Non-cerebral organ autoregulation status determination

1. A method comprising:

receiving, by processing circuitry, a blood pressure signal indicative of a blood pressure of a patient and an oxygen saturation signal indicative of an oxygen saturation of the patient;

determining, by the processing circuitry, a cerebral autoregulation status value based on the blood pressure signal and the oxygen saturation signal;

determining, by the processing circuitry, a non-cerebral autoregulation status value based on the cerebral autoregulation status value and an adjustment value; and

providing, by the processing circuitry and to an output device, a signal indicative of the non-cerebral autoregulation status value and a signal indicative of the cerebral autoregulation status value.

2. The method of claim 1 , further comprising determining, by the processing circuitry, the adjustment value based on a model associating the cerebral autoregulation status value or a predetermined cerebral autoregulation status value with a predetermined non-cerebral autoregulation status value.

3. The method of claim 2 , wherein the model comprises at least one of a physiological model, a population-based model, a neural network algorithm, or a finite element model to associate the cerebral autoregulation status value with the non-cerebral autoregulation status value.

4. The method of claim 1 , wherein the adjustment value is based on a population-based model defining a predetermined association between cerebral autoregulation status values of a population of patients and non-cerebral autoregulation status values of the population of patients.

5. The method of claim 4 , wherein the population-based model comprises demographic data, and wherein determining the adjustment value comprises:

selecting at least one predetermined association based on the demographic data; and

determining the relationship between the cerebral autoregulation status value and the non-cerebral autoregulation status value based on the selected at least one predetermined association.

6. The method of claim 1 , further comprising determining, by the processing circuitry, the adjustment value, wherein determining the adjustment value comprises determining a relationship between the cerebral autoregulation status value and the non-cerebral autoregulation status value using a physiological model based on a predetermined association between the cerebral autoregulation status value of the patient and the non-cerebral autoregulation status value of the patient.

7. The method of claim 1 , further comprising determining, by the processing circuitry, the adjustment value, wherein determining the adjustment value comprises determining a relationship between the cerebral autoregulation status value and the non-cerebral autoregulation status value using a neural network algorithm comprising a plurality of nodes, at least some of the nodes having node parameters, by:

inputting at least the cerebral autoregulation status value into the neural network algorithm;

iteratively evaluating outputs of the neural network algorithm, wherein the outputs comprise a non-cerebral autoregulation status value estimate;

iteratively modifying at least one of the node parameters based on the evaluation of the outputs of the neural network algorithm; and

determining the adjustment value based on the modified neural network algorithm.

8. The method of claim 1 , further comprising determining, by the processing circuitry, the adjustment value, wherein determining the adjustment value comprises determining a relationship between the cerebral autoregulation status value and the non-cerebral autoregulation status value using a finite element model based on a plurality of finite elements configured to model an association between the cerebral autoregulation status value and the non-cerebral autoregulation status value.

9. The method of claim 1 wherein the output device is configured to display via a user interface the non-cerebral autoregulation status and the cerebral autoregulation status.

10. The method of claim 1 , wherein the non-cerebral autoregulation status value comprises at least one of a lower limit of autoregulation or an upper limit of autoregulation.

11. The method of claim 1 , wherein the non-cerebral autoregulation status value comprises a range of non-cerebral autoregulation status values.

12. The method of claim 1 , wherein the non-cerebral autoregulation status value comprises a plurality of non-cerebral autoregulation status values, each indicative of an autoregulation status of an organ or organ system of the patient.

13. The method of claim 1 , wherein the non-cerebral autoregulation status value comprises at least one of a kidney autoregulation status value or a gastrointestinal tract autoregulation status value.

14. The method of claim 1 , wherein the cerebral autoregulation status value comprises at least one of a lower limit of cerebral autoregulation or an upper limit of cerebral autoregulation.

15. A system comprising:

a blood pressure sensor configured to transmit a blood pressure signal indicative of a blood pressure of a patient;

an oxygen saturation sensor configured to transmit an oxygen saturation signal indicative of an oxygen saturation of the patient; and

processing circuitry configured to:

receive the blood pressure signal from the blood pressure sensor;

receive the oxygen saturation signal from the oxygen saturation sensor;

determine a cerebral autoregulation status value based on the blood pressure signal and the oxygen saturation signal;

determine a non-cerebral autoregulation status value based on the cerebral autoregulation status value and an adjustment value; and

provide to an output device a signal indicative of the non-cerebral autoregulation status value and a signal indicative of the cerebral autoregulation status value.

16. The system of claim 15 , wherein the processor is configured to determine the adjustment value based on a model associating the cerebral autoregulation status value or a predetermined cerebral autoregulation status value with a predetermined non-cerebral autoregulation status value.

17. The system of claim 16 , the model comprises at least one of a physiological model, a population-based model, a neural network algorithm, or a finite element model to associate the cerebral autoregulation status value with the non-cerebral autoregulation status value.

18. The system of claim 15 , wherein the adjustment value is based on a population-based model defining a predetermined association between cerebral autoregulation status values of a population of patients and non-cerebral autoregulation status values of the population of patients.

19. The system of claim 18 , wherein the population-based model comprises demographic data, and wherein the processing circuitry is configured to determine the adjustment value by:

selecting at least one predetermined association based on the demographic data; and

determining the relationship between the cerebral autoregulation status value and the non-cerebral autoregulation status value based on the selected at least one predetermined association.

20. The system of claim 15 , wherein the processing circuitry is configured to determine the adjustment value by determining a relationship between the cerebral autoregulation status value and the non-cerebral autoregulation status value using a physiological model based on a predetermined association between the cerebral autoregulation status value of the patient and the non-cerebral autoregulation status value of the patient.

21. The system of claim 15 , wherein the processing circuitry is configured to determine the adjustment value using a neural network algorithm comprising a plurality of nodes, at least some of the nodes having node parameters, by:

inputting at least the cerebral autoregulation status value into the neural network algorithm;

iteratively evaluating outputs of the neural network algorithm, wherein the outputs comprise a non-cerebral autoregulation status value estimate;

iteratively modifying at least one of the node parameters based on the evaluation of the outputs of the neural network algorithm; and

determining the adjustment value based on the modified neural network algorithm.

22. The system of claim 15 , wherein the processing circuitry is configured to determine the adjustment value using a finite element model based on a plurality of finite elements configured to model an association between the cerebral autoregulation status value and the non-cerebral autoregulation status value.

23. The system of claim 15 , wherein the output device is configured to display via a user interface the non-cerebral autoregulation status and the cerebral autoregulation status.

24. The system of claim 15 , wherein the non-cerebral autoregulation status value comprises at least one of a lower limit of autoregulation or an upper limit of autoregulation.

25. The system of claim 15 , wherein the non-cerebral autoregulation status value comprises a range of non-cerebral autoregulation status values.

26. The system of claim 15 , wherein the non-cerebral autoregulation status value comprises a plurality of non-cerebral autoregulation status values, each indicative of an autoregulation status of an organ or organ system of the patient.

27. The system of claim 15 , wherein the non-cerebral autoregulation status value comprises at least one of a kidney autoregulation status value or a gastrointestinal tract autoregulation status value.

28. The system of claim 15 , wherein the cerebral autoregulation status value comprises at least one of a lower limit of cerebral autoregulation or an upper limit of cerebral autoregulation.

29. A non-transitory computer readable storable medium comprising instructions that, when executed, cause processing circuitry to:

receive a blood pressure signal indicative of a blood pressure of a patient and an oxygen saturation signal indicative of an oxygen saturation of the patient;

determine a cerebral autoregulation status value based on the blood pressure signal and the oxygen saturation signal;

determine a non-cerebral autoregulation status value based on the cerebral autoregulation status value and an adjustment value; and

provide to an output device a signal indicative of the non-cerebral autoregulation status value and a signal indicative of the cerebral autoregulation status value.