, intubation or any combination thereof.

24. The system according to claim 23, wherein the medical history comprises smoking, heart disease, lung disease, sleep apnea, a pacemaker, or any combination thereof.