WO2023216633A1

WO2023216633A1 - Sample real-time detection method and device, sample analyzer, and storage medium

Info

Publication number: WO2023216633A1
Application number: PCT/CN2022/144189
Authority: WO
Inventors: 方建伟; 霍子凌; 李国军
Original assignee: 深圳市帝迈生物技术有限公司
Priority date: 2022-05-07
Filing date: 2022-12-30
Publication date: 2023-11-16
Also published as: CN114636828B; CN114636828A

Abstract

The present application discloses a sample real-time detection method and device, a sample analyzer, and a storage medium. The method comprises: when a reaction curve satisfies a preset curve parameter condition, analyzing the reaction curve according to a current sample detection method, and detecting characteristics to be analyzed of the reaction curve; if the reaction curve does not have said characteristics, repeatedly detecting according to a preset detection period until said characteristics are detected or the length of the reaction curve is greater than a preset length threshold, and ending the detection; and if the reaction curve has said characteristics, obtaining a detection result on the basis of said characteristics. Data can be analyzed in real time on the basis of the reaction curve, the detection is stopped after the needed result is obtained, the detection time is shortened, and resources are saved.

Description

Sample real-time detection method, device, sample analyzer and storage medium

Technical field

The present invention relates to the technical field of medical detection and analysis, and in particular to a real-time detection method, device, sample analyzer and storage medium for samples.

Background technique

In medical or experimental scenarios, it is often necessary to test and analyze various samples. The coagulation analyzer is a routine testing medical device that clinically measures the content of various components in human blood, quantifies biochemical analysis results, and provides reliable digital basis for clinical diagnosis of various diseases in patients. Different types of coagulometers use different principles. Currently, the main detection methods used are: coagulation method, immunoturbidimetric method, latex agglutination method, etc.

technical problem

When analyzing coagulation projects, the instrument usually collects signals of a fixed length (for example, the D-Dimer project collects 200s signals), and then submits them to the algorithm for analysis to obtain the required results. The current detection and analysis methods require reactions and detections. longer time.

Technical solutions

This application provides a real-time sample detection method, device, sample analyzer and storage medium.

The first aspect provides a real-time detection method for samples, including:

When the reaction curve meets the preset curve parameter conditions, the reaction curve is processed according to the current sample detection method, and the characteristics to be analyzed of the reaction curve are detected;

If the characteristic to be analyzed does not appear in the reaction curve, the detection is repeated according to the preset detection cycle until the characteristic to be analyzed is detected, or the length of the reaction curve is greater than the preset length threshold, and the detection is terminated;

If the characteristic to be analyzed appears in the reaction curve, a detection result is obtained based on the characteristic to be analyzed.

In an optional implementation, the current sample detection method is a coagulation method; processing the reaction curve according to the current sample detection method and detecting the characteristics to be analyzed of the reaction curve includes:

Process the reaction curve and detect whether a plateau occurs in the reaction curve;

Obtaining detection results based on the characteristics to be analyzed includes:

The setting time of the reaction curve was calculated using the percentage method.

Process the reaction curve and detect the maximum value of the first derivative of the reaction curve;

The time corresponding to the maximum value of the first derivative in the reaction curve is determined to be the coagulation time.

In an optional embodiment, processing the reaction curve and detecting the maximum value of the first derivative of the reaction curve includes:

Calculate the first derivative of the reaction curve;

If the position corresponding to the maximum value in the first derivative of the reaction curve is smaller than the first curve length position, then the maximum value is determined to be the maximum value of the first derivative of the reaction curve.

Process the reaction curve and detect the maximum value of the second derivative of the reaction curve;

The time corresponding to the maximum value of the second derivative in the reaction curve is determined to be the coagulation time.

In an optional embodiment, processing the reaction curve and detecting the maximum value of the second derivative of the reaction curve includes:

Calculate the second derivative of the reaction curve;

If the position corresponding to the maximum value in the second derivative of the reaction curve is smaller than the second curve length position, then the maximum value is determined to be the maximum value of the second derivative of the reaction curve.

In an optional embodiment, the current sample detection method is an immunoturbidimetric method; processing the reaction curve according to the current sample detection method and detecting the characteristics to be analyzed of the reaction curve includes:

Calculate the maximum rate point of the reaction curve through an integration algorithm;

If the position of the maximum speed point is less than the third curve length position, determine the maximum speed point as the target speed point;

The absorbance change rate is calculated based on the target rate point and the corresponding concentration value is calculated using the calibration curve.

In an optional embodiment, the current sample detection method is a magnetic bead method; processing the reaction curve according to the current sample detection method and detecting the characteristics to be analyzed of the reaction curve includes:

Process the reaction curve and detect whether a freezing point appears in the reaction curve;

If the position of the freezing point is smaller than the fourth curve length position, the freezing point is determined to be the target freezing point.

In an optional implementation, the reaction curve satisfies preset curve parameter conditions, including:

The curve length of the reaction curve is greater than a preset length threshold, and the curve length is an integer multiple of the preset value.

In the second aspect, a real-time sample detection device is provided, including:

A detection module, used to process the reaction curve according to the current sample detection method when the reaction curve meets the preset curve parameter conditions, and detect the characteristics to be analyzed of the reaction curve;

The detection module is also configured to, if the characteristic to be analyzed does not appear in the reaction curve, repeat the detection according to the preset detection cycle until the characteristic to be analyzed is detected, or the length of the reaction curve is greater than the preset length threshold, End detection;

An analysis module is used to obtain detection results based on the characteristics to be analyzed if the characteristics to be analyzed appear in the reaction curve.

In a third aspect, a sample analyzer is provided, including a real-time sample detection device as described in the second aspect.

In a fourth aspect, a computer storage medium is provided. The computer storage medium stores one or more instructions. The one or more instructions are suitable for being loaded and executed by a processor as described in the first aspect and any one thereof. Steps for possible implementation.

beneficial effects

The sample real-time detection method in this application processes the reaction curve according to the current sample detection method when the reaction curve meets the preset curve parameter conditions to detect the characteristics to be analyzed of the reaction curve; if the reaction curve does not appear The characteristics to be analyzed are repeatedly detected according to the preset detection cycle until the characteristics to be analyzed are detected, or the length of the reaction curve is greater than the preset length threshold, and the detection is terminated; if the characteristics to be analyzed appear in the reaction curve, The detection results are obtained based on the characteristics to be analyzed, and the data can be analyzed in real time during the reaction process. After the required results are obtained, the detection is stopped to shorten the detection time and save resources.

Description of the drawings

In order to more clearly explain the technical solutions in the embodiments of the present application or the background technology, the drawings required to be used in the embodiments or the background technology of the present application will be described below.

Figure 1 is a schematic flow chart of a real-time sample detection method provided by an embodiment of the present application;

Figure 2 is a schematic diagram of a scattered light curve provided by an embodiment of the present application;

Figure 3 is a schematic diagram of a transmitted light curve provided by an embodiment of the present application;

Figure 4 is a schematic diagram of a coagulation scattered light curve percentage method provided by an embodiment of the present application;

Figure 5 is a schematic diagram of the detection process of the scattered light curve percentage method of coagulation method provided by the embodiment of the present application;

Figure 6 is a schematic diagram of the first derivative method of scattered light curve of a coagulation method provided by the embodiment of the present application;

Figure 7 is a schematic diagram of the detection process of the first derivative method of scattered light curve of a coagulation method provided by the embodiment of the present application;

Figure 8 is a schematic diagram of the second derivative method of scattered light curve of a coagulation method provided by the embodiment of the present application;

Figure 9 is a schematic diagram of the detection process of the second derivative method of scattered light curve of a coagulation method provided by the embodiment of the present application;

Figure 10 is a schematic diagram of the transmitted light curve VIL integral rate method of an immunoturbidimetric method provided by the embodiment of the present application;

Figure 11 is a schematic flow chart of the transmitted light curve VIL integral rate method of an immunoturbidimetric method provided by the embodiment of the present application;

Figure 12 is a schematic diagram of a magnetic bead method reaction curve provided by the embodiment of the present application;

Figure 13 is a schematic flow chart of a magnetic bead method detection provided by the embodiment of the present application;

Figure 14 is a schematic structural diagram of a real-time sample detection device provided by an embodiment of the present application.

Embodiments of the invention

In order to enable those in the technical field to better understand the solutions of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only These are part of the embodiments of this application, but not all of them. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of this application.

The terms "first", "second", etc. in the description and claims of this application and the above-mentioned drawings are used to distinguish different objects, rather than describing a specific sequence. Furthermore, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally also includes steps or units that are not listed, or optionally also includes Other steps or units inherent to such processes, methods, products or devices.

Reference herein to "an embodiment" means that a particular feature, structure or characteristic described in connection with the embodiment can be included in at least one embodiment of the present application. The appearances of this phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those skilled in the art understand, both explicitly and implicitly, that the embodiments described herein may be combined with other embodiments.

In the field of blood testing, detecting the response curve data characteristics of the sample (such as coagulation time, concentration value, etc.) cannot directly conclude whether there is a disease. Therefore, the real-time detection method of samples described in the embodiments of this application does not belong to the diagnosis and treatment methods of diseases.

The embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application.

Please refer to Figure 1. Figure 1 is a schematic flowchart of a real-time sample detection method provided by an embodiment of the present application. This method may include:

101. When the reaction curve meets the preset curve parameter conditions, process the above reaction curve according to the current sample detection method, and detect the characteristics to be analyzed of the above reaction curve.

The execution subject of the embodiment of the present application may be a real-time sample detection device. In specific applications, it may be a sample analyzer, such as a coagulation analyzer.

The above reaction curve can be reaction curve data obtained by performing a sample detection operation on the blood sample to be tested. Specifically, different operations can be used to obtain different reaction curves according to different sample detection methods.

Specifically, in the embodiments of the present application, the curve parameter conditions are preset, and the reaction curve is monitored in real time. When the reaction curve meets the preset curve parameter conditions, the reaction curve is used for analysis. The characteristics to be analyzed of the reaction curve can be detected first for further analysis. For different sample detection methods, the reaction curve processing and analysis methods used may be different, that is, the characteristics of the required curves to be analyzed may be different. The sample detection methods in the embodiments of the present application may include coagulation methods, immunoturbidimetric methods, etc. Different sample detection methods and their corresponding characteristics to be analyzed and analysis methods may be set as needed.

In an optional implementation, the above reaction curve satisfies the preset curve parameter conditions, including:

The curve length of the above reaction curve is greater than the preset length threshold, and the above curve length is an integer multiple of the preset value.

Specifically, the device starts to detect. When the length of the reaction curve is greater than the preset length threshold a, and the length of the reaction curve is an integer multiple of the preset value k, it starts to analyze the reaction curve data and input the reaction curve into the algorithm for processing.

Step 102 or step 103 may be performed after the above step 101.

102. If the above-mentioned characteristics to be analyzed do not appear in the above-mentioned reaction curve, the detection is repeated according to the preset detection cycle until the above-mentioned characteristics to be analyzed are detected, or the length of the above-mentioned reaction curve is greater than the preset length threshold, and the detection is terminated.

If the feature to be analyzed is not detected, it means that the reaction is still continuing and detection needs to continue. The above-mentioned preset detection cycle can be set and adjusted as needed, and the detection is repeated according to the preset detection cycle until the required feature to be analyzed is detected. Alternatively, the above-mentioned preset length threshold can be set and adjusted as needed. When it is detected that the length of the reaction curve is greater than the preset length threshold, the detection can be ended. For example, the preset length threshold of 5000 means that the maximum length allowed for curve analysis is 5000. If it exceeds Stopping calculations avoids long waits for invalid detections.

If the above characteristics to be analyzed are detected, step 103 is executed.

103. If the above-mentioned characteristics to be analyzed appear in the above-mentioned reaction curve, the detection result is obtained based on the above-mentioned characteristics to be analyzed.

If the required feature to be analyzed is detected, the detection result of the sample can be obtained based on the feature to be analyzed.

Different sample detection methods require different analysis characteristics of the reaction curves collected, and the analysis methods used are also different. The corresponding detection results to be obtained can be the same or different, such as coagulation time, coagulation point, concentration value, etc., which will be discussed in A detailed description will follow.

In an optional implementation, the current sample detection method is a coagulation method; the above step 101 may include:

A1. Analyze the above reaction curve and detect whether there is a plateau in the above reaction curve;

The above detection results are obtained based on the above characteristics to be analyzed, including:

A2. Use the above percentage method to calculate the coagulation time of the above reaction curve.

The coagulation method can use transmitted light or scattered light. Specifically, reference may be made to the schematic diagram of a scattered light curve shown in Figure 2 and the schematic diagram of a transmitted light curve shown in Figure 3, in which the abscissa of the reaction curve is the sampling point and the ordinate is the AD value. The response curve can be divided into baseline period, acceleration period, deceleration period and plateau period.

The first analytical method is introduced here: the coagulation method (percentage method).

Figure 4 is a schematic diagram of the scattered light curve percentage method of a coagulation method provided by the embodiment of the present application. In this method, the plateau period of the reaction curve can be detected, and then the percentage method is used to calculate the coagulation time, that is, on the curve in Figure 4 The marked black dot corresponds to the time.

Specifically, Figure 5 is a schematic flow chart of the coagulation scattered light curve percentage method detection provided by the embodiment of the present application. As shown in Figure 5, the method includes:

Step 1. The instrument starts to detect. When the curve length is greater than a and the curve length is an integer multiple of k, it starts analyzing the data and inputs the reaction curve data into the algorithm;

Step 2. The algorithm analyzes the reaction curve and detects whether a plateau occurs. If a plateau is detected, the coagulation time is calculated using the percentage method; if a plateau is not detected, it means that the reaction is still continuing and detection needs to continue;

Step 3. Detect every k data and repeat step 2 until a plateau is detected or the curve length > b, then the detection is terminated.

Among them, the above parameters a, b, k can be set as needed, for example a=200, b=5000, k=100, which means: when the length of the curve is greater than 200, the calculation starts, and the calculation is performed every 100 points. The maximum curve The length is allowed to be 5000. If it exceeds, the calculation will stop.

B1. Analyze the above reaction curve and detect the maximum value of the first derivative of the above reaction curve;

B2. Determine the time corresponding to the maximum value of the above-mentioned first-order derivative in the above-mentioned reaction curve as the solidification time.

Optional, the above step B1 includes:

Calculate the first derivative of the above reaction curve;

The second analysis method is introduced here: the solidification method (first derivative method).

Figure 6 is a schematic diagram of the first derivative method of scattered light curve of a coagulation method provided by the embodiment of the present application. In this method, the maximum value of the first derivative of the reaction curve can be detected to determine the coagulation time, that is, in Figure 6 The time corresponding to the small black dot marked on the curve.

Specifically, Figure 7 is a schematic diagram of the detection process of the first derivative method of scattered light curve of a coagulation method provided by the embodiment of the present application. As shown in Figure 7, the method includes:

Step 2. The algorithm analyzes the reaction curve and calculates the first derivative of the reaction curve;

Step 3. If the maximum value position of the first-order derivative of the reaction curve < curve length * p, and p is a floating point number less than 1, it means that the maximum value of the first-order derivative has been found, and the position of the maximum value of the first-order derivative is the solidification time; otherwise, It means that the reaction is still continuing and testing needs to continue;

Step 4. Detect every k pieces of data and repeat step 2 until the maximum value of the first derivative is detected or the curve length > b, then end the detection.

C1. Analyze the above reaction curve and detect the maximum value of the second derivative of the above reaction curve;

C3. Determine the time corresponding to the maximum value of the second-order derivative in the above reaction curve as the solidification time.

Optional, the above step C1 includes:

Calculate the second derivative of the above reaction curve;

If the position corresponding to the maximum value in the second-order derivative of the above-mentioned reaction curve is smaller than the second curve length position, then the above-mentioned maximum value is determined to be the maximum value of the second-order derivative of the above-mentioned reaction curve.

The third analysis method is introduced here: solidification method (second derivative method).

Figure 8 is a schematic diagram of the second derivative method of scattered light curve of a coagulation method provided by the embodiment of the present application. In this method, the maximum value of the second derivative of the reaction curve can be detected to determine the coagulation time, that is, in Figure 8 The time corresponding to the small black dot marked on the curve.

Specifically, Figure 9 is a schematic flow chart of the detection process of the second derivative method of the scattered light curve of a coagulation method provided by the embodiment of the present application. As shown in Figure 9, the method includes:

Step 2. The algorithm analyzes the reaction curve and calculates the second derivative of the reaction curve;

Step 3. If the maximum position of the second derivative of the reaction curve < curve length * p, and p is a floating point number less than 1, it means that the maximum value of the second derivative has been found, and the position of the maximum second derivative is the solidification time; otherwise, It means that the reaction is still continuing and testing needs to continue;

Step 4. Detect every k pieces of data and repeat step 1 until the maximum value of the second derivative is detected or the curve length > b, then the detection ends.

In an optional implementation, the current sample detection method is an immunoturbidimetric method; the above step 101 may include:

D1. Calculate the maximum rate point of the above reaction curve through the integral algorithm;

D2. If the position of the above-mentioned maximum speed point is smaller than the third curve length position, then determine the above-mentioned maximum speed point as the target speed point;

D3. Calculate the absorbance change rate based on the above target rate point, and use the calibration curve to calculate the corresponding concentration value.

The fourth analysis method is introduced here: immunoturbidimetric method (VIL integral rate method).

The immunoturbidimetric method uses transmitted light. Figure 10 is a schematic diagram of the VIL integral rate method of the transmitted light curve of an immunoturbidimetric method provided by the embodiment of the present application. In this method, the most intense time point of the reaction is found through the Vlin integral algorithm, and the absorbance change rate is obtained. Use polynomial regression algorithm to fit the curve, and then derive the derivation to find the maximum rate point Vmax. Then make a linear judgment around this point, and use the least squares method to calculate the slope of this interval, which is the absorbance change rate dOD/min.

Specifically, Figure 11 is a schematic flow chart of the transmitted light curve VIL integral rate method of an immunoturbidimetric method provided by the embodiment of the present application. As shown in Figure 11, the method includes:

Step 2. The algorithm analyzes the reaction curve and finds the maximum rate point through the Vlin integral algorithm;

Step 3. If the position of the maximum rate point < curve length * p, and p is a floating point number less than 1, it means that the maximum rate point has been found; otherwise, it means that the reaction is still continuing and detection needs to continue;

Step 4. Detect every k data, and repeat step 2 until the maximum rate point is detected or the curve length > b, then the detection ends;

Step 5. Make a linear judgment around the maximum rate point, and use the least squares method to calculate the slope of this interval, which is the absorbance change rate dOD/min;

Step 6. Use the calibration curve to calculate the corresponding concentration value.

In an optional implementation, the current sample detection method is a magnetic bead method; the above step 101 may include:

E1. Analyze the above reaction curve and detect whether there is a freezing point in the above reaction curve;

E2. If the position of the above-mentioned freezing point is smaller than the length position of the fourth curve, determine the above-mentioned freezing point as the target freezing point.

The fifth analysis method is introduced here: real-time detection for the magnetic bead method.

A schematic diagram of the reaction curve of a magnetic bead method is shown in Figure 12. The magnetic bead method in the embodiment of the present application adopts the eddy current induction method. A magnetic bead is added to the test sample, and it moves in the sample through the electromagnetic field. The reagent is added to the reaction cup, and the test starts automatically. The eddy current sensor senses the vibration of the test magnetic beads, and determines the coagulation time of the test sample by testing the amplitude change of the vibration of the magnetic beads.

Specifically, Figure 13 is a schematic flow chart of a magnetic bead method detection provided by the embodiment of the present application. As shown in Figure 13, the method includes:

Step 2. The algorithm analyzes the reaction curve and detects whether a freezing point occurs, and the position of the freezing point is <curve length*p; otherwise, it means that the reaction is still continuing and detection needs to continue;

Step 3. Detect every k data and repeat step 2 until the freezing point is detected or the curve length > b, then the detection is terminated.

For different sample detection methods, the reaction curve can be detected in real time, and different curve characteristics can be used for analysis to obtain corresponding detection results in a timely manner.

In the embodiment of the present application, when the reaction curve meets the preset curve parameter conditions, the reaction curve is analyzed according to the current sample detection method, and the characteristics to be analyzed of the reaction curve are detected; if the reaction curve does not appear the characteristics to be analyzed Characteristics, the detection is repeated according to the preset detection cycle until the characteristic to be analyzed is detected, or the length of the reaction curve is greater than the preset length threshold, and the detection is terminated; if the characteristic to be analyzed appears in the reaction curve, based on the characteristic to be analyzed, Analyze the characteristics to obtain the detection results, and analyze the data in real time based on the reaction curve. After the required results are obtained, the detection is stopped, shortening the detection time and saving resources.

Based on the description of the above embodiments of the sample real-time detection method, the embodiment of the present application also discloses a sample real-time detection device. As shown in Figure 14, the sample real-time detection device 1400 includes:

The detection module 141 is used to process the reaction curve according to the current sample detection method when the reaction curve meets the preset curve parameter conditions, and detect the characteristics to be analyzed of the reaction curve;

The detection module 141 is also configured to, if the characteristic to be analyzed does not appear in the reaction curve, repeat the detection according to the preset detection cycle until the characteristic to be analyzed is detected, or the length of the reaction curve is greater than the preset length threshold. , end the detection;

The analysis module 142 is used to obtain a detection result based on the characteristic to be analyzed if the characteristic to be analyzed appears in the reaction curve.

According to an embodiment of the present application, each step involved in the methods shown in Figure 1, Figure 5, Figure 7, Figure 9, Figure 11 and Figure 13 can be performed by the sample real-time detection device 1400 shown in Figure 14 The execution of each module will not be repeated here.

The sample real-time detection device 1400 in the embodiment of the present application can analyze the reaction curve according to the current sample detection method when the reaction curve meets the preset curve parameter conditions, and detect the characteristics to be analyzed of the reaction curve; if the reaction If the characteristic to be analyzed does not appear in the curve, the detection is repeated according to the preset detection cycle until the characteristic to be analyzed is detected, or the length of the reaction curve is greater than the preset length threshold, and the detection is terminated; if the characteristic to be analyzed appears in the reaction curve Analyze features, obtain detection results based on the features to be analyzed, analyze the data in real time based on the reaction curve, and stop detection after obtaining the required results, shortening detection time and saving resources.

Based on the description of the above method embodiments and device embodiments, embodiments of the present application also provide a sample analyzer. The sample analyzer may be a blood cell analyzer, and also includes a real-time sample detection device 1400 as shown in Figure 14.

The above-mentioned real-time sample detection device 1400 can be a hardware module or a software system, and can perform any of the steps in Figure 1, Figure 5, Figure 7, Figure 9, Figure 11 and Figure 13, which will not be described again here. The sample analyzer may also include other components or modules to implement corresponding sample reaction, sample analysis and other functions. The embodiment of the present application does not limit the specific hardware structure of the sample analyzer.

Optionally, the above-mentioned real-time sample detection device 1400 can also be used as a software system in other electronic devices (terminals) to execute the real-time sample detection method in the embodiment of the present application, which will not be described again here.

An embodiment of the present application also provides a computer storage medium (Memory). The computer storage medium is a memory device in an electronic device and is used to store programs and data. It can be understood that the computer storage media here may include built-in storage media in the electronic device, and of course may also include extended storage media supported by the electronic device. Computer storage media provides storage space that stores the operating system of the electronic device. Furthermore, one or more instructions suitable for being loaded and executed by the processor are also stored in the storage space. These instructions may be one or more computer programs (including program codes). It should be noted that the computer storage medium here can be a high-speed RAM memory or a non-volatile memory (non-volatile memory), such as at least one disk memory; optionally, it can also be at least one located far away from the aforementioned processor. computer storage media.

In one embodiment, one or more instructions stored in the computer storage medium can be loaded and executed by the processor to implement the corresponding steps in the above embodiment; in specific implementation, one or more instructions in the computer storage medium can be loaded by The processor loads and executes any steps of the methods in the embodiments shown in Figures 1, 5, 7, 9, 11 and 13, which will not be described again here.

Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the above-described devices and modules can be referred to the corresponding processes in the foregoing method embodiments, and will not be described again here.

In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the division of this module is only a logical function division. In actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not used. implement. The mutual coupling, direct coupling, or communication connection shown or discussed may be through some interfaces, and the indirect coupling or communication connection of devices or modules may be in electrical, mechanical, or other forms.

Modules described as separate components may or may not be physically separated, and components shown as modules may or may not be physical modules, that is, they may be located in one place, or they may be distributed to multiple network modules. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In the above embodiments, it may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on the computer, the processes or functions according to the embodiments of the present application are generated in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable device. The computer instructions may be stored in or transmitted over a computer-readable storage medium. The computer instructions may be transmitted from a website, computer, server, or data center via wires (e.g., coaxial cable, fiber optic, digital subscriber line). subscriber line (DSL)) or wireless (such as infrared, wireless, microwave, etc.) to another website, computer, server or data center. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center integrated with one or more available media. The available media may be read-only memory (read-only memory, ROM), or random access memory (random access memory (RAM), or magnetic media, such as floppy disks, hard disks, tapes, magnetic disks, or optical media, such as digital versatile discs versatile disc (DVD), or semiconductor media such as solid state drive (solid state disk, SSD), etc.

Claims

A device for real-time detection of samples, characterized by including:

A detection module, used to process the reaction curve when the reaction curve meets the preset curve parameter conditions, and detect the characteristics to be analyzed of the reaction curve;

The detection module is also configured to, if the characteristic to be analyzed does not appear in the reaction curve, repeat the detection according to the preset detection cycle until the characteristic to be analyzed is detected, or the length of the reaction curve is greater than the preset length threshold, End detection;

An analysis module is used to obtain detection results based on the characteristics to be analyzed if the characteristics to be analyzed appear in the reaction curve.
The device for real-time detection of samples according to claim 1, characterized in that the detection module is specifically used to: when the reaction curve meets the preset curve parameter conditions, process the reaction curve according to the current sample detection method, and detect the Characteristics of the response curve to be analyzed.
The real-time sample detection device according to claim 2, characterized in that the current sample detection method is a coagulation method; the detection module is specifically used to: when the reaction curve meets the preset curve parameter conditions, perform a test on the reaction curve. Processing, detecting whether a plateau period appears in the reaction curve, and the plateau period is the characteristic to be analyzed;

The analysis module is specifically used to calculate the coagulation time of the reaction curve using the percentage method.
The real-time sample detection device according to claim 2, characterized in that the current sample detection method is a coagulation method; the detection module is specifically used to: when the reaction curve meets the preset curve parameter conditions, perform a test on the reaction curve. Processing, detecting the maximum value of the first-order derivative of the reaction curve, and the maximum value of the first-order derivative is the feature to be analyzed;

The analysis module is specifically configured to determine that the time corresponding to the maximum value of the first derivative in the reaction curve is the coagulation time.
The real-time sample detection device according to claim 4, wherein the detection module is further configured to: calculate the first-order derivative of the reaction curve;

If the position corresponding to the maximum value in the first derivative of the reaction curve is smaller than the first curve length position, then the maximum value is determined to be the maximum value of the first derivative of the reaction curve.
The real-time sample detection device according to claim 2, characterized in that the current sample detection method is a coagulation method; the detection module is specifically used to: when the reaction curve meets the preset curve parameter conditions, perform a test on the reaction curve. Processing, detecting the maximum value of the second-order derivative of the reaction curve, and the maximum value of the second-order derivative is the feature to be analyzed;

The analysis module is specifically configured to determine that the time corresponding to the maximum value of the second derivative in the reaction curve is the coagulation time.
The device for real-time detection of samples according to claim 6, wherein the detection module is further configured to: calculate the second-order derivative of the reaction curve;

If the position corresponding to the maximum value in the second derivative of the reaction curve is smaller than the second curve length position, then the maximum value is determined to be the maximum value of the second derivative of the reaction curve.
The real-time sample detection device according to claim 2, characterized in that the current sample detection method is a magnetic bead method; the detection module is specifically used to: when the reaction curve meets the preset curve parameter conditions, the reaction curve Perform processing to detect whether a freezing point appears in the reaction curve, and the freezing point is the characteristic to be analyzed;

The analysis module is specifically configured to: if the position of the freezing point is smaller than the fourth curve length position, determine the freezing point as the target freezing point.
The real-time sample detection device according to claim 2, characterized in that the current sample detection method is an immunoturbidimetric method; the detection module is specifically used to: when the reaction curve meets the preset curve parameter conditions, calculate it through an integral algorithm The maximum rate point of the reaction curve; if the position of the maximum rate point is less than the third curve length position, then the maximum rate point is determined to be the target rate point, and the target rate point is the feature to be analyzed;

The analysis module is specifically configured to: calculate the absorbance change rate based on the target rate point, and use the calibration curve to calculate the corresponding concentration value.
A sample analyzer, characterized by comprising a real-time sample detection device according to claim 1.
A method for real-time detection of samples, which is characterized by including:

When the reaction curve meets the preset curve parameter conditions, the reaction curve is processed and the characteristics to be analyzed of the reaction curve are detected;

If the characteristic to be analyzed does not appear in the reaction curve, the detection is repeated according to the preset detection cycle until the characteristic to be analyzed is detected, or the length of the reaction curve is greater than the preset length threshold, and the detection is terminated;

If the characteristic to be analyzed appears in the reaction curve, a detection result is obtained based on the characteristic to be analyzed.
The real-time detection method of samples according to claim 11, characterized in that when the reaction curve meets the preset curve parameter conditions, the reaction curve is processed and the characteristics to be analyzed of the reaction curve are detected, including:

When the reaction curve meets the preset curve parameter conditions, the reaction curve is processed according to the current sample detection method, and the characteristics to be analyzed of the reaction curve are detected.
The real-time sample detection method according to claim 12, characterized in that the current sample detection method is a coagulation method; the reaction curve is processed according to the current sample detection method, and the characteristics to be analyzed of the reaction curve are detected ,include:

Process the reaction curve and detect whether a plateau occurs in the reaction curve;

Obtaining detection results based on the characteristics to be analyzed includes:

The setting time of the reaction curve was calculated using the percentage method.
The real-time sample detection method according to claim 12, characterized in that the current sample detection method is a coagulation method; the reaction curve is processed according to the current sample detection method, and the characteristics to be analyzed of the reaction curve are detected ,include:

Process the reaction curve and detect the maximum value of the first derivative of the reaction curve;

Obtaining detection results based on the characteristics to be analyzed includes:

The time corresponding to the maximum value of the first derivative in the reaction curve is determined to be the coagulation time.
The real-time detection method of samples according to claim 14, characterized in that, processing the reaction curve and detecting the maximum value of the first derivative of the reaction curve includes:

Calculate the first derivative of the reaction curve;

If the position corresponding to the maximum value in the first derivative of the reaction curve is smaller than the first curve length position, then the maximum value is determined to be the maximum value of the first derivative of the reaction curve.
The real-time sample detection method according to claim 12, characterized in that the current sample detection method is a coagulation method; the reaction curve is processed according to the current sample detection method, and the characteristics to be analyzed of the reaction curve are detected ,include:

Process the reaction curve and detect the maximum value of the second derivative of the reaction curve;

Obtaining detection results based on the characteristics to be analyzed includes:

The time corresponding to the maximum value of the second derivative in the reaction curve is determined to be the coagulation time.
The real-time detection method of samples according to claim 16, characterized in that, processing the reaction curve and detecting the maximum value of the second derivative of the reaction curve includes:

Calculate the second derivative of the reaction curve;

If the position corresponding to the maximum value in the second derivative of the reaction curve is smaller than the second curve length position, then the maximum value is determined to be the maximum value of the second derivative of the reaction curve.
The real-time sample detection method according to claim 12, characterized in that the current sample detection method is a magnetic bead method; the reaction curve is processed according to the current sample detection method, and the to-be-analyzed content of the reaction curve is detected. Features, including:

Process the reaction curve and detect whether a freezing point appears in the reaction curve;

Obtaining detection results based on the characteristics to be analyzed includes:

If the position of the freezing point is smaller than the fourth curve length position, the freezing point is determined to be the target freezing point.
The real-time sample detection method according to claim 12, characterized in that the current sample detection method is an immunoturbidimetric method; the reaction curve is processed according to the current sample detection method, and the to-be-determined value of the reaction curve is detected. Analysis features, including:

Calculate the maximum rate point of the reaction curve through an integration algorithm;

If the position of the maximum speed point is less than the third curve length position, determine the maximum speed point as the target speed point;

Obtaining detection results based on the characteristics to be analyzed includes:

The absorbance change rate is calculated based on the target rate point and the corresponding concentration value is calculated using the calibration curve.
The real-time detection method of samples according to claim 12, characterized in that the reaction curve satisfies preset curve parameter conditions, including:

The curve length of the reaction curve is greater than a preset length threshold, and the curve length is an integer multiple of the preset value.
A computer-readable storage medium, characterized by storing a computer program, which when executed by a processor causes the processor to execute the steps of the real-time sample detection method as claimed in claim 11.