Device for diagnosing chronic diseases through body fluid testing

Abstract

This invention relates to a body fluid-based detection device for chronic diseases, which belongs to the field of medical devices. The device includes a body fluid detection fluid channel, a detection probe, a data processing module, and a data display module. The detection probe is disposed within the body fluid detection fluid channel, and the detection probe is connected to the data processing module, which is connected to the data display module. The body fluid detection fluid channels include: a body fluid ion detection channel, a body fluid pH detection channel, a body fluid hydrodynamic characteristic detection channel, a channel for detecting the content of soluble gases such as oxygen, a channel for detecting the physical characteristics of white blood cells and tumor cells, a channel for detecting the electrical characteristics of white blood cells and tumor cells, a channel for detecting the physical characteristics of red blood cells, a channel for detecting the electrical characteristics of red blood cells, a channel for detecting the electrical characteristics of separated body fluids, and a channel for detecting anticoagulation and fibrinolysis functions. This invention enables highly sensitive, non-invasive testing, providing a powerful tool for the early diagnosis of chronic diseases.

Description

[Technical Field]

[0001] The present invention relates to a device for diagnosing chronic diseases through body fluid testing, and belongs to the field of medical device technology. [Background technology]

[0002] Traditionally, chronic disease diagnostic monitoring has primarily been achieved through testing of general blood biochemistry indicators, diagnostic imaging, and disease biomarker testing. However, these conventional technologies have limited effectiveness in disease monitoring. In the early stages of chronic disease, the differences in hematological tests such as general blood biochemistry indicators and disease biomarkers are not very significant, and diagnostic imaging also has difficulty identifying very small lesions. This poses significant challenges to early diagnosis of chronic disease. Therefore, there is an urgent need to develop devices that can diagnose chronic diseases early based on body fluid testing. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] CN 116068156 A (Xu▲Chang▼) May 5, 2023 (2023-05-05) Manual paragraphs 22-30

[0004] [Patent Document 2] CN 113164949 A (Chang Wei System ▲ General Technology (Shanghai) Co., Ltd.) July 23, 2021 (2021-07-23) Manual No. 12~57, 209~238, 247~291, 342~354, Figures 25~28

[0005] [Patent Document 3] CN 113574382 A (Chang Wei System ▲ Control ▼ Science and Technology (Shanghai) Co., Ltd.) October 29, 2021 (2021-10-29) Manual paragraphs 15 to 80, Figures 25 to 28

[0006] [Patent Document 4] CN 108745426 A(Qiqihar Medical University) November 6, 2018 (2018-11-06) Full text

[0007]

Patent Document 5

[0008]

Patent Document 6

Summary of the Invention

[0009] This invention relates to a detection device based on body fluids for chronic diseases and belongs to the technical field of medical devices. This device includes a body fluid detection fluid channel, a detection probe, a data processing module, and a data display module. The detection probe is arranged in the body fluid detection fluid channel, the detection probe is connected to the data processing module, and the data processing module is connected to the data display module. The body fluid detection fluid channel includes the following: a body fluid ion detection channel, a body fluid pH detection channel, a body fluid hydrodynamic characteristic detection channel, a channel for detecting the content of soluble gases such as oxygen, a channel for detecting the physical characteristics of white blood cells and tumor cells, an electrical characteristic detection channel for white blood cells and tumor cells, a physical characteristic detection channel for red blood cells, an electrical characteristic detection channel for red blood cells, a body fluid electrical characteristic detection channel after separation, an anticoagulation and fibrinolysis function detection channel. This invention can perform highly sensitive and non-invasive examinations and provides a powerful means for the early diagnosis of chronic diseases.

Problems to be Solved by the Invention

[0010] The object of this invention is to solve the technical problem of early diagnosis of chronic diseases based on body fluid examinations.

Means for Solving the Problems

[0011] To achieve this objective, the technical solution of the present invention is to provide a body fluid testing device, including a fluid passage for body fluid testing, a detection probe, a data processing module and a data display module, wherein the detection probe is installed in the body fluid testing fluid passage, the detection probe is connected to the data processing module, and the data processing module is connected to the data display module.

[0012] The fluid pathways for body fluid testing include pathways for ions, cellular factors, nucleic acids, proteins and their derivatives or trace elements in body fluids, pathways for soluble gases such as oxygen in body fluids, pathways for pH of body fluids, pathways for hydrodynamic properties such as viscosity of body fluids, pathways for detecting physical properties including osmotic pressure of white blood cells and tumor cells, pathways for detecting electrical properties (including electrical resistance and charge) of white blood cells and tumor cells, pathways for physical properties including osmotic pressure of red blood cells, pathways for electrical properties (including electrical resistance and charge) of red blood cells, pathways for electrical properties (including electrical resistance and charge) of separated body fluids, and pathways for measuring coagulation, anticoagulation and fibrinolysis functions to measure coagulation factors, fibrinogen, D-dimer, platelets, etc. contained in separated body fluids.

[0013] Processing method using diagnostic data of chronic diseases by body fluid tests:

[0014] Step 1:

[0015] Calculate the n1 value based on the following formula:

[0016] n1=3.73v+6.38SpO2+6.29ph+6.4η+3.51π1+1.75Ze1+3.64π2+5.19Ze2+9.09t+8.74Ze3+6.58v1+4.95v2

[0017] v: ion concentration in body fluid, SpO2: oxygen content, ph: pH value of body fluid, η: viscosity value of body fluid, π1: osmotic pressure value of white blood cells and tumor cells, π2: osmotic pressure value of red blood cells, Ze1: electrical resistance value of white blood cells and tumor cells, Ze2: electrical resistance value of red blood cells, Ze3: electrical resistance value of body fluid after separation, t: clotting time, v1: D-dimer concentration in body fluid after separation, v2: fibrinogen degradation product concentration in body fluid after separation

[0018] Step 2:

[0019] TIFF2026502037000002.tif12162135: Medium risk, n1>135: High risk (the higher the number, the greater the risk)

[0020] Selected Example: Chronic diseases include tumors. Preferably, the cellular factor is hypoxia inducible factor 1α and / or hypoxia inducible factor 1β.

[0021] Processing method using diagnostic data of chronic diseases obtained by body fluid tests

[0022] Step 1:

[0023] Calculate the n2 value based on the following formula:

[0024] n2=5.69H1+7.32H2+3.73v+6.38SpO2+6.29ph+6.4η+3.51π1+1.75Ze1+3.64π2+5.19Ze2+9.09t+8.55Ze3+4.72v1+6.94v2

[0025] H1: concentration of hypoxia-inducible factor 1α, H2: concentration of hypoxia-inducible factor 1β, v: ion concentration in body fluid, SpO2: oxygen content, ph: pH value of body fluid, η: viscosity value of body fluid, π1: osmotic pressure value of white blood cells and tumor cells, π2: osmotic pressure value of red blood cells, Ze1: electrical resistance value of white blood cells and tumor cells, Ze2: electrical resistance value of red blood cells, Ze3: electrical resistance value of body fluid after separation, t: clotting time, v1: D-dimer concentration in body fluid after separation, v2: fibrinogen degradation product concentration in body fluid after separation

[0026] Step 2:

[0027] The subject's risk of chronic disease is assessed based on the n2 value.

[0028] TIFF2026502037000003.tif8159 (increased risk)

[0029] Selected Example: The body fluid pH sensing channel is equipped with a probe that detects physical properties such as electrical resistance or charge of the body fluid.

[0030] Processing method using diagnostic data of chronic diseases obtained by body fluid tests

[0031] Step 1:

[0032] Calculate the n3 value based on the following formula:

[0033] n3=Ze4

[0034] Ze4: The electrical resistance value of the entire body fluid before cell separation. The Ze4 value is obtained using a probe installed in the body fluid pH detection channel.

[0035] Step 2:

[0036] The n3 value is used to assess the subject's risk of chronic disease.

[0037] TIFF2026502037000004.tif7159 (increases size)

[0038] During the subclinical and clinical stages of chronic disease, the n3 level gradually increases, and an increase in the level is an indicator that the patient should seek further testing at the hospital and check their medical history.

[0039] Optional embodiment: The probes provided in the body fluid pH detection channel include a probe for detecting the electrical resistance value Ze5 of the body fluid cell portion and a probe for detecting the electrical resistance value Ze4 of the entire body fluid.

[0040] Processing method using diagnostic data of chronic diseases obtained by body fluid tests

[0041] Step 1:

[0042] The total electrical resistance value of the body fluid (Ze4), the electrical resistance value of the cellular part of the body fluid (Ze5), and the electrical resistance value of the body fluid after separation (Ze3) are obtained.

[0043] Step 2:

[0044] Each cancer risk is assessed based on the following formula:

[0045] Breast cancer: n4 = 1.73Ze4 + 1.89Ze3 + 1.36Ze5 n4 = 1.73Ze4 + 1.89Ze3 + 1.36Ze5 n4 = 1.73Ze4 + 1.89Ze3 + 1.36Ze5

[0046] Prostate cancer: n5 = 1.79Ze4 + 1.85Ze3 + 1.73Ze5 n5 = 1.79Ze4 + 1.85Ze3 + 1.73Ze5 n5 = 1.79Ze4 + 1.85Ze3 + 1.73Ze5

[0047] Colorectal cancer: n6 = 1.64Ze4 + 1.58Ze3 + 1.56Ze5 n6 = 1.64Ze4 + 1.58Ze3 + 1.56Ze5 n6 = 1.64Ze4 + 1.58Ze3 + 1.56Ze5

[0048] Stomach cancer: n7 = 1.67Ze4 + 1.88Ze3 + 1.49Ze5 n7 = 1.67Ze4 + 1.88Ze3 + 1.49Ze5 n7 = 1.67Ze4 + 1.88Ze3 + 1.49Ze5

[0049] Liver cancer: n8 = 1.85Ze4 + 1.48Ze3 + 1.61Ze5 n8 = 1.85Ze4 + 1.48Ze3 + 1.61Ze5 n8 = 1.85Ze4 + 1.48Ze3 + 1.61Ze5

[0050] Thyroid cancer: n9 = 1.59Ze4 + 1.86Ze3 + 1.47Ze5 n9 = 1.59Ze4 + 1.86Ze3 + 1.47Ze5 n9 = 1.59Ze4 + 1.86Ze3 + 1.47Ze5

[0051] Pancreatic cancer: n10 = 1.56Ze4 + 1.47Ze3 + 1.41Ze5 n10 = 1.56Ze4 + 1.47Ze3 + 1.41Ze5 n10 = 1.56Ze4 + 1.47Ze3 + 1.41Ze5

[0052] Leukemia:n11=1.37Ze4+1.93Ze3+1.52Ze5n11=1.37Ze4+1.93Ze3+1.52Ze5n11=1.37Ze4+1.93Ze3+1.52Ze5

[0053] Renal cancer: n12 = 1.86Ze4 + 1.82Ze3 + 1.44Ze5 n12 = 1.86Ze4 + 1.82Ze3 + 1.44Ze5 n12 = 1.86Ze4 + 1.82Ze3 + 1.44Ze5

[0054] Uterine fibroid:n13=1.72Ze4+1.52Ze3+1.85Ze5n13=1.72Ze4+1.52Ze3+1.85Ze5n13=1.72Ze4+1.52Ze3+1.85Ze5

[0055] Oral cancer: n14 = 1.35Ze4 + 1.57Ze3 + 1.69Ze5 n14 = 1.35Ze4 + 1.57Ze3 + 1.69Ze5 n14 = 1.35Ze4 + 1.57Ze3 + 1.69Ze5

[0056] Ovarian cancer: n15 = 1.69Ze4 + 1.55Ze3 + 1.42Ze5 n15 = 1.69Ze4 + 1.55Ze3 + 1.42Ze5 n15 = 1.69Ze4 + 1.55Ze3 + 1.42Ze5

[0057] Brain cancer: n16 = 1.74Ze4 + 1.69Ze3 + 1.63Ze5 n16 = 1.74Ze4 + 1.69Ze3 + 1.63Ze5 n16 = 1.74Ze4 + 1.69Ze3 + 1.63Ze5

[0058] Nose cancer: n17 = 1.63Ze4 + 1.77Ze3 + 1.78Ze5 n17 = 1.63Ze4 + 1.77Ze3 + 1.78Ze5 n17 = 1.63Ze4 + 1.77Ze3 + 1.78Ze5

[0059] Throat cancer: n18 = 1.62Ze4 + 1.67Ze3 + 1.96Ze5 n18 = 1.62Ze4 + 1.67Ze3 + 1.96Ze5 n18 = 1.62Ze4 + 1.67Ze3 + 1.96Ze5

[0060] Esophageal cancer: n19 = 1.64Ze4 + 1.68Ze3 + 1.71Ze5 n19 = 1.64Ze4 + 1.68Ze3 + 1.71Ze5 n19 = 1.64Ze4 + 1.68Ze3 + 1.71Ze5

[0061] Cardia cancer: n20 = 1.56Ze4 + 1.73Ze3 + 1.58Ze5 n20 = 1.56Ze4 + 1.73Ze3 + 1.58Ze5 n20 = 1.56Ze4 + 1.73Ze3 + 1.58Ze5

[0062] Bile duct cancer: n21 = 1.74Ze4 + 1.98Ze3 + 1.89Ze5 n21 = 1.74Ze4 + 1.98Ze3 + 1.89Ze5 n21 = 1.74Ze4 + 1.98Ze3 + 1.89Ze5

[0063] Bladder cancer: n22 = 1.55Ze4 + 1.85Ze3 + 1.91Ze5 n22 = 1.55Ze4 + 1.85Ze3 + 1.91Ze5 n22 = 1.55Ze4 + 1.85Ze3 + 1.91Ze5

[0064] Lymphatic cancer: n23 = 1.88Ze4 + 1.61Ze3 + 1.84Ze5 n23 = 1.88Ze4 + 1.61Ze3 + 1.84Ze5 n23 = 1.88Ze4 + 1.61Ze3 + 1.84Ze5

[0065] Skin cancer: n24 = 1.75Ze4 + 1.82Ze3 + 1.86Ze5 n24 = 1.75Ze4 + 1.82Ze3 + 1.86Ze5 n24 = 1.75Ze4 + 1.82Ze3 + 1.86Ze5

[0066] Bone cancer: n25 = 1.91Ze4 + 1.66Ze3 + 1.57Ze5 n25 = 1.91Ze4 + 1.66Ze3 + 1.57Ze5 n25 = 1.91Ze4 + 1.66Ze3 + 1.57Ze5

[0067] Testicular cancer: n26 = 1.87Ze4 + 1.78Ze3 + 1.72Ze5 n26 = 1.87Ze4 + 1.78Ze3 + 1.72Ze5 n26 = 1.87Ze4 + 1.78Ze3 + 1.72Ze5

[0068] Gallbladder cancer: n27 = 1.53Ze4 + 1.96Ze3 + 1.83Ze5 n27 = 1.53Ze4 + 1.96Ze3 + 1.83Ze5 n27 = 1.53Ze4 + 1.96Ze3 + 1.83Ze5

[0069] Lung cancer: n28 = 1.69Ze4 + 1.83Ze3 + 1.56Ze5 n28 = 1.69Ze4 + 1.83Ze3 + 1.56Ze5 n28 = 1.69Ze4 + 1.83Ze3 + 1.56Ze5

[0070] Step 3:

[0071] The risk of each cancer is assessed based on the values ​​of n4 to n28 obtained in Step 2 above. If the values ​​of n4 to n28 are greater than 60: This indicates a high risk of the corresponding cancer and further clinical testing is required. [Effects of the Invention]

[0072] The present invention aims to determine changes in body fluids by detecting changes in viscosity and the electrical properties of metabolites in the body fluids, thereby enabling risk screening, diagnosis, monitoring of treatment effects, and evaluation of prognosis for chronic diseases (hereinafter abbreviated as "disease monitoring").The present invention aims to reduce the mortality rate from disease and improve the quality of life of patients by enabling early detection and treatment of diseases in patients.

[0073] The present invention enables non-invasive testing without harmful effects on the human body, such as radiation exposure. It is also highly sensitive and provides a powerful means for early diagnosis of chronic diseases. Furthermore, the required sample volume is small, making testing possible without being restricted by physiological conditions (such as fasting or urination restriction) at the time of collection. In addition, the testing procedure is simple, and results can be obtained quickly. [Brief explanation of the drawings]

[0074] [Figure 1] : Schematic diagram of the body fluid testing fluid channel structure, which is a main component of the present invention.

[0075] [Figure 2] : Work curve of the subject obtained using Formula 1. Comparing the effectiveness of the algorithm of the present invention in distinguishing between chronic disease patients and healthy individuals.

[0076] [Figure 3] : Work curve of the subject obtained using formula 2. Comparing the effectiveness of the algorithm of the present invention in distinguishing between chronic disease patients and healthy individuals.

[0077] [Figure 4] : Work curve of the subject obtained using formula 3. Comparing the effectiveness of the algorithm of the present invention in distinguishing between chronic disease patients and healthy individuals.

[0078] Symbols on the accompanying diagram:

[0079] 1. Detection channels for ions, cytokines, nucleic acids, proteins and their derivatives, and trace elements in body fluids; 2. Detection channel for pH of body fluids; 3. Detection channel for viscosity and hydrodynamic properties of body fluids; 4. Separation channel for white blood cells and tumor cells; 5. Detection channel for physical properties including osmotic pressure of white blood cells and tumor cells; 6. Detection channel for electrical properties including electrical impedance and charge of white blood cells and tumor cells; 7. Separation channel for red blood cells; 8. Detection channel for physical properties including osmotic pressure of red blood cells; 9. Detection channel for electrical properties including electrical impedance and charge of red blood cells; 10. Channel for body fluid after separation; 11. Detection channel for coagulation factors; 12. Microfluidic channel for cell separation; 13. Body fluid inlet; 14. Detection channel for coagulation, anticoagulation, and fibrinolysis functions including coagulation factors, fibrinogen, D-dimer, and platelets; 15. Channel for cell separation in body fluids; 16. Detection channel for the amount of dissolved oxygen gas; 17. Detection channel for electrical properties including electrical impedance and charge of body fluid after separation. [Example]

[0080] In order to make the present invention more clearly understood, preferred embodiments are shown below and will be described in detail in conjunction with the drawings.

[0081] The present invention provides a chronic disease detection device based on body fluid testing, as shown in Figure 1. The device includes a body fluid testing fluid channel, a detection probe, a data processing module, and a data display module. The body fluid testing fluid channel is equipped with a detection probe, which is connected to the data processing module, which is in turn connected to the data display module. The body fluid testing fluid channels include: a detection channel 1 for detecting ions, cytokines, nucleic acids, proteins and their derivatives, and trace elements in the body fluid; a detection channel 2 for detecting body fluid pH; a detection channel 3 for detecting fluid dynamic properties such as body fluid viscosity; a detection channel 16 for detecting dissolved gases such as oxygen; a detection channel 5 for detecting physical properties including the osmotic pressure of white blood cells and tumor cells; a detection channel 6 for detecting electrical properties including the electrical impedance and charge of white blood cells and tumor cells; a detection channel 8 for detecting physical properties including the osmotic pressure of red blood cells; a detection channel 9 for detecting electrical properties including the electrical impedance and charge of red blood cells; a detection channel 14 for detecting coagulation, anticoagulation, and fibrinolysis functions including coagulation factors, fibrinogen, D-dimer, and platelets; and a detection channel 17 for detecting electrical properties including the electrical impedance and charge of separated body fluids. The device is equipped with a body fluid inlet 13, which is connected to a detection channel 1 for detecting ions, cytokines, nucleic acids, proteins and their derivatives, and trace elements in the body fluid; a body fluid pH detection channel 2; a detection channel 3 for detecting hydrodynamic properties such as body fluid viscosity; a detection channel 16 for detecting dissolved gases such as oxygen; and a body fluid cell separation channel 15. The device is equipped with a cell separation microfluidic channel 12, one end of which is connected to the body fluid cell separation channel 15, and the other end of which is connected to a white blood cell and tumor cell separation channel 4, a red blood cell separation channel 7, and a separated body fluid channel 10. The white blood cell and tumor cell separation channel 4 is connected to a physical property detection channel 5, including the osmotic pressure of white blood cells and tumor cells, and a channel 6, including electrical properties such as electrical impedance and charge, respectively. The red blood cell separation channel 7 is connected to a physical property detection channel 8, including the osmotic pressure of red blood cells, and a channel 9, including electrical properties such as electrical impedance and charge, respectively.The separated body fluid channel 10 is connected to a coagulation / anticoagulation / fibrinolysis function detection channel 14 containing coagulation factors, fibrinogen, D-dimer, and platelets, and an electrical property detection channel 17 containing the electrical impedance and charge of the separated body fluid. Furthermore, the coagulation / anticoagulation / fibrinolysis function detection channel 14 containing coagulation factors, fibrinogen, D-dimer, and platelets is provided with a coagulation factor channel 11 for adding coagulation factors. The structures of the detection probes installed in these detection channels are the same as those in the prior art. The detection of ions, cytokines, nucleic acids, proteins and their derivatives, and trace elements in body fluids; the detection of body fluid pH; the detection of fluid viscosity and other hydrodynamic properties; the detection of dissolved gases such as oxygen; the detection of physical properties such as the osmotic pressure of white blood cells and tumor cells; the detection of electrical properties such as the electrical impedance and charge of white blood cells and tumor cells; the detection of physical properties such as the osmotic pressure of red blood cells; the detection of electrical properties such as the electrical impedance and charge of red blood cells; the detection of electrical properties such as the electrical impedance and charge of separated body fluids; and the detection of coagulation, anticoagulation, and fibrinolysis functions, including coagulation factors, fibrinogen, D-dimers, and platelets, are well-known in the art. Separation of white blood cells, tumor cells, red blood cells, and separated body fluids has been reported in a previously published paper (NATURE COMMUNICATIONS (2022) 13:3086 https: / / doi.org / 10.1038 / s41467-022-30384-7; www.nature.com / naturecommunications). 「 The technology used is similar to the blood cell separator described in "A role for microfluidic systems in precision medicine."

[0082] How to treat chronic diseases using test data acquired by this device:

[0083] Step 1: Based on Equation 1, calculate the n value using n = 3.73v + 6.38SpO + 6.29ph + 6.4η + 3.51π + 1.75Ze + 3.64π + 5.19Ze + 9.09t + 8.74Ze + 6.58v + 4.95v, where v is the ion concentration in the body fluid, SpO is the oxygen content, ph is the pH value of the body fluid, η is the viscosity value of the body fluid, π is the osmotic pressure value of white blood cells and circulating tumor cells, π is the osmotic pressure value of red blood cells, Ze is the electrical impedance value of white blood cells and tumor cells, Ze is the electrical impedance value of red blood cells, Ze is the electrical impedance value of the body fluid after separation, t is the clotting time, v is the D-dimer concentration in the body fluid after separation, and v is the fibrinogen degradation product concentration in the body fluid after separation.

[0084] Step 2: Evaluate the subject's risk of chronic disease based on the n1 value. An n1 value of 105 or less is classified as low risk, an n1 value of 105-135 as medium risk, and an n1 value of 135 or more as high risk. The higher the value, the greater the risk. Chronic diseases include tumors.

[0085] A method for diagnosing a chronic disease using test data obtained from a chronic disease detection device based on a separate body fluid test is provided, in which hypoxia-inducible factor 1α (HIF-1α) and / or hypoxia-inducible factor 1β (HIF-1β) is measured as a cellular factor. The method includes the following steps:

[0086] Step 1: Based on Equation 2, calculate the n2 value using n2 = 5.69H1 + 7.32H2 + 3.73v + 6.38SpO2 + 6.29ph + 6.4η + 3.51π1 + 1.75Ze1 + 3.64π2 + 5.19Ze2 + 9.09t + 8.55Ze3 + 4.72v1 + 6.94v2. where H1 is the concentration of hypoxia-inducible factor 1α, H2 is the concentration of hypoxia-inducible factor 1β, v is the ion concentration in the body fluid, SpO2 is the oxygen content, ph is the pH value of the body fluid, η is the viscosity value of the body fluid, π1 is the osmotic pressure value of white blood cells and circulating tumor cells, π2 is the osmotic pressure value of red blood cells, Ze1 is the electrical impedance value of white blood cells and tumor cells, Ze2 is the electrical impedance value of red blood cells, Ze3 is the electrical impedance value of the body fluid after separation, t is the clotting time, v1 is the D-dimer concentration in the body fluid after separation, and v2 is the concentration of fibrinogen degradation products in the body fluid after separation. Step 2: Evaluate the subject's risk of chronic disease based on the n2 value. An n2 value of 120 or less is classified as low risk, an n2 value of 120-150 as medium risk, and an n2 value of 150 or more as high risk. The higher the value, the greater the risk.

[0087] Furthermore, when a detection probe for measuring the electrical impedance or charge of the body fluid is installed in the body fluid pH detection channel, the present invention also provides a method for diagnosing a chronic disease using data obtained from a chronic disease detection device based on body fluid testing.

[0088] Step 1: Based on Equation 3, calculate the n3 value using n3 = Ze4, where Ze4 is the electrical impedance value of the whole body fluid before body fluid cell separation, which is obtained by the detection probe installed in the body fluid pH detection channel.

[0089] Step 2: Evaluate the subject's risk of chronic disease based on the n3 value. An n3 value of 10 or less is classified as low risk, an n3 value of 10-14 is classified as medium risk, and an n3 value of 14 or more is classified as high risk. The higher the n3 value, the greater the risk. During the subclinical and clinical stages of chronic disease, the n3 value gradually increases, and the higher the value, the more recommended the patient is to undergo additional testing at the hospital and check their medical history.

[0090] This also applies to cases where the detection probes installed in the body fluid pH detection channel include a probe that measures the electrical impedance value Ze5 of the body fluid cell portion and a probe that measures the electrical impedance value Ze4 of the entire body fluid.

[0091] Method for assessing risk of chronic diseases and specific cancers using body fluid test data

[0092] Step 1: Obtain the electrical impedance value Ze4 of the entire body fluid, the electrical impedance value Ze5 of the cellular portion of the body fluid, and the electrical impedance value Ze3 of the separated body fluid.

[0093] Step 2: Calculate the n value based on one of the following formulas to assess the subject's cancer risk.

[0094] Formula 4: n4 = 1.73Ze4 + 1.89Ze3 + 1.36Ze5 (breast cancer risk assessment)

[0095] Formula 5: n5 = 1.79Ze4 + 1.85Ze3 + 1.73Ze5 (prostate cancer risk assessment)

[0096] Formula 6: n6 = 1.64Ze4 + 1.58Ze3 + 1.56Ze5 (Colorectal cancer risk assessment)

[0097] Formula 7: n7 = 1.67Ze4 + 1.88Ze3 + 1.49Ze5 (gastric cancer risk assessment)

[0098] Formula 8: n8 = 1.85Ze4 + 1.48Ze3 + 1.61Ze5 (liver cancer risk assessment)

[0099] Formula 9: n9 = 1.59Ze4 + 1.86Ze3 + 1.47Ze5 (thyroid cancer risk assessment)

[0100] Formula 10: n10 = 1.56Ze4 + 1.47Ze3 + 1.41Ze5 (pancreatic cancer risk assessment)

[0101] Formula 11: n11 = 1.37Ze4 + 1.93Ze3 + 1.52Ze5 (leukemia risk assessment)

[0102] Formula 12: n12 = 1.86Ze4 + 1.82Ze3 + 1.44Ze5 (kidney cancer risk assessment)

[0103] Formula 13: n13 = 1.72Ze4 + 1.52Ze3 + 1.85Ze5 (uterine fibroid risk assessment)

[0104] Formula 14: n14 = 1.35Ze4 + 1.57Ze3 + 1.69Ze5 (Oral cancer risk assessment)

[0105] Formula 15: n15 = 1.69Ze4 + 1.55Ze3 + 1.42Ze5 (ovarian cancer risk assessment)

[0106] Formula 16: n16 = 1.74Ze4 + 1.69Ze3 + 1.63Ze5 (brain cancer risk assessment)

[0107] Formula 17: n17 = 1.63Ze4 + 1.77Ze3 + 1.78Ze5 (nose cancer risk assessment)

[0108] Formula 18: n18 = 1.62Ze4 + 1.67Ze3 + 1.96Ze5 (pharyngeal cancer risk assessment)

[0109] Formula 19: n19 = 1.64Ze4 + 1.68Ze3 + 1.71Ze5 (esophageal cancer risk assessment)

[0110] Formula 20: n20 = 1.56Ze4 + 1.73Ze3 + 1.58Ze5 (cardia cancer risk assessment)

[0111] Formula 21: n21 = 1.74Ze4 + 1.98Ze3 + 1.89Ze5 (bile duct cancer risk assessment)

[0112] Formula 22: n22 = 1.55Ze4 + 1.85Ze3 + 1.91Ze5 (bladder cancer risk assessment)

[0113] Formula 23: n23 = 1.88Ze4 + 1.61Ze3 + 1.84Ze5 (lymphatic cancer risk assessment)

[0114] Formula 24: n24 = 1.75Ze4 + 1.82Ze3 + 1.86Ze5 (skin cancer risk assessment)

[0115] Formula 25: n25 = 1.91Ze4 + 1.66Ze3 + 1.57Ze5 (bone cancer risk assessment)

[0116] Formula 26: n26 = 1.87Ze4 + 1.78Ze3 + 1.72Ze5 (testicular cancer risk assessment)

[0117] Formula 27: n27 = 1.53Ze4 + 1.96Ze3 + 1.83Ze5 (gallbladder cancer risk assessment)

[0118] Formula 28: n28 = 1.69Ze4 + 1.83Ze3 + 1.56Ze5 (lung cancer risk assessment)

[0119] Step 3: Assess cancer risk

[0120] The risk of the subject developing the corresponding cancer is assessed based on the values ​​of n4 to n28 in Step 2. If the values ​​of n4 to n28 exceed 60, it indicates a high risk of the cancer, and further clinical testing is required.

[0121] Use process of this device

[0122] The collection tube containing the collected bodily fluid is placed in the testing device, and the built-in pump draws the bodily fluid and delivers it into the bodily fluid testing fluid channel provided by the present invention. A probe placed in the bodily fluid testing fluid channel collects relevant signals, and the collected signal values ​​are sent to a computer data processing module. The data processing module uses a built-in program to calculate a value n, which is compared with a reference value to determine the donor's risk of chronic disease. The results are presented to medical professionals through a display module.

[0123] Figure 2: Discrimination effect between tumor and healthy groups using formula 1

[0124] In this study, blood samples were collected from 1,103 cancer patients (605 with lung cancer, 110 with prostate cancer, 182 with breast cancer, and 206 with esophageal cancer) and 1,063 healthy controls from a health checkup center. Using the testing technology provided by the present invention and the algorithm of Formula 1, conventional tumor markers CEA (carcino-embryonic antigen) and AFP (alpha-fetoprotein) were simultaneously measured. Receiver operating characteristic (ROC) curves were constructed, and the area under the ROC curve (AUC) was calculated to compare the discriminatory efficacy of these three markers between cancer patients and healthy controls. As shown in Figure 2, when the ROC curve was used as the statistical method in this study, the algorithm provided by the present invention achieved an AUC of 0.910, a sensitivity of 84.3%, and a specificity of 92.6% for discriminating between chronic disease patients and healthy controls. This method significantly outperforms the discriminative effects of CEA and AFP, suggesting that Formula 1 can effectively distinguish between chronic disease patients and healthy subjects in case-control studies. The experimental results demonstrate that the device of the present invention enables the effective detection of chronic diseases.

[0125] Figure 3: Discrimination effect between tumor and healthy groups using formula 2

[0126] In this study, blood samples were collected from 1,103 cancer patients (605 lung cancer, 110 prostate cancer, 182 breast cancer, and 206 esophageal cancer) and 1,063 healthy controls from a health checkup center. Using the testing technology provided by the present invention and the algorithm of Formula 2, conventional tumor markers CEA and AFP were simultaneously measured. ROC curves were created and AUCs were calculated to compare the effectiveness of these three markers in distinguishing between cancer patients and healthy controls. As shown in Figure 3, when the ROC curve was used as the statistical method in this study, the algorithm provided by the present invention achieved an AUC of 0.908, a sensitivity of 84.6%, and a specificity of 92.7% in distinguishing between chronic disease patients and healthy controls. This method significantly outperformed the discriminative effectiveness of CEA and AFP, suggesting that Formula 2 can effectively distinguish between chronic disease patients and healthy controls in case-control studies. Experimental results demonstrate that the device of the present invention enables the effective detection of chronic diseases.

[0127] Figure 4: Discrimination effect between tumor and healthy groups using formula 3

[0128] In this study, blood samples were collected from 1,103 cancer patients (605 with lung cancer, 110 with prostate cancer, 182 with breast cancer, and 206 with esophageal cancer) and 1,063 healthy controls from a health checkup center. Using the testing technology provided by this invention and the algorithm of Formula 3, conventional tumor markers CEA (carcino-embryonic antigen) and AFP (alpha-fetoprotein) were simultaneously measured.

[0129] A receiver operator characteristic curve (ROC) was constructed and the area under the curve (AUC) was calculated to compare the effectiveness of these three methods in distinguishing between cancer patients and healthy subjects. As shown in Figure 4, when the ROC curve was used as the statistical method in this study, the algorithm provided by the present invention achieved an AUC of 0.864, a sensitivity of 82.4%, and a specificity of 89.6% in distinguishing between chronic disease patients and healthy subjects. This method outperformed the CEA and AFP methods in discriminating between chronic disease patients and healthy subjects, suggesting that Formula 3 can effectively distinguish between chronic disease patients and healthy subjects in case-control studies. The experimental results demonstrate that the device of the present invention enables the effective detection of chronic diseases.

[0130] Effectiveness of Cancer Detection Using Formulas 4 to 28

[0131] In this study, blood samples were collected from 4,457 cancer patients (605 lung cancer, 110 prostate cancer, 182 breast cancer, 206 esophageal cancer, 194 colorectal cancer, 195 gastric cancer, 129 liver cancer, 193 thyroid cancer, 137 pancreatic cancer, 196 leukemia, 153 kidney cancer, 164 uterine fibroids, 128 oral cancer, 183 ovarian cancer, 159 brain cancer, 156 nasal cancer, 176 pharyngeal cancer, 112 cardia cancer, 171 bile duct cancer, 189 bladder cancer, 122 lymphatic cancer, 135 skin cancer, 157 bone cancer, 179 testicular cancer, and 126 gallbladder cancer) and 1,063 healthy controls at a health checkup center. The testing technology provided by the present invention and the algorithms of Formulas 4 to 28 were used to simultaneously measure the conventional tumor markers CEA and AFP.

[0132] The ROC curves were created and the AUCs were calculated to compare the effectiveness of these three methods in distinguishing between cancer patients and healthy subjects. The experimental results showed that the sensitivity and specificity of the algorithms provided by the present invention (Formula 4 to Formula 28) for distinguishing between cancer patients and healthy subjects are as shown in Table 1. These results suggest that Formula 4 to Formula 28 can effectively distinguish between cancer patients and healthy subjects in case-control studies. The experimental results demonstrate that the device of the present invention enables effective cancer detection. [Table 1] TIFF2026502037000006.tif254155

[0133] The above description is merely a preferred embodiment of the present invention and does not limit the present invention in any form or substance. It should be noted that a person skilled in the art may make some improvements and supplements without departing from the spirit of the present invention, and these improvements and supplements are also within the scope of protection of the present invention. Any equivalent changes, modifications, advancements, etc. made by a person skilled in the art using the above technical content without departing from the spirit and scope of the present invention are all considered equivalent embodiments of the present invention. At the same time, any equivalent changes, modifications, and advancements made to the above embodiments based on the essential technology of the present invention are also within the technical scope of the present invention.

Claims

1. The present invention is characterized by comprising a body fluid testing fluid channel, a detection probe, a data processing module, and a data display module. The detection probe is provided within the body fluid testing fluid channel, and the detection probe is connected to the data processing module, which is connected to the data display module. The body fluid testing fluid channels include: a channel for detecting body fluid ions, cytokines, nucleic acids, proteins and their derivatives, or trace elements; a channel for detecting oxygen-soluble gas content; a channel for detecting body fluid pH; a channel for detecting fluid viscosity hydrodynamic characteristics; a channel for detecting physical characteristics including osmotic pressure of white blood cells and tumor cells; a channel for detecting electrical characteristics including electrical impedance and charge of white blood cells and tumor cells; a channel for detecting physical characteristics including osmotic pressure of red blood cells; a channel for detecting electrical characteristics including electrical impedance and charge of red blood cells; a channel for detecting electrical characteristics including electrical impedance and charge of separated body fluids; and a channel for detecting coagulation, anticoagulation, and fibrinolysis functions including coagulation factors, fibrinogen, D-dimer, platelets, etc.

2. A device for detecting chronic diseases based on body fluid testing according to claim 1. The device has a body fluid inlet and the following channels connected to the body fluid inlet: a channel for detecting body fluid ions, cytokines, nucleic acids, proteins and their derivatives or trace elements, a channel for detecting body fluid pH, a channel for detecting oxygen-soluble gas content, a channel for detecting the hydrodynamic properties of body fluid viscosity, and a body fluid cell separation channel.

3. A device for detecting chronic diseases based on body fluid testing according to claim 2. The device is provided with a cell separation microfluidic channel, one end of which is connected to a body fluid cell separation channel, and the other end of which is provided with a separated white blood cell and tumor cell channel, a separated red blood cell channel, and a separated body fluid channel.

4. A device for detecting chronic diseases based on body fluid testing according to claim 3. The separated leukocyte and tumor cell channels are connected to channels that detect physical properties of the leukocytes and tumor cells, including osmotic pressure, and channels that detect electrical properties of the leukocytes and tumor cells, including electrical impedance and charge, respectively.

5. A chronic disease detection device based on body fluid testing according to claim 4. The separated red blood cell channels are respectively connected to a channel for detecting a physical property of the red blood cells, including the osmotic pressure, and a channel for detecting an electrical property of the red blood cells, including the electrical impedance and charge.

6. A chronic disease detection device based on body fluid testing according to claim 5. The separated body fluid channels are connected to channels for detecting coagulation, anticoagulation, and fibrinolysis functions including coagulation factors, fibrinogen, D-dimer, and platelets, and channels for detecting electrical properties including electrical impedance and charge of the separated body fluid. Furthermore, the channels for detecting coagulation, anticoagulation, and fibrinolysis functions including coagulation factors, fibrinogen, D-dimer, and platelets are provided with coagulation factor channels for adding coagulation factors.

7. A method for treating a chronic disease using detection data obtained by a chronic disease detection device based on a body fluid test according to any one of claims 1 to 6. The method is characterized in that it comprises the following steps: Step 1: Based on Equation 1, The n1 value was calculated using the following equation: n1 = 3.73v + 6.38SpO2 + 6.29ph + 6.4η + 3.51π1 + 1.75Ze1 + 3.64π2 + 5.19Ze2 + 9.09t + 8.74Ze3 + 6.58v1 + 4.95v2, where v is the ion concentration of the body fluid, SpO2 is the oxygen content, ph is the pH value of the body fluid, η is the viscosity value of the body fluid, π1 is the osmotic pressure value of white blood cells and circulating tumor cells, π2 is the osmotic pressure value of red blood cells, Ze1 is the electrical impedance value of white blood cells and tumor cells, Ze2 is the electrical impedance value of red blood cells, Ze3 is the electrical impedance value of the body fluid after separation, t is the clotting time, v1 is the D-dimer concentration in the body fluid after separation, and v2 is the fibrinogen degradation product concentration in the body fluid after separation. Step 2: Evaluate the subject's risk of chronic disease based on the n1 value. n1 value below 105: low risk n1 value 105-135: Medium risk n1 value of 135 or more: High risk (the higher the value, the greater the risk)

8. Method according to claim 7 The method is characterized in that the chronic disease includes a tumor.

9. A device for detecting chronic diseases based on body fluid testing according to claim 1. This device detects cytokines ＊＊ Hypoxia-inducible factor 1α (HIF-1α) and / or hypoxia-inducible factor 1β (HIF-1β) ＊＊ The present invention is characterized by comprising:

10. A method for treating chronic diseases using detection data obtained by a chronic disease detection device based on body fluid testing according to claim 9. The method is characterized in that it comprises the following steps: Step 1: Based on Equation 2, Calculate the n2 value using n2 = 5.69H1 + 7.32H2 + 3.73v + 6.38SpO2 + 6.29ph + 6.4η + 3.51π1 + 1.75Ze1 + 3.64π2 + 5.19Ze2 + 9.09t + 8.55Ze3 + 4.72v1 + 6.94v2. H1: hypoxia-inducible factor 1α concentration, H2: hypoxia-inducible factor 1β concentration, v: body fluid ion concentration, SpO2: oxygen content, ph: body fluid pH value, η: body fluid viscosity value, π1: osmotic pressure value of white blood cells and circulating tumor cells, π2: osmotic pressure value of red blood cells, Ze1: electrical impedance value of white blood cells and tumor cells, Ze2: electrical impedance value of red blood cells, Ze3: electrical impedance value of body fluid after separation, t: coagulation time, v1: D-dimer concentration in body fluid after separation, v2: fibrinogen degradation product concentration in body fluid after separation. Step 2: Evaluate the subject's risk of chronic disease based on the n2 value. n2 value below 120: low risk n2 value 120-150: Medium risk n2 value of 150 or more: High risk (the higher the value, the greater the risk)

11. A device for detecting chronic diseases based on body fluid testing according to claim 1. The device features a body fluid pH detection channel equipped with a detection probe that detects physical properties of the body fluid, including electrical impedance and charge.

12. A method for treating chronic diseases using detection data obtained by a chronic disease detection device based on body fluid testing according to claim 11. The method is characterized in that it comprises the following steps: Step 1: Calculate the n3 value using equation 3, n3 = Ze4. Ze4: Electrical impedance value of the whole body fluid before body fluid cell separation The Ze4 value is obtained from a detection probe provided in the body fluid pH detection channel. Step 2: Evaluate the subject's risk of chronic disease based on the n3 value. n3 value below 10: low risk n3 value 10-14: Medium risk n3 value of 14 or more: High risk (the higher the value, the greater the risk) During the subclinical and clinical stages of chronic disease, n3 levels increase stepwise, with increasing levels indicating the need for further testing.

13. A device for detecting chronic diseases based on body fluid testing according to claim 11. The detection probes in the body fluid pH detection channel of this device are characterized by including a probe for detecting the electrical impedance value (Ze5) of the cellular portion of the body fluid, and a probe for detecting the electrical impedance value (Ze4) of the entire body fluid.

14. A method for treating chronic diseases using detection data obtained by a chronic disease detection device based on body fluid testing according to claim 13. The method is characterized in that it comprises the following steps: Step 1: Obtain the electrical impedance value Ze4 of the entire body fluid, the electrical impedance value Ze5 of the cellular portion of the body fluid, and the electrical impedance value Ze3 of the separated body fluid. Step 2: Assess specific cancer risk based on the following formula: Breast cancer: n4 = 1.73Ze4 + 1.89Ze3 + 1.36Ze5 Prostate cancer: n5 = 1.79Ze4 + 1.85Ze3 + 1.73Ze5 Colorectal cancer: n6 = 1.64Ze4 + 1.58Ze3 + 1.56Ze5 Gastric cancer: n7 = 1.67Ze4 + 1.88Ze3 + 1.49Ze5 Liver cancer: n8 = 1.85Ze4 + 1.48Ze3 + 1.61Ze5 Thyroid cancer: n9 = 1.59Ze4 + 1.86Ze3 + 1.47Ze5 Pancreatic cancer: n10 = 1.56Ze4 + 1.47Ze3 + 1.41Ze5 Leukemia: n11=1.37Ze4+1.93Ze3+1.52Ze5 Renal cancer: n12 = 1.86Ze4 + 1.82Ze3 + 1.44Ze5 Uterine fibroid: n13=1.72Ze4+1.52Ze3+1.85Ze5 Oral cancer: n14 = 1.35Ze4 + 1.57Ze3 + 1.69Ze5 Ovarian cancer: n15 = 1.69Ze4 + 1.55Ze3 + 1.42Ze5 Brain tumor: n16 = 1.74Ze4 + 1.69Ze3 + 1.63Ze5 Nasal tumor: n17 = 1.63Ze4 + 1.77Ze3 + 1.78Ze5 Pharyngeal cancer: n18 = 1.62Ze4 + 1.67Ze3 + 1.96Ze5 Esophageal cancer: n19 = 1.64Ze4 + 1.68Ze3 + 1.71Ze5 Cardia cancer: n20 = 1.56Ze4 + 1.73Ze3 + 1.58Ze5 Bile duct cancer: n21 = 1.74Ze4 + 1.98Ze3 + 1.89Ze5 Bladder cancer: n22 = 1.55Ze4 + 1.85Ze3 + 1.91Ze5 Lymphoma: n23 = 1.88Ze4 + 1.61Ze3 + 1.84Ze5 Skin cancer: n24 = 1.75Ze4 + 1.82Ze3 + 1.86Ze5 Bone cancer: n25 = 1.91Ze4 + 1.66Ze3 + 1.57Ze5 Testicular cancer: n26 = 1.87Ze4 + 1.78Ze3 + 1.72Ze5 Gallbladder cancer: n27 = 1.53Ze4 + 1.96Ze3 + 1.83Ze5 Lung cancer: n28 = 1.69Ze4 + 1.83Ze3 + 1.56Ze5 Step 3: Based on the values ​​of n4 to n28 obtained in Step 2, assess each cancer risk. If the value of n4 to n28 is greater than 60: This indicates a high risk of the corresponding cancer and further clinical testing is required.

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