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Use of biomarker in preparation of heart failure diagnosis composition and diagnosis device

A diagnostic composition and biomarker technology, which can be used in disease diagnosis, biological testing, measurement devices, etc., to solve problems such as cardiac insufficiency and increased discomfort

Inactive Publication Date: 2015-04-15
CHANG GUNG UNIVERSITY +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Class I: Unrestricted physical activity, ordinary physical activity does not cause undue fatigue, palpitations, or dyspnea (shortness of breath); Class II: Slight restriction of physical activity, comfortable at rest, but ordinary physical activity causes undue fatigue, Palpitations or dyspnea; Class III: significant limitation of physical activity, comfortable at rest, but a small amount of ordinary activity causes excessive fatigue, palpitations, or dyspnea; Class IV: unable to perform any physical activity without discomfort, resting Feeling of cardiac insufficiency, increased discomfort with any physical activity

Method used

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  • Use of biomarker in preparation of heart failure diagnosis composition and diagnosis device
  • Use of biomarker in preparation of heart failure diagnosis composition and diagnosis device
  • Use of biomarker in preparation of heart failure diagnosis composition and diagnosis device

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0106] Example 1: Whole metabolomics analysis for diagnosing and judging the stage of heart failure

[0107] 1. Basic characteristics of each group of patients

[0108] In this embodiment, a total of 234 individuals were recruited, including 51 normal individuals and 183 patients in stage A (n=43), stage B (n=67) and stage C (n=73). The room data are shown in Table 1. In most of the variables, a significant trend of change from normal controls to patients with stages A, B, and C can be noted. Compared with the normal control group, the BNP content of patients in stage C was significantly higher, and the QRS complex was wider, but the total cholesterol, low and high density lipoprotein cholesterol (low and high density lipoprotein cholesterol), sodium, hemoglobin , albumin (albumin) and estimated glomerular filtration rate (estimated glomerular filtration rate) are lower. In terms of age, although there was no significant difference among the patients in each group, they wer...

Embodiment 2

[0158] Example 2: Targeted Metabolomics Analysis for Diagnosis and Judgment of Heart Failure Stage

[0159] 1. Patient

[0160] A total of 145 individuals were enrolled in this embodiment, including 62 normal individuals and 83 patients in stage C.

[0161] 2. Target metabolomic analysis in HF and normal control group

[0162] In order to quantify the concentration of metabolites, this example uses the Biocrates kit to perform plasma metabolomics analysis according to the target metabolomics workflow, and uses the OPLS-DA mode to perform bioinformatics data set analysis. To test whether target metabolite profiles could distinguish stage C HF patients from normal controls, a total of 201 variables were used in this analysis. Metabolites sufficient to distinguish between the two groups are listed in Table 9 (these metabolites had a VIP score >1.0).

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[0168] 3. Distinguish stage C patients from normal controls

[016...

Embodiment 3

[0173] Example 3: Targeted Metabolomics Analysis for Assessing Heart Failure Prognosis

[0174] 1. Prognostic value of metabolomic signatures

[0175] To assess the prognostic value of metabolomics and BNP, the following assays were performed for stage B and C patients. In order to search for predictive metabolites (predictors) in the composite event of all-cause mortality and HF-related readmission rate, extensive analysis in the target metabolite data set showed that four metabolites (dimethylarginine / Arginine ratio, spermidine, butyrylcarnitine, and total essential amino acids) combined to produce ideal prognostic value significantly better than BNP. The resulting parameter by combining these four metabolites is called tPS [3]. The AUCs of the ROC curves for tPS[3], tPS[2] (derived from all target metabolite data sets) and BNP content were 0.853, 0.792 and 0.744 ( Figure 5 A). Table 11 shows the AUC data (by ROC curve) and log rank (by Kaplan-Meire analysis) of these ...

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Abstract

A method for diagnosing heart failure in a subject is provided. The method includes steps of measuring a biological sample of the subject to obtain an amount of at least one biomarker selected from the group consisting of xanthine, spermidine, propionylcarnitine, butyrylcarnitine and P-cresyl sulfate; and comparing the amount of the at least one biomarker to a reference. Moreover, the present invention relates to a method for staging heart failure or evaluating a prognosis of heart failure in a subject.

Description

technical field [0001] The present invention relates to the use of a biomarker in a biological sample of an individual for the preparation of a diagnostic composition and a diagnostic device containing the biomarker. Background technique [0002] Heart failure (heart failure) is a clinical syndrome presented in the final stage of a variety of cardiovascular diseases. Over the past few decades, there have been substantial advances in the understanding of the underlying pathophysiology and hemodynamics, as well as in the development of novel drugs and invasive treatments. Despite this, short- and long-term rates of rehospitalization and mortality associated with heart failure remain high and require substantial health care resources. Existing therapeutic strategies have limited effects in advanced heart failure, and new interventional measures are urgently needed to reduce inappropriate molecular processes in the sub-clinical stage to avoid progression to the next stage of he...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N33/92G01N33/68G01N30/02G01N27/62G01N21/64G01N27/622
CPCG01N33/493G01N33/49G01N33/6809G01N33/6848G01N33/92G01N2570/00G01N2800/325G01N33/6806
Inventor 王兆弘萧明熙郑美玲
Owner CHANG GUNG UNIVERSITY
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