Method for presenting thrombosis and hemostasis assay data

• US 6,502,040 B2
• Filed: 06/30/1999
• Issued: 12/31/2002
• Est. Priority Date: 12/31/1997
• Status: Expired due to Fees

• Current Assignee: Biomerieux B.V. (Compagnie Merieux Alliance SAS)
• Original Assignee: Biomerieux Incorporated (Compagnie Merieux Alliance SAS)
• Inventors: Beck, Lisa, Givens, Thomas, Braun, Paul
• Primary Examiner(s): WACHSMAN, HAL D
• Application Number:
  US09/345,080
• Publication Number:
  US 20020010553A1
• Time in Patent Office: 1,280 Days
• Field of Search: 702/22, 702/23, 702/27-32, 702/128, 702/131, 702/139, 702/179, 702/180, 702/183, 702/FOR-115, 702/FOR.17, 702/FOR.171, 702/FOR.131, 700/266, 700/268, 73/644.3, 436/66, 436/43, 436/47-50, 436/54, 436/55, 436/69, 436/174, 436/164, 436/171, 436/180, 436/805, 422/50, 422/61-67, 422/68.1, 422/73, 422/82.05, 382/133, 382/134, 382/156-159, 356/39, 356/40, 356/42, 706/924, 706/21, 706/20, 435/13, 377/10, 377/11, 703/6, 703/9, 703/11, 703/12
• US Class Current: 702/22
• CPC Class Codes: G01N 2800/226 Thrombotic disorders, i.e. thrombo-embolism irrespective of location/organ involved, e.g. renal vein thrombosis, venous thrombosis
• CPC Class Codes: G01N 2800/385 Congenital anomalies
• CPC Class Codes: G01N 33/4905 Determining clotting time of blood by chemical methods G01N33/86, C12Q1/54
• CPC Class Codes: G01N 33/86 involving blood coagulating time or factors, or their receptors
• CPC Class Codes: G16H 10/40 for data related to laboratory analysis, e.g. patient specimen analysis
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 70/60 relating to pathologies

Abstract

A method for presenting relationships between data from a thrombosis-hemostasis assay on an unknown sample and data from a purality of assays on known samples, which can be in the form of a topological feature map wherein spatial locations within the map correspond to intrinsic features of the known samples. The position of the unknown sample is superimposed on the positions of the known samples. An alternative presentation is showing the distance of each of a purality of predictor variables from an unknown sample to the mean values of a known population.

Claims

1. A method for presenting the relationship between data from an assay relating to thrombosis-hemostasis on an unknown sample, and data from a plurality of assays relating to thrombosis-hemostasis from known sample populations comprising:

(a) providing data from at least one time-dependent measurement for each of a purality of known blood samples;

(b) measuring a property over time to derive at least one time-dependent measurement on an unknown blood sample;

(c) transforming data from steps (a) and (b) to at least one predictor variable which captures information content of both the unknown blood sample'"'"'s at least one time-dependent measurement and the at least one time-dependent measurement for each of said plurality of known blood samples;

(d) creating a topological feature map of the at least one predictor variable from step (c) of the plurality of known blood samples in step (a) whose spatial locations within the topological feature map correspond to intrinsic features of the at least one predictor variable;

(e) determining the position on the topological feature map of the unknown blood sample corresponding to the unknown blood sample'"'"'s at least one predictor variable; and

(f) presenting the position of the unknown blood sample and the positions of the plurality of known samples used to create the map in step (d) on the map created in step (d).

2. The method according to claim 1, wherein in step (c), data from the at least one time-dependent measurement in steps (a) and (b) is transformed into at least one predictor variable that characterizes timing, rate and/or magnitude of changes over time during the at least one time-dependent measurement of steps (a) and (b).

3. The method according to claim 2, wherein said at least one predictor variable in step (c) includes a minimum of the first derivative of the at least one time-dependent measurement.

4. The method according to claim 2, wherein said at least one predictor variable in step (c) includes a time index of the minimum of the first derivative of the at least one time-dependent measurement.

5. The method according to claim 2, wherein said at least one predictor variable in step (c) includes a minimum of the second derivative of the at least one time-dependent measurement.

6. The method according to claim 2, wherein said at least one predictor variable in step (c) includes a time index of the minimum of the second derivative of the at least one time-dependent measurement.

7. The method according to claim 2, wherein said at least one predictor variable in step (c) includes a maximum of the second derivative of the at least one time-dependent measurement.

8. The method according to claim 2, wherein said at least one predictor variable in step (c) includes a time index of the maximum of the second derivative of the at least one time-dependent measurement.

9. The method according to claim 2, wherein said at least one predictor variable in step (c) includes an overall change in the at least one time-dependent measurement.

10. The method according to claim 2, wherein said at least one predictor variable in step (c) includes a clotting time.

11. The method according to claim 2, wherein said at least one predictor variable in step (c) includes a slope of the at least one time-dependent measurement prior to clot formation.

12. The method according to claim 2, wherein said at least one predictor variable in step (c) includes a slope of the at least one time-dependent measurement after clot formation.

13. The method according to claim 1, wherein said plurality of known blood samples and said unknown blood samples are samples of whole blood or plasma.

14. The method according to claim 1, wherein said plurality of known blood samples are samples of which information is known relating to one or more intrinsic or extrinsic clotting factors and/or therapeutic agents, or are normal samples.

15. The method according to claim 1, wherein said at least one time-dependent measurement comprises at least one time-dependent measurement from a prothrombin time assay.

16. The method according to claim 1, wherein said at least one time-dependent measurement comprises at least one time-dependent measurement from an activated partial thromboplastin time assay.

17. The method according to claim 1, wherein at least one of said at least one time-dependent measurement consists of an optical measurement.

18. The method according to claim 17, wherein said optical measurement correspond to changes in light scattering and/or light absorption.

19. A method according to claim 1, wherein in addition to the at least one predictor variable in step (c), additional patient medical data associated with each blood sample is used for creating the topological feature map.

20. The method according to claim 1, wherein in steps (a) and (b), a plurality of assays relating to thrombosis-hemostasis are performed to provide said at least one time-dependent measurement of step (a) and (b).

21. The method according to claim 1, wherein a plurality of topological feature maps are provided for presenting data in step (f).

22. A method according to claim 1, wherein said at least one time-dependent measurement in steps (a) and (b) is provided by an automated analyzer for thrombosis and hemostasis testing.

23. A method according to claim 22, wherein a plurality of optical measurements are made at multiple wavelengths.

24. A method according to claim 22, wherein at least one time-dependent measurement is provided automatically by said automated analyzer, and the unknown blood sample is automatically removed by an automated probe from a sample container to a test well, one or more reagents are automatically added to the test well to initiate property changes over time within said blood sample, and the development of changes over time is automatically monitored to derive a time-dependent measurement.

25. A method according to claim 22, wherein after step (e), the position of the unknown blood sample on the map is stored in a memory of said automated analyzer and/or displayed on said automated analyzer.

26. A method for presenting the relationship between data from an assay relating to thrombosis-hemostasis on an unknown sample, and data from a plurality of assays relating to thrombosis-hemostasis from known sample populations comprising:

(a) providing data from at least one time-dependent measurement for each of a plurality of known blood samples;

(b) measuring a respective property over time to derive data comprising at least one time-dependent measurement on an unknown blood sample;

(c) transforming data from steps (a) and (b) to at least one predictor variable which captures information content of both the unknown blood sample'"'"'s at least one time-dependent measurement and the at least one time-dependent measurement for each of said plurality of known blood samples;

(d) computing the standard deviation for each predictor variable in step (c) of the plurality of known blood samples in step (a)

(e) determining the z-score of the unknown blood sample in (b) for each predictor variable, and determining if one or more of the z-scores for the unknown blood sample is greater than a predetermined limit, signifying that the unknown blood sample is different from the plurality of known blood samples represented by the at least one predictor variable.

27. The method according to claim 26, wherein in step (c), data from the at least one time-dependent measurement in steps (a) and (b) is transformed into at least one predictor variable that characterizes timing, rate and/or magnitude of changes during the at least one time-dependent measurement in steps (a) and (b).

28. The method according to claim 27, wherein said at least one predictor variable in step (c) includes a minimum of the first derivative of the at least one time-dependent measurement.

29. The method according to claim 27, wherein said at least one predictor variable in step (c) includes a time index of the minimum of the first derivative of the at least one time-dependent measurement.

30. The method according to claim 27, wherein said at least one predictor variable in step (c) includes a minimum of the second derivative of the at least one time-dependent measurement.

31. The method according to claim 27, wherein said at least one predictor variable in step (c) includes a time index of the minimum of the second derivative of the at least one time-dependent measurement.

32. The method according to claim 27, wherein said at least one predictor variable in step (c) includes a maximum of the second derivative of the at least one time-dependent measurement.

33. The method according to claim 27, wherein said at least one predictor variable in step (c) includes a time index of the maximum of the second derivative of the at least one time-dependent measurement.

34. The method according to claim 27, wherein said at least one predictor variable in step (c) includes an overall change in the at least one time-dependent measurement.

35. The method according to claim 27, wherein said at least one predictor variable in step (c) includes a clotting time.

36. The method according to claim 27, wherein said at least one predictor variable in step (c) includes a slope of the at least one time-dependent measurement prior to clot formation.

37. The method according to claim 27, wherein said at least one predictor variable in step (c) includes a slope of the at least one time-dependent measurement after clot formation.

38. The method according to claim 26, wherein said plurality of known blood samples and said unknown blood sample are samples of whole blood or plasma.

39. The method according to claim 26, wherein said plurality of known blood samples are samples of which information is known relating to one or more intrinsic or extrinsic clotting factors and/or therapeutic agents, or are normal samples.

40. The method according to claim 26, wherein said at least one time-dependent measurement comprises at least one time-dependent measurement from a prothrombin time assay.

41. The method according to claim 26, wherein said at least one time-dependent measurement comprises at least one time-dependent measurement from an activated partial thromboplastin time assay.

42. The method according to claim 26, wherein at least one of said at least one time-dependent measurement comprises an optical measurement.

43. The method according to claim 42, wherein said optical measurement corresponds to changes in light scattering and/or light absorption.

44. The method according to claim 26, wherein in steps (a) or (b), a plurality of assays relating to thrombosis-hemostasis are performed to provide said at least one time-dependent measurement.

45. A method according to claim 26, wherein said at least one time-dependent measurement in steps (a) and (b) is provided by an automated analyzer for thrombosis and hemostasis testing.

46. A method according to claim 45, wherein at least one time-dependent measurement is provided automatically by said automated analyzer, and the unknown blood sample is automatically removed by an automated probe from a sample container to a test well, one or more reagents are automatically added to said test well so as to initiate property changes over time within said blood sample, and the development of respective property changes over time is automatically monitored so as to derive a data profile.

47. A method according to claim 45, wherein after step (e), the z-scores of the unknown blood sample are stored in a memory of said automated analyzer and/or displayed on said automated analyzer.

48. A method according to claim 26, wherein a plurality of optical measurements are made at multiple wavelengths.