Method and apparatus for predicting the presence of an abnormal level of one or more proteins in the clotting cascade

• US 6,564,153 B2
• Filed: 05/07/2001
• Issued: 05/13/2003
• Est. Priority Date: 06/07/1995
• Status: Expired due to Fees

• Current Assignee: Biomerieux B.V. (Compagnie Merieux Alliance SAS)
• Original Assignee: Biomerieux B.V. (Compagnie Merieux Alliance SAS)
• Inventors: Braun, Paul, Givens, Thomas B., Fischer, Timothy J.
• Primary Examiner(s): WACHSMAN, HAL D
• Application Number:
  US09/850,255
• Publication Number:
  US 20020019706A1
• Time in Patent Office: 736 Days
• Field of Search: 702/22, 702/23, 702/27-32, 702/128, 702/131, 702/139, 702/179-181, 702/183, 702/FOR-115, 702/FOR.131, 702/FOR.170, 702/FOR.171, 702/19, 702/21, 700/266, 700/268, 73/64, 73/43, 703/6, 703/9, 703/11, 703/12, 436/69, 436/66, 436/43, 436/47-50, 436/54, 436/55, 436/174, 436/164, 436/171, 436/180, 436/805, 422/73, 422/68.1, 422/50, 422/61-67, 422/82.05, 382/133, 382/134, 382/156-159, 356/39, 356/42, 356/40, 706/924, 706/21, 706/20, 435/13, 377/10, 377/11
• 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, C12Q1/56
• CPC Class Codes: G01N 33/86 involving blood coagulating time or factors, or their receptors
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

A method is disclosed for predicting the presence of an abnormal level of one or more proteins in the clotting cascade from at least one time-dependent measurement profile. At least one time-dependent measurement on an unknown sample is performed and a respective property of said sample is measured over time so as to derive a time-dependent measurement profile. A set of a plurality of predictor variables are defined which sufficiently define the data of the time-dependent measurement profile. A model is then derived that represents the relationship between the abnormality and the set of predictor variables. Subsequently, the model is utilized to predict which protein or proteins in the clotting cascade are at an abnormal level, with the prediction being a more informative prediction than clot time alone.

Claims

1. A method for predicting the presence of at least one congenital or acquired imbalance or therapeutic condition associated with thrombosis or hemostasis from at least one time-dependent measurement profile, comprising:

(a) adding one or more reagents to a sample to cause coagulation in said sample and performing at least one time-dependent measurement on said sample by taking a plurality of measurements of a property of said sample over time, which property changes when said sample undergoes coagulation. so as to derive a respective at least one time-dependent measurement profile;

(b) defining a set of predictor variables which define the at least onetime-dependent measurement profile, said set of predictor variables including at least (i) rate or (ii) acceleration of fibrin polymerization;

(c) deriving a model that represents the relationship between the at least one congenital or acquired imbalance or therapeutic condition associated with thrombosis or hemostasis, and the set of predictor variables; and

(d) utilizing the model of step (c) to predict the presence of the at least one congenital or acquired imbalance or therapeutic condition associated with thrombosis or hemostasis in the sample.

2. A method according to claim 1, wherein said set of predictor variables includes both rate and acceleration of fibrin polymerization.

3. The method of claim 1, wherein the rate is defined as the minimum of the first derivative of the at least one time-dependent measurement profile.

4. The method of claim 1, wherein acceleration is defined as the minimum of the second derivative of the at least one time-dependent measurement profile.