CN114636828B - Sample real-time detection method and device, sample analyzer and storage medium - Google Patents
Sample real-time detection method and device, sample analyzer and storage medium Download PDFInfo
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Abstract
The application discloses a sample real-time detection method and device, a sample analyzer and a storage medium. The method comprises the following steps: when the reaction curve meets the preset curve parameter condition, analyzing the reaction curve according to the current sample detection method, and detecting the characteristic to be analyzed of the reaction curve; if the characteristic to be analyzed does not appear on the reaction curve, repeatedly detecting according to a preset detection period until the characteristic to be analyzed is detected or the length of the reaction curve is greater than a preset length threshold value, and finishing the detection; if the characteristics to be analyzed appear on the reaction curve, a detection result is obtained based on the characteristics to be analyzed, data can be analyzed in real time based on the reaction curve, detection is stopped after a required result is obtained, detection time is shortened, and resources are saved.
Description
Technical Field
The invention relates to the technical field of medical detection and analysis, in particular to a real-time sample detection method and device, a sample analyzer and a storage medium.
Background
In a medical or experimental scenario, various samples are often required to be tested and analyzed. The blood coagulation analyzer is a conventional detection medical device which measures the content of various components in human blood clinically, quantifies biochemical analysis results and provides reliable digital basis for clinically diagnosing various diseases of patients. The principles adopted by different types of thrombometers are also different, and the detection methods mainly adopted at present are as follows: coagulation, immunoturbidimetry, latex agglutination, and the like.
In the blood coagulation analysis, a signal with a fixed length is generally collected by an instrument (for example, a signal is collected for 200s in a D-Dimer analysis), and then the signal is sent to an algorithm for analysis to obtain a required result.
Disclosure of Invention
The application provides a sample real-time detection method and device, a sample analyzer and a storage medium.
In a first aspect, a method for detecting a sample in real time is provided, which includes:
when the reaction curve meets the preset curve parameter condition, processing the reaction curve according to the current sample detection method, and detecting the characteristic to be analyzed of the reaction curve;
if the characteristic to be analyzed does not appear on the reaction curve, repeatedly detecting according to a preset detection period until the characteristic to be analyzed is detected or the length of the reaction curve is larger than a preset length threshold value, and finishing detection;
and if the characteristic to be analyzed appears on the reaction curve, obtaining a detection result based on the characteristic to be analyzed.
In an alternative embodiment, the current sample detection method is a coagulation method; the processing the reaction curve according to the current sample detection method to detect the feature to be analyzed of the reaction curve comprises the following steps:
processing the reaction curve, and detecting whether the reaction curve has a plateau period;
the obtaining of the detection result based on the feature to be analyzed comprises:
the percent method was used to calculate the set time of the reaction curve.
In an alternative embodiment, the current sample detection method is a coagulation method; the processing the reaction curve according to the current sample detection method to detect the characteristic to be analyzed of the reaction curve comprises the following steps:
processing the reaction curve, and detecting the maximum value of the first derivative of the reaction curve;
the obtaining of the detection result based on the feature to be analyzed includes:
and determining the time corresponding to the maximum value of the first derivative in the reaction curve as the solidification time.
In an alternative embodiment, the processing the reaction curve to detect the maximum of the first derivative of the reaction curve includes:
calculating a first derivative of the reaction curve;
and if the position corresponding to the maximum value in the first derivative of the reaction curve is smaller than the length position of the first curve, determining the maximum value as the maximum value of the first derivative of the reaction curve.
In an alternative embodiment, the current sample detection method is coagulation; the processing the reaction curve according to the current sample detection method to detect the characteristic to be analyzed of the reaction curve comprises the following steps:
processing the reaction curve, and detecting the maximum value of the second derivative of the reaction curve;
the obtaining of the detection result based on the feature to be analyzed includes:
and determining the time corresponding to the maximum value of the second derivative in the reaction curve as the solidification time.
In an alternative embodiment, the processing the response curve to detect the maximum value of the second derivative of the response curve includes:
calculating a second derivative of the reaction curve;
and if the position corresponding to the maximum value in the second derivative of the reaction curve is smaller than the length position of a second curve, determining the maximum value as the maximum value of the second derivative of the reaction curve.
In an alternative embodiment, the current sample detection method is immunoturbidimetry; the processing the reaction curve according to the current sample detection method to detect the characteristic to be analyzed of the reaction curve comprises the following steps:
calculating a maximum rate point of the reaction curve by an integral algorithm;
if the position of the maximum speed point is smaller than the position of the length of the third curve, determining the maximum speed point as a target speed point;
the obtaining of the detection result based on the feature to be analyzed includes:
calculating a rate of change of absorbance based on the target rate point, and calculating a corresponding concentration value using a calibration curve.
In an alternative embodiment, the current sample detection method is a magnetic bead method; the processing the reaction curve according to the current sample detection method to detect the feature to be analyzed of the reaction curve comprises the following steps:
processing the reaction curve, and detecting whether the freezing point of the reaction curve appears;
the obtaining of the detection result based on the feature to be analyzed includes:
and if the position of the freezing point is less than the fourth curve length position, determining that the freezing point is the target freezing point.
In an alternative embodiment, the response curve satisfies a predetermined curve parameter condition, which includes:
the curve length of the reaction curve is larger than a preset length threshold value, and the curve length is integral multiple of the preset value.
In a second aspect, a real-time sample detection device is provided, which includes:
the detection module is used for processing the reaction curve according to the current sample detection method when the reaction curve meets the preset curve parameter condition, and detecting the characteristic to be analyzed of the reaction curve;
the detection module is further used for repeating detection according to a preset detection period if the characteristic to be analyzed does not appear on the reaction curve until the characteristic to be analyzed is detected or the length of the reaction curve is greater than a preset length threshold value, and ending the detection;
and the analysis module is used for obtaining a detection result based on the feature to be analyzed if the feature to be analyzed appears on the reaction curve.
In a third aspect, there is provided a sample analyzer comprising a real-time sample detection device as described in the second aspect.
In a fourth aspect, a computer storage medium is provided, which stores one or more instructions adapted to be loaded by a processor and to perform the steps of the first aspect and any possible implementation thereof as described above.
According to the sample real-time detection method, when a reaction curve meets a preset curve parameter condition, the reaction curve is processed according to a current sample detection method, and characteristics to be analyzed of the reaction curve are detected; if the characteristic to be analyzed does not appear on the reaction curve, repeatedly detecting according to a preset detection period until the characteristic to be analyzed is detected or the length of the reaction curve is larger than a preset length threshold value, and finishing detection; if the characteristic to be analyzed appears on the reaction curve, a detection result is obtained based on the characteristic to be analyzed, data can be analyzed in real time in the reaction process, and detection is stopped after a required result is obtained, so that the detection time is shortened, and resources are saved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments or the background art of the present application, the drawings required to be used in the embodiments or the background art of the present application will be described below.
Fig. 1 is a schematic flowchart of a real-time sample detection method according to an embodiment of the present disclosure;
FIG. 2 is a schematic diagram of a scattered light curve provided by an embodiment of the present application;
FIG. 3 is a schematic diagram of a transmission curve provided by an embodiment of the present application;
FIG. 4 is a graphical illustration of a percent scattering curve of a coagulation method according to an embodiment of the present disclosure;
FIG. 5 is a schematic diagram of a detection process by a coagulation scattering light curve percentage method according to an embodiment of the present application;
FIG. 6 is a schematic diagram illustrating a first derivative method of a scattering light curve of a coagulation method according to an embodiment of the present application;
FIG. 7 is a schematic diagram of a first derivative method detection process of a coagulation scattering light curve according to an embodiment of the present application;
FIG. 8 is a schematic diagram illustrating a second derivative method of a scattering light curve of a coagulation method according to an embodiment of the present application;
FIG. 9 is a schematic diagram of a second derivative method detection process of a scattering light curve by a solidification method according to an embodiment of the present application;
FIG. 10 is a chart illustrating a VIL integral rate method for immunoturbidimetric light transmission curves according to an embodiment of the present application;
FIG. 11 is a flow chart of a VIL integral rate method for turbidimetric immunometry transmission light curves according to an embodiment of the present application;
FIG. 12 is a schematic diagram illustrating a reaction curve of a magnetic bead method according to an embodiment of the present application;
FIG. 13 is a schematic view of a magnetic bead method detection process according to an embodiment of the present disclosure;
fig. 14 is a schematic structural diagram of a real-time sample detection device according to an embodiment of the present disclosure.
Detailed Description
In order to make the technical solutions of the present application better understood, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present application without making any creative effort belong to the protection scope of the present application.
The terms "first," "second," and the like in the description and claims of the present application and in the foregoing drawings are used for distinguishing between different objects and not for describing a particular sequential order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
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 application. The appearances of the 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. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein may be combined with other embodiments.
In the field of blood detection, detection of data characteristics (such as coagulation time, concentration value, etc.) of a reaction curve of a sample cannot directly draw a conclusion on whether a disease exists. Therefore, the real-time detection method of the sample described in the embodiment of the present application does not belong to the diagnosis and treatment method of the disease.
The embodiments of the present application will be described below with reference to the drawings.
Referring to fig. 1, fig. 1 is a schematic flow chart of a real-time sample detection method according to an embodiment of the present disclosure. The method can comprise the following steps:
101. and when the reaction curve meets the preset curve parameter condition, processing the reaction curve according to the current sample detection method, and detecting the characteristic to be analyzed of the reaction curve.
The execution subject of the embodiment of the present application may be a sample real-time detection device, and in a specific application, may be a sample analyzer, such as a blood coagulation analyzer.
The reaction curve may be reaction curve data obtained by performing a sample detection operation on a blood sample to be detected, and different reaction curves may be obtained by different operations according to different sample detection methods.
Specifically, curve parameter conditions are preset in the embodiment of the application, a reaction curve is monitored in real time, and when the reaction curve meets the preset curve parameter conditions, the reaction curve is used for analysis. The characteristics of the reaction curve to be analyzed can be detected first for further analysis. The reaction curve processing and analysis methods used may be different for different sample detection methods, i.e. the characteristics to be analyzed of the curve to be detected may be different. The sample detection method in the embodiment of the present application may include a coagulation method, an immunoturbidimetry method, and the like, and different sample detection methods and corresponding features to be analyzed and analysis methods thereof may be set as needed.
In an alternative embodiment, the reaction curve satisfies a predetermined curve parameter condition, which includes:
the curve length of the reaction curve is larger than a preset length threshold value, and the curve length is integral multiple of the preset value.
Specifically, the device starts to detect, and when the length of the reaction curve is greater than a preset length threshold value a and the length of the reaction curve is an integral multiple of a preset value k, the device starts to analyze the data of the reaction curve and inputs the reaction curve into an algorithm for processing.
Step 102 or step 103 may be performed after step 101 described above.
102. If the characteristic to be analyzed does not appear on the reaction curve, the detection is repeated according to a preset detection period until the characteristic to be analyzed is detected or the length of the reaction curve is greater than a preset length threshold value, and the detection is finished.
If the feature to be analyzed is not detected, the reaction continues, the detection is required to continue, the preset detection period can be set and adjusted according to the requirement, and the detection is repeated according to the preset detection period until the required feature to be analyzed is detected. Or, the preset length threshold may be set and adjusted as needed, and when the length of the response curve is detected to be greater than the preset length threshold, the detection may be ended, for example, the preset length threshold 5000 indicates that the maximum length of the curve analysis is allowed to be 5000, and if the maximum length of the curve analysis exceeds the preset length threshold, the calculation is stopped, so that the long-time waiting for invalid detection may be avoided.
If the feature to be analyzed is detected, step 103 is executed.
103. And if the characteristic to be analyzed appears on the reaction curve, obtaining a detection result based on the characteristic 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.
The characteristics to be analyzed of the reaction curves required to be collected by different sample detection methods are different, the analysis methods used are also different, and the detection results to be obtained may be the same or different, for example, the solidification time, the solidification point, the concentration value, and the like, and will be described in detail later.
In an alternative embodiment, the current sample detection method is a coagulation method; the step 101 may include:
a1, analyzing the reaction curve, and detecting whether the reaction curve has a plateau period;
the obtaining of the detection result based on the feature to be analyzed includes:
and A2, calculating the solidification time of the reaction curve by using the percentage method.
The solidification method may use transmitted light or scattered light. Specifically, reference may be made to a scattered light curve diagram shown in fig. 2 and a transmitted light curve diagram shown in fig. 3, wherein the abscissa of the reaction curve is the sampling point and the ordinate is the AD value. The response curves can be divided into a baseline phase, an acceleration phase, a deceleration phase and a plateau phase.
A first analysis method is presented here: coagulation method (percentage method).
Fig. 4 is a schematic diagram of a percentage method of a scattering light curve of a coagulation method provided in the embodiment of the present application, in which a plateau of a reaction curve can be detected, and then a coagulation time, that is, a time corresponding to a small black dot marked on the curve in fig. 4, is calculated by the percentage method.
Specifically, fig. 5 is a schematic diagram of a detection flow of a coagulation method by a percentage of scattering light curve method according to an embodiment of the present disclosure, as shown in fig. 5, the method includes:
step 1, an instrument starts to detect, when the length of a curve is greater than a and the length of the curve is integral multiple of k, data are analyzed, and the data of a reaction curve are input into an algorithm;
and 3, detecting every k data, repeating the step 2 until a plateau period is detected or the curve length is greater than b, and finishing the detection.
The parameters a, b, and k may be set as needed, for example, a =200, b =5000, and k =100, which indicate: when the length of the curve is larger than 200, the calculation is started, the calculation is performed every 100 points, the maximum length of the curve is allowed to be 5000, and the calculation is stopped when the maximum length of the curve exceeds the maximum length of the curve.
In an alternative embodiment, the current sample detection method is a coagulation method; the step 101 may include:
b1, analyzing the reaction curve, and detecting the maximum value of the first derivative of the reaction curve;
the obtaining of the detection result based on the feature to be analyzed includes:
and B2, determining the time corresponding to the maximum value of the first derivative in the reaction curve as the solidification time.
Optionally, step B1 includes:
calculating the first derivative of the reaction curve;
and if the position corresponding to the maximum value in the first derivative of the reaction curve is smaller than the first curve length position, determining the maximum value as the maximum value of the first derivative of the reaction curve.
A second analysis method is introduced here: coagulation method (first derivative method).
Fig. 6 is a schematic diagram illustrating a first derivative method of a scattered light curve of a coagulation method according to an embodiment of the present application, in which a maximum value of the first derivative of the reaction curve can be detected to determine a coagulation time, i.e., a time corresponding to a small black dot marked on the curve in fig. 6.
Specifically, fig. 7 is a schematic diagram of a detection flow of a coagulation scattered light curve first-order derivative method according to an embodiment of the present application, as shown in fig. 7, the method includes:
step 1, starting detection by an instrument, when the length of a curve is greater than a and the length of the curve is an integral multiple of k, starting to analyze data, and inputting the data of a reaction curve into an algorithm;
and 4, detecting every k data, repeating the step 2 until the maximum value of the first derivative is detected or the length of the curve is greater than b, and ending the detection.
In an alternative embodiment, the current sample detection method is a coagulation method; the step 101 may include:
c1, analyzing the reaction curve, and detecting the maximum value of a second derivative of the reaction curve;
the obtaining of the detection result based on the feature to be analyzed includes:
and C3, determining the time corresponding to the maximum value of the second derivative in the reaction curve as the solidification time.
Optionally, step C1 includes:
calculating the second derivative of the reaction curve;
and if the position corresponding to the maximum value in the second derivative of the reaction curve is smaller than the second curve length position, determining the maximum value as the maximum value of the second derivative of the reaction curve.
A third analysis method is presented here: coagulation method (second derivative method).
Fig. 8 is a schematic diagram illustrating a second derivative method of a scattered light curve of a coagulation method according to an embodiment of the present disclosure, in which a maximum value of the second derivative of a reaction curve can be detected to determine a coagulation time, i.e., a time corresponding to a small black dot marked on the curve in fig. 8.
Specifically, fig. 9 is a schematic diagram of a detection flow of a second derivative method of a scattering light curve of a coagulation method according to an embodiment of the present application, as shown in fig. 9, the method includes:
step 1, an instrument starts to detect, when the length of a curve is greater than a and the length of the curve is integral multiple of k, data are analyzed, and the data of a reaction curve are input into an algorithm;
and 4, detecting every k data, repeating the step 1 until the maximum value of the second derivative is detected or the length of the curve is greater than b, and finishing the detection.
In an alternative embodiment, the current sample detection method is immunoturbidimetry; the step 101 may include:
d1, calculating the maximum speed point of the reaction curve through an integral algorithm;
d2, if the position of the maximum speed point is smaller than the position of the length of the third curve, determining the maximum speed point as a target speed point;
the obtaining of the detection result based on the feature to be analyzed includes:
and D3, calculating the change rate of the absorbance based on the target rate point, and calculating a corresponding concentration value by using a calibration curve.
A fourth analytical method is presented herein: immunoturbidimetry (VIL integration rate method).
Immunoturbidimetry uses transmitted light. Fig. 10 is a schematic diagram of an immunoturbidimetric light transmission curve VIL integration rate method according to an embodiment of the present application, in which: the most drastic time point of the reaction was found by the Vlin integration algorithm and the absorbance change rate was obtained. The curve is fitted using a polynomial regression algorithm and then derived to find the maximum velocity point Vmax. And performing linear judgment around the point, and calculating the slope of the interval by using a least square method, namely the absorbance change rate dOD/min.
Specifically, fig. 11 is a schematic flow chart of a method for integrating rate of immunoturbidimetry transmittance curve VIL according to an embodiment of the present disclosure, as shown in fig. 11, the method includes:
step 1, an instrument starts to detect, when the length of a curve is greater than a and the length of the curve is integral multiple of k, data are analyzed, and the data of a reaction curve are input into an algorithm;
step 4, detecting every k data, repeating the step 2 until the maximum speed point is detected or the curve length is greater than b, and finishing the detection;
step 5, performing linear judgment around the maximum rate point, and calculating the slope of the interval by using a least square method, namely the absorbance change rate dOD/min;
and 6, calculating corresponding concentration values by using the calibration curve.
In an alternative embodiment, the current sample detection method is a magnetic bead method; the step 101 may include:
e1, analyzing the reaction curve, and detecting whether the reaction curve has a freezing point;
the obtaining of the detection result based on the feature to be analyzed includes:
and E2, if the position of the freezing point is less than the position of the length of the fourth curve, determining the freezing point as the target freezing point.
A fifth analysis method is introduced here: real-time detection for the magnetic bead method.
FIG. 12 is a schematic diagram showing a reaction curve of the magnetic bead method. The magnetic bead method in the embodiment of the application adopts an eddy current induction method, one magnetic bead is added into a test sample, the test sample moves in the sample through an electromagnetic field, a reagent is added into a reaction cup, and the test is automatically started. The eddy current sensor senses the vibration condition of the test magnetic beads, and the coagulation time of the test sample is judged through the amplitude change of the vibration of the test magnetic beads.
Specifically, fig. 13 is a schematic view of a detection process by a magnetic bead method according to an embodiment of the present disclosure, and as shown in fig. 13, the method includes:
step 1, starting detection by an instrument, when the length of a curve is greater than a and the length of the curve is an integral multiple of k, starting to analyze data, and inputting the data of a reaction curve into an algorithm;
and 3, detecting every k data, repeating the step 2 until a freezing point is detected or the curve length is greater than b, and ending the detection.
The reaction curve can be detected in real time by aiming at different sample detection methods, and different curve characteristics are adopted for analysis, so that corresponding detection results can be obtained in time.
In the embodiment of the application, when a reaction curve meets a preset curve parameter condition, analyzing the reaction curve according to a current sample detection method, and detecting the characteristic to be analyzed of the reaction curve; if the characteristic to be analyzed does not appear on the reaction curve, repeatedly detecting according to a preset detection period until the characteristic to be analyzed is detected or the length of the reaction curve is greater than a preset length threshold value, and finishing the detection; if the characteristics to be analyzed appear on the reaction curve, a detection result is obtained based on the characteristics to be analyzed, data can be analyzed in real time based on the reaction curve, detection is stopped after a required result is obtained, detection time is shortened, and resources are saved.
Based on the description of the embodiment of the real-time sample detection method, the embodiment of the present application further discloses a real-time sample detection apparatus, as shown in fig. 14, the real-time sample detection apparatus 1400 includes:
the detection module 141 is configured to, when a reaction curve meets a preset curve parameter condition, process the reaction curve according to a current sample detection method, and detect a feature to be analyzed of the reaction curve;
the detecting module 141 is further configured to, if the feature to be analyzed does not appear on the reaction curve, repeat detection according to a preset detection period until the feature to be analyzed is detected or the length of the reaction curve is greater than a preset length threshold, and end the detection;
and an analysis module 142, configured to, if the feature to be analyzed appears in the response curve, obtain a detection result based on the feature to be analyzed.
According to an embodiment of the present application, steps involved in the methods shown in fig. 1, fig. 5, fig. 7, fig. 9, fig. 11, and fig. 13 may be performed by modules in the real-time sample detection apparatus 1400 shown in fig. 14, and are not described herein again.
The real-time sample detection device 1400 in the embodiment of the present application can analyze a reaction curve according to a current sample detection method when the reaction curve meets a preset curve parameter condition, and detect a feature to be analyzed of the reaction curve; if the characteristic to be analyzed does not appear on the reaction curve, repeatedly detecting according to a preset detection period until the characteristic to be analyzed is detected or the length of the reaction curve is larger than a preset length threshold value, and finishing detection; if the characteristics to be analyzed appear on the reaction curve, a detection result is obtained based on the characteristics to be analyzed, data can be analyzed in real time based on the reaction curve, detection is stopped after a required result is obtained, detection time is shortened, and resources are saved.
Based on the description of the method embodiment and the device embodiment, the embodiment of the application also provides a sample analyzer. The sample analyzer may be a blood cell analyzer, and further comprises a real-time sample detection device 1400 as shown in fig. 14.
The real-time sample detection apparatus 1400 may be a hardware module or a software system, and may perform any steps shown in fig. 1, fig. 5, fig. 7, fig. 9, fig. 11, and fig. 13, which are not described herein again. The sample analyzer may further include other components or modules to implement functions such as corresponding sample reaction and sample analysis, and the embodiment of the present application does not limit a specific hardware structure of the sample analyzer.
Optionally, the sample real-time detection apparatus 1400 may also be applied to other electronic devices (terminals) as a software system, and execute the sample real-time detection method in this embodiment, which is not described herein again.
An embodiment of the present application further provides a computer storage medium (Memory), which is a Memory device in an electronic device and is used to store programs and data. It is understood that the computer storage medium herein may include both a built-in storage medium in the electronic device and, of course, an extended storage medium supported by the electronic device. The computer storage medium provides a storage space that stores an operating system of the electronic device. Also stored in the memory space are one or more instructions, which may be one or more computer programs (including program code), suitable for loading and execution by the processor. The computer storage medium may be a high-speed RAM memory, or may be a non-volatile memory (non-volatile memory), such as at least one disk memory; and optionally at least one computer storage medium located remotely from the processor.
In one embodiment, one or more instructions stored in a computer storage medium may be loaded and executed by a processor to implement the corresponding steps in the above embodiments; in a specific implementation, one or more instructions in the computer storage medium may be loaded by the processor and execute any step of the method in the embodiments shown in fig. 1, fig. 5, fig. 7, fig. 9, fig. 11, and fig. 13, which is not described herein again.
It can be clearly understood by those skilled in the art that, for convenience and simplicity of description, the specific working processes of the above-described apparatuses and modules may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. For example, the division of the module is only one logical division, and other divisions may be possible in actual implementation, for example, a plurality of modules or components may be combined or integrated into another system, or some features may be omitted, or not performed. The shown or discussed mutual coupling, direct coupling or communication connection may be an indirect coupling or communication connection of some interfaces, devices or modules, and may be in an electrical, mechanical or other form.
Modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical modules, may be located in one place, or may be distributed on a plurality of network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, 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. The procedures or functions according to the embodiments of the present application are all or partially generated when the computer program instructions are loaded and executed on a computer. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored on or transmitted over a computer-readable storage medium. The computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire (e.g., coaxial cable, fiber optic, digital Subscriber Line (DSL)), or wirelessly (e.g., infrared, wireless, microwave, etc.). 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, a data center, etc., that includes one or more of the available media. The usable medium may be a read-only memory (ROM), or a Random Access Memory (RAM), or a magnetic medium, such as a floppy disk, a hard disk, a magnetic tape, a magnetic disk, or an optical medium, such as a Digital Versatile Disk (DVD), or a semiconductor medium, such as a Solid State Disk (SSD).
Claims (10)
1. A real-time sample detection method is characterized by comprising the following steps:
when the reaction curve meets the preset curve parameter condition, processing the reaction curve according to the current sample detection method, and detecting the characteristic to be analyzed of the reaction curve, wherein the reaction curve meets the preset curve parameter condition and comprises the following steps: the curve length of the reaction curve is greater than a preset length threshold value and is an integral multiple of a preset value; the reaction curves required to be collected by different sample detection methods have different characteristics to be analyzed;
if the characteristic to be analyzed does not appear on the reaction curve, repeatedly detecting according to a preset detection period until the characteristic to be analyzed is detected or the length of the reaction curve is greater than a preset length threshold value, and finishing the detection;
if the characteristic to be analyzed appears on the reaction curve, obtaining a detection result based on the characteristic to be analyzed;
the current sample detection method is an immunoturbidimetry method; the processing the reaction curve according to the current sample detection method to detect the characteristic to be analyzed of the reaction curve comprises the following steps: calculating a maximum rate point of the reaction curve by an integral algorithm; if the position of the maximum speed point is smaller than the position of the length of the third curve, determining the maximum speed point as a target speed point;
the obtaining of the detection result based on the feature to be analyzed includes: calculating a rate of change of absorbance based on the target rate point, and calculating a corresponding concentration value using a calibration curve.
2. The real-time sample detection method according to claim 1, wherein the current sample detection method is a coagulation method; the processing the reaction curve according to the current sample detection method to detect the feature to be analyzed of the reaction curve comprises the following steps:
processing the reaction curve, and detecting whether the reaction curve has a plateau period;
the obtaining of the detection result based on the feature to be analyzed includes:
the percent method was used to calculate the set time of the reaction curve.
3. The real-time sample detection method according to claim 1, wherein the current sample detection method is a coagulation method; the processing the reaction curve according to the current sample detection method to detect the feature to be analyzed of the reaction curve comprises the following steps:
processing the reaction curve, and detecting the maximum value of the first derivative of the reaction curve;
the obtaining of the detection result based on the feature to be analyzed comprises:
and determining the time corresponding to the maximum value of the first derivative in the reaction curve as the solidification time.
4. The method for real-time detection of a sample according to claim 3, wherein the processing the reaction curve to detect the maximum value of the first derivative of the reaction curve comprises:
calculating a first derivative of the reaction curve;
and if the position corresponding to the maximum value in the first derivative of the reaction curve is smaller than the first curve length position, determining the maximum value as the maximum value of the first derivative of the reaction curve.
5. The real-time sample detection method according to claim 1, wherein the current sample detection method is a coagulation method; the processing the reaction curve according to the current sample detection method to detect the characteristic to be analyzed of the reaction curve comprises the following steps:
processing the reaction curve, and detecting the maximum value of the second derivative of the reaction curve;
the obtaining of the detection result based on the feature to be analyzed includes:
and determining the time corresponding to the maximum value of the second derivative in the reaction curve as the solidification time.
6. The method for real-time detection of a sample according to claim 5, wherein the processing the reaction curve to detect the maximum value of the second derivative of the reaction curve comprises:
calculating a second derivative of the reaction curve;
and if the position corresponding to the maximum value in the second derivative of the reaction curve is smaller than the length position of a second curve, determining the maximum value as the maximum value of the second derivative of the reaction curve.
7. The method for real-time detection of a sample according to claim 1, wherein the current sample detection method is a magnetic bead method; the processing the reaction curve according to the current sample detection method to detect the characteristic to be analyzed of the reaction curve comprises the following steps:
processing the reaction curve, and detecting whether the reaction curve has a freezing point;
the obtaining of the detection result based on the feature to be analyzed includes:
and if the position of the freezing point is less than the fourth curve length position, determining the freezing point as the target freezing point.
8. A real-time sample detection device, comprising:
the detection module is used for processing the reaction curve according to the current sample detection method and detecting the characteristic to be analyzed of the reaction curve when the curve length of the reaction curve is larger than a preset length threshold and is an integral multiple of a preset value; different sample detection methods need different characteristics to be analyzed of the acquired reaction curves;
the detection module is further used for repeating detection according to a preset detection period if the characteristic to be analyzed does not appear on the reaction curve until the characteristic to be analyzed is detected or the length of the reaction curve is greater than a preset length threshold value, and ending the detection;
the analysis module is used for obtaining a detection result based on the feature to be analyzed if the feature to be analyzed appears on the reaction curve;
the detection module is specifically configured to calculate a maximum rate point of the reaction curve through an integration algorithm if the current sample detection method is an immunoturbidimetry method; if the position of the maximum speed point is smaller than the position of the length of the third curve, determining the maximum speed point as a target speed point;
the analysis module is specifically configured to calculate an absorbance change rate based on the target rate point, and calculate a corresponding concentration value using a calibration curve.
9. A sample analyzer, characterized by comprising a real-time sample detection device according to claim 8.
10. A computer-readable storage medium, in which a computer program is stored which, when executed by a processor, causes the processor to carry out the steps of the method of real-time detection of a sample according to any one of claims 1 to 7.
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| CN202210489772.0A CN114636828B (en) | 2022-05-07 | 2022-05-07 | Sample real-time detection method and device, sample analyzer and storage medium |
| PCT/CN2022/144189 WO2023216633A1 (en) | 2022-05-07 | 2022-12-30 | Sample real-time detection method and device, sample analyzer, and storage medium |
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| CN202210489772.0A CN114636828B (en) | 2022-05-07 | 2022-05-07 | Sample real-time detection method and device, sample analyzer and storage medium |
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| CN114636828A (en) | 2022-06-17 |
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