Novel Simulation and Permutation Methods for the Determination of Temporal Association between Two Events

• US 20140258306A1
• Filed: 10/12/2012
• Published: 09/11/2014
• Est. Priority Date: 10/12/2011
• Status: Abandoned Application

• Current Assignee: Johns Hopkins University
• Original Assignee: Johns Hopkins University
• Inventors: Nunez, Jeanne S., Murakami, Peter, Glen, Daniel
• Application Number:
  US14/351,170
• Publication Number:
  US 20140258306A1
• Time in Patent Office: Days
• US Class Current: 707/741
• CPC Class Codes: A61B 5/0826 Detecting or evaluating apnoea events A61B5/4818 takes precedence
• CPC Class Codes: A61B 5/4211 Diagnosing or evaluating reflux
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass

Abstract

An embodiment in accordance with the present invention provides methods and software for determining an association between two health events, temporally. The methods can be implemented on a computing device either individually, or as a group, and are noted as simulation, permutation shuffling, and permutation sliding. Simulation, permutation shuffling, and permutation sliding each use the comparison of the experimentally found occurrence of association between the two health events to the null distribution of the association statistics, obtained by independently simulating the two health events. In particular, these methods of determining association between two health events can be used for determining an association between reflux and apnea in infants. However, these methods can also be applied more generally to determining a potential relationship between health or other events in the temporal plane.

Claims

1. A method for determining an association between two types of health events during a tested association window size in a patient, using a computer readable medium configured to execute steps comprising:

determining data related to a timing of and a number of occurrences of a first type of health event;

determining data related to a timing of and number of occurrence of a second type of health event;

computing a value for a symptom index for the first type of health event and the second type of health event using a fraction of the number of occurrences of events of the second type occurring within the tested association window size following an event of the first type compared to the total number of events of the second type;

computing a value for a symptom sensitivity index similarly by using a fraction of the number of occurrences of events of the first type occurring within the tested association window size preceding an event of the second type compared to the total number of events of the second type;

using the symptom index value, the symptom sensitivity index value, and a p-value of the symptom index and symptom sensitivity index obtained in simulation and permutation data to determine whether there is an association between the first type of event and the second type of event; and

determining a care and treatment plan for the patient based on whether there is an association between the first type of event and the second type of event.

2. The method of claim 1 wherein the first type of event comprises a reflux event.

3. The method of claim 1 wherein the second type of event comprises one selected from a group consisting of an apnea, cough, and pain events.

4. The method of claim 1 further comprising determining a number of association windows having a predetermined duration.

5. The method of claim 4 further comprising calculating the symptom index, the symptom sensitivity index, and the p-value for each one of the number of association windows.

6. The method of claim 1 further comprising applying the simulation of constraints between events for both types of events.

7. The method of claim 6 further comprising the constraint taking the form of a minimum gap.

8. A method for determining an association between two health events in a patient, using a computer readable medium configured to execute steps comprising:

determining data related to a length of time between occurrences of a first type of health event;

determining data related to a length of time between occurrences of a second type of health event;

computing a value for a symptom index for the first type of health event and the second type of health event using the length of time between occurrences of the first type of health event and the length of time between occurrences of the second type of health event;

computing a value for a symptom sensitive index for the first type of health event and the second type of health event using the length of time between occurrences of the first type of health event and the length of time between occurrences of the second type of health event;

using the symptom index value, the symptom sensitive index value, and a p-value obtained with permutation methods to determine whether there is an association between the first type of event and the second type of event; and

determining a care and treatment plan for the patient based on whether there is an association between the first type of event and the second type of event.

9. The method of claim 8 wherein the first type of event comprises a reflux event.

10. The method of claim 8 wherein the second type of event comprises an apnea event.

11. The method of claim 8 further comprising re-ordering the lengths of time between occurrences of the first type of event and lengths of time between the occurrences of the second type of event a predetermined number of times.

12. The method of claim 11 further comprising calculating the symptom index, the symptom sensitive index, and the p-value for each of the predetermined number of times.

13. The method of claim 8 further comprising shifting the lengths of time between occurrences of the first type of event and lengths of time between occurrences of the second type of event by random amounts for a predetermined number of times.

14. The method of claim 13 further comprising calculating the symptom index, the symptom sensitivity index, and the p-value for each of the predetermined number of times.

15. The method of claim 13 further comprising wrapping-around any length of time between occurrences of the first type of health event and any length of time for the second type of health event that extend beyond an end time.