Point of care diagnostic systems

• US 6,394,952 B1
• Filed: 04/20/1998
• Issued: 05/28/2002
• Est. Priority Date: 02/03/1998
• Status: Expired due to Term

• Current Assignee: Cytyc Corporation (Hologic Incorporated)
• Original Assignee: Cytyc Prenatal Products Corp. (Hologic Incorporated)
• Inventors: Senyei, Andrew E., Jones, Lynn, Martinez, Ricardo, Anderson, Emory V., Marzolf, Gail, Nemec, Edward, Pong, Ronald, Lapointe, Jerome, DeSieno, Duane, Hussa, Robert O.
• Primary Examiner(s): Lacyk, John P.
• Assistant Examiner(s): CARTER, RYAN CHRISTOPHER
• Application Number:
  US09/063,497
• Time in Patent Office: 1,499 Days
• Field of Search: 436/514,516,518,811,814 435/4,7.1,14,970 422/56 600/300-301,304,310,316,322,345-351,362,365-367,573,584
• US Class Current: 600/300
• CPC Class Codes: G01N 21/474 Details of optical heads therefor, e.g. using optical fibres
• CPC Class Codes: G01N 21/8483 Investigating reagent band test-element handling not specific to a test method G01N33/4875; analytical elements specific to chemical analysis of biological material G01N33/52; autometer with reagent band G01N35/04
• CPC Class Codes: G01N 2333/78 Connective tissue peptides, e.g. collagen, elastin, laminin, fibronectin, vitronectin, cold insoluble globulin [CIG]
• CPC Class Codes: G01N 2800/368 Pregnancy complicated by disease or abnormalities of pregnancy, e.g. preeclampsia, preterm labour
• CPC Class Codes: G01N 33/54388 based on lateral flow
• CPC Class Codes: G01N 33/558 using diffusion or migration of antigen or antibody immunochromatographic test strips G01N33/54387
• CPC Class Codes: G01N 33/6887 from muscle, cartilage or connective tissue
• CPC Class Codes: G01N 33/689 related to pregnancy or the gonads
• 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 15/00 ICT specially adapted for medical reports, e.g. generation or transmission thereof
• CPC Class Codes: G16H 30/40 for processing medical images, e.g. editing
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: Y02A 90/10 Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
• CPC Class Codes: Y10S 436/811 Test for named disease, body condition or organ function
• CPC Class Codes: Y10S 436/814 Pregnancy

Abstract

Systems and methods for medical diagnosis or risk assessment for a patient are provided. These systems and methods are designed to be employed at the point of care, such as in emergency rooms and operating rooms, or in any situation in which a rapid and accurate result is desired. The systems and methods process patient data, particularly data from point of care diagnostic tests or assays, including immunoassays, electrocardiograms, X-rays and other such tests, and provide an indication of a medical condition or risk or absence thereof. The systems include an instrument for reading or evaluating the test data and software for converting the data into diagnostic or risk assessment information.

Claims

1. A method for determining results from an immunoassay, comprising:

(a) testing a patient sample for the presence of a target analyte indicative of a condition or risk of having the condition by reacting the sample with antibodies specific for the analyte in a sandwich assay performed on a test strip, in which one of the antibodies is labeled with a detectable label;

(b) scanning the surface of the test strip in with a reader head in a reflectance reader where the reader head is substantially normal to the surface of the strip, wherein;

the reflectance reader includes a reader head that comprises;

a reader head body;

a light emitting diode (LED);

a first fiberoptic bundle optically coupled to the light emitting diode;

a photodetector;

a second fiberoptic bundle optically coupled to the photodetector;

an aperture in the reader head body; and

a plurality of fiberoptic conductor ends arranged in a sigmoidal distribution in the aperture, a first portion of the fiberoptic conductor ends comprising fiberoptic conductors of the first fiberoptic bundle, and a second portion of the fiberoptic conductor ends comprising fiberoptic conductors of the second fiberoptic bundle such that the plurality of fiberoptic conductor ends are arranged in a substantially co-planar relationship; and

the planar surface is held substantially parallel to a plane at an upper surface of the test strip during scanning of the test strip, whereby light is conducted by fiberoptic bundles to the photodetector, which generates a reflection signal indicative of an amount of reflected light;

(c) detecting the signal produced by the label in the reflectance reader, wherein the signal is indicative of the presence of the analyte.

2. The method of claim 1, wherein the results are qualitative.

3. The method of claim 1, wherein the results are quantitative.

4. The method of claim 1, further comprising:

inputting the data obtained from the reflectance signal inputting it into a neural network trained for assessing risk related to or for diagnosing the condition, wherein;

the trained neural network converts the reflectance signal obtained from reading the test strip into a result indicative of the presence or absence of a threshold concentration of analyte in a sample.

5. The method of claim 4, wherein the analyte is fetal fibronectin (fFN).

6. The method of claim 5, wherein the condition is pregnancy-related or is related to fertility status.

7. The method of claim 5, wherein the condition is an infertility-related disorder.

8. The method of claim 5 that assesses the risk of ectopic pregnancy, pre-eclampsia, infertility, preterm labor, imminent delivery, term induction or fetal membrane rupture.

9. The method of claim 1, further comprising:

(d) processing the data obtained from the reflectance signal obtained from reading the test strip into a result indicative of the presence or absence or a threshold concentration of analyte in a sample.

10. The method of claim 1, wherein the analyte is fetal fibronectin (fFN).

11. The method of claim 1, wherein the analyte is fetal fibronectin (fFN).

12. The method of claim 1 wherein the immunoassay is performed on a test strip.

13. The method of claim 1, wherein the patient sample is reacted with an antibody labeled with a detectable label prior to application to the test strip.

28. The method of claim 9, wherein the data is processed by:

i) optionally correcting the reflectance readings to correct for light leakage;

(ii) reducing the raw reflectance data with a ratiometric formula; and

(iii) generating an image of the test data by plotting the reduced data.

29. The method of claim 28, further comprising one or more of the following steps:

(iv) expressing this image as a polynomial mathematical function;

(v) generating parameters that define the image;

(vi) optimizing the reconstruction of the image and producing a fitted image;

(vii) comparing a scanned image and fitted image by solving the linear regression through the curves;

(viii) validating the parameters obtained from the curve-fitting and the peak heights obtained; and

(ix) classifying the validated result as positive or negative by comparing peak heights of a clinical sample to reference samples.

30. The method of claim 9, further comprising inputting the test results into a decision-support system to generate a medical diagnosis or risk assessment.

31. The method of claim 30, wherein the decision-support system is a neural network.

14. A method for determining results from an immunoassay, comprising:

(a) testing a patient sample for the presence of a target analyte indicative of a condition or risk of having the condition by applying the sample to a lateral flow immunoassay test strip that comprises antibodies specific for the analyte, wherein one of the antibodies is labeled with a detectable label,

wherein the immunoassay test strip comprises;

(i) a conjugate pad which serves as a sample application component;

(ii) a porous or bibulous member which is capable of transporting a liquid sample along the test strip and serves as a solid support upon which immunoreactions occur; and

(iii) an absorbent pad, which serves to draw liquid continuously through the device, wherein;

the materials of the membrane system form a single fluid flow pathway and the test strip is designed to be read by the reader;

(b) either before or after reacting the sample with the antibodies, inserting the test strip into a computer-controlled reflectance reader that scans the test strip; and

(c) detecting the signal produced by the label in a reflectance reader, wherein the intensity of reflected signal in the test region or detection zone of the test strip is correlated with an amount of analyte present in the test sample.

15. The method of claim 14, wherein the porous or bibulous member comprises an immobilized capture antibody that binds to the analyte of interest in a detection zone.

16. The method of claim 14, wherein:

the conjugate pad comprises an antibody diffusively bound thereto; and

the antibody is labeled with a calorimetrically or fluorometrically detectable label.

17. The method of claim 14, further comprising:

analyzing the results from the test.

18. The method of claim 14, wherein the condition is pregnancy-related or is related to fertility status.

19. The method of claim 14, wherein the condition is an infertility-related disorder, a neurological disorder, a cardiovascular disorder, an inflammatory disorder, a viral or bacterial infection, a hormonal disorder, a metabolic disorder or a genetic disease.

20. The method of claim 14, wherein the results of the test are qualitative.

21. The method of claim 14, wherein the results of the test are quantitative.

22. The method of claim 14, wherein the immunoassay detects fetal fibronectin (fFN) in a sample.

23. The method of claim 14, further comprising:

(d) processing the data obtained from the reflectance signal using data processing software employing data reduction and curve fitting algorithms to convert the reflectance signal obtained from reading the test strip into a result indicative of the presence or absence or a threshold concentration of analyte in a sample.

24. The method of claim 14, further comprising:

(d) processing the data obtained from the reflectance signal obtained from reading the test strip into a result indicative of the presence or absence or a threshold concentration of analyte in a sample.

25. The method of claim 14, wherein the patient sample is reacted with an antibody labeled with a detectable label prior to application to the test strip.

26. The method of claim 14, wherein the conjugate pad comprises an anti-fetal fibronectin (fFN) antibody.

27. The method of claim 26, wherein the anti-fFN antibody is FDC-6 or A137.

32. The method of claim 14, further comprising inputting the test results into a decision-support system to generate a medical diagnosis or risk assessment.

33. The method of claim 22, wherein the decision-support system is a neural network.