CN118830816A - Microvascular endothelial function detection method, device, electronic equipment and storage medium - Google Patents

Abstract

The present disclosure provides a microvascular endothelial function detection method, device, electronic device and storage medium, the method comprising: obtaining a target user's basic blood oxygen saturation, a blood oxygen saturation net recovery time and a blood perfusion index increase; determining a vascular endothelial function abnormality index according to the basic blood oxygen saturation, the blood oxygen saturation net recovery time and the blood perfusion index increase; when the vascular endothelial function abnormality index is greater than an abnormality index threshold, determining that the target user has vascular endothelial dysfunction.

Description

Microvascular endothelial function detection method, device, electronic equipment and storage medium

Technical Field

The present disclosure relates to the field of data processing technology, and in particular to a microvascular endothelial function detection method, device, electronic equipment and storage medium.

Background Art

Endothelial cells are a single cell layer covering the innermost wall of blood vessels and are one of the most important metabolic and endocrine organs in the human body. An adult has about 10 ¹² endothelial cells, covering 400 to 500 ^m2 of the vascular lumen surface. Endothelial cells are the mechanical and biological barrier between the vascular wall and the lumen. In addition to maintaining the integrity of the vascular wall and the smoothness of the inner surface, they also have the functions of regulating vascular permeability and tension, anti-inflammatory, antioxidant, inhibiting proliferation, maintaining the balance of coagulation, anticoagulation and fibrinolysis, and promoting the formation of new blood vessels. Therefore, they play an important role in maintaining vascular homeostasis. Although endothelial cells have a strong repair ability, under the continuous action of cardiovascular risk factors, drugs, microorganisms, immune response and inflammation, the protective effect of endothelial cells on blood vessels is weakened or disappears, which is called endothelial dysfunction, which is manifested as insufficient vasodilation, platelet aggregation, inflammatory cell infiltration, and even thrombosis. Endothelial dysfunction is closely related to the occurrence and development of many diseases such as cardiovascular and cerebrovascular diseases, kidney diseases, preeclampsia, and bone and joint diseases. In particular, patients with cerebrovascular diseases have an increased risk of vascular dementia as they age, resulting in a series of diseases such as geriatric syndrome that seriously affect the quality of life. Endothelial dysfunction has been confirmed to be an independent predictor of cardiovascular and cerebrovascular events and is the earliest clinically measurable indicator of atherosclerotic vascular damage. Endothelial function testing can be used as a reliable indicator for cardiovascular and cerebrovascular risk stratification, which is of great significance for both primary and secondary prevention.

Among the related technologies, peripheral arterial tonometry (PAT) is widely used to measure microvascular endothelial function. For example, the EndoPAT software is used to automatically analyze the signal amplitude ratio before and after occlusion to obtain the endothelial function assessment index (Reactive Hyperemia Index, RHI). The endothelial function assessment index is used to determine whether there is endothelial function disorder. The higher the RHI value, the better the endothelial function. When RHI ≤ 1.67, it indicates endothelial dysfunction. However, the existing technology for detecting microvascular endothelial function requires the use of the EndoPAT instrument to measure the reactive hyperemia index, and the use of the EndoPAT instrument will make the entire detection process time-consuming, resulting in low detection efficiency. Therefore, how to improve the detection efficiency is an urgent problem that needs to be solved.

Summary of the invention

In order to solve the above technical problems or at least partially solve the above technical problems, the present disclosure provides a method for detecting microvascular endothelial function, which solves the technical problems of low efficiency and high detection cost of microvascular endothelial function detection in the prior art.

In order to achieve the above objectives, the embodiments of the present disclosure provide the following technical solutions:

In a first aspect, an embodiment of the present disclosure provides a method for detecting microvascular endothelial function, the method comprising:

Obtain the target user's basic blood oxygen saturation, blood oxygen saturation net recovery time, and blood perfusion index increase value;

Determining a vascular endothelial dysfunction index according to the basal blood oxygen saturation, the blood oxygen saturation net recovery time, and the blood perfusion index increase value;

When the vascular endothelial dysfunction index is greater than the abnormal index threshold, it is determined that the target user has vascular endothelial dysfunction.

As an optional implementation of the embodiment of the present disclosure, the obtaining of the basic blood oxygen saturation net recovery time of the target user includes:

The time for the target user's blood oxygen saturation to recover from the first blood oxygen saturation to the second blood oxygen saturation is recorded as a first duration; the first blood oxygen saturation is used to represent the blood oxygen saturation of the target user when the brachial artery blood flow is blocked for a preset duration, and the second blood oxygen saturation is obtained based on the basic blood oxygen saturation multiplied by a preset coefficient;

Recording the time from when the brachial artery blood flow of the target user is blocked to when the pulse is restored as the second duration;

A difference operation is performed between the first time length and the second time length to obtain the blood oxygen saturation net recovery time.

As an optional implementation of the embodiment of the present disclosure, the step of obtaining the blood perfusion index increase value of the target user includes:

Acquire a basic blood perfusion index and a first blood perfusion index of the target user; the first blood perfusion index is the maximum blood perfusion index of the target user during the process from when the brachial artery blood flow is blocked to when the pulse is restored;

The blood perfusion index increase value is determined according to the first blood perfusion index and the basic blood perfusion index.

As an optional implementation of the embodiment of the present disclosure, when the vascular endothelial dysfunction index is greater than the abnormal index threshold, before determining that the target user has vascular endothelial dysfunction, the method further includes:

Classifying the target user population according to the attributes of the target user population;

For different target user groups, determine the abnormal index thresholds corresponding to different target user groups.

As an optional implementation of the embodiment of the present disclosure, determining the vascular endothelial dysfunction index according to the basal blood oxygen saturation, the blood oxygen saturation net recovery time, and the blood perfusion index increase value includes:

According to the formula , calculate the endothelial dysfunction index;

in, Represents the endothelial dysfunction index. Indicates the net recovery time of blood oxygen saturation, Indicates the basic blood oxygen saturation, Indicates the increase in blood perfusion index.

As an optional implementation of the embodiment of the present disclosure, when the age of the target user is greater than or equal to a first preset age, determining the vascular endothelial dysfunction index according to the basal blood oxygen saturation, the blood oxygen saturation net recovery time, and the blood perfusion index increase value includes:

According to the formula , calculate the endothelial dysfunction index;

in, Represents the endothelial dysfunction index. Indicates the net recovery time of blood oxygen saturation, Indicates the basic blood oxygen saturation, Indicates the increase in blood perfusion index.

As an optional implementation of the embodiment of the present disclosure, when the age of the target user is greater than or equal to a second preset age and less than the first preset age, determining the vascular endothelial dysfunction index according to the basal blood oxygen saturation, the blood oxygen saturation net recovery time, and the blood perfusion index increase value includes:

According to the formula , calculate the endothelial dysfunction index;

in, Represents the endothelial dysfunction index. Indicates the net recovery time of blood oxygen saturation, Indicates the basic blood oxygen saturation, Indicates the increase in blood perfusion index.

In a second aspect, the present disclosure provides a microvascular endothelial function detection device, comprising:

An acquisition module is used to obtain the target user's basic blood oxygen saturation, blood oxygen saturation net recovery time, and blood perfusion index increase value;

A calculation module, used for determining a vascular endothelial dysfunction index according to the basic blood oxygen saturation, the blood oxygen saturation net recovery time, and the blood perfusion index increase value;

The determination module is used to determine that the target user has endothelial dysfunction when the endothelial dysfunction index is greater than an abnormal index threshold.

As an optional implementation of the embodiment of the present disclosure, the acquisition module is specifically used to:

The time for the target user's blood oxygen saturation to recover from the first blood oxygen saturation to the second blood oxygen saturation is recorded as a first duration; the first blood oxygen saturation is used to represent the blood oxygen saturation of the target user when the brachial artery blood flow is blocked for a preset duration, and the second blood oxygen saturation is obtained based on the basic blood oxygen saturation multiplied by a preset coefficient;

Recording the time from when the brachial artery blood flow of the target user is blocked to when the pulse is restored as the second duration;

A difference operation is performed between the first time length and the second time length to obtain the blood oxygen saturation net recovery time.

As an optional implementation of the embodiment of the present disclosure, the acquisition module is specifically used to:

Acquire a basic blood perfusion index and a first blood perfusion index of the target user; the first blood perfusion index is the maximum blood perfusion index of the target user during the process from when the brachial artery blood flow is blocked to when the pulse is restored;

The blood perfusion index increase value is determined according to the first blood perfusion index and the basic blood perfusion index.

As an optional implementation of the embodiment of the present disclosure, the device further includes:

A classification module, used to classify the target user population according to the attributes of the target user population;

The threshold determination module is used to determine the abnormal index thresholds corresponding to different target user groups.

As an optional implementation of the embodiment of the present disclosure, the computing module is specifically used for:

According to the formula , calculate the endothelial dysfunction index;

in, Represents the endothelial dysfunction index. Indicates the net recovery time of blood oxygen saturation, Indicates the basic blood oxygen saturation, Indicates the increase in blood perfusion index.

As an optional implementation of the embodiment of the present disclosure, when the age of the target user is greater than or equal to a first preset age, the calculation module is specifically configured to:

According to the formula , calculate the endothelial dysfunction index;

in, Represents the endothelial dysfunction index. Indicates the net recovery time of blood oxygen saturation, Indicates the basic blood oxygen saturation, Indicates the increase in blood perfusion index.

As an optional implementation of the embodiment of the present disclosure, when the age of the target user is greater than or equal to a second preset age and less than the first preset age, the calculation module is specifically configured to:

According to the formula , calculate the endothelial dysfunction index;

in, Represents the endothelial dysfunction index. Indicates the net recovery time of blood oxygen saturation, Indicates the basic blood oxygen saturation, Indicates the increase in blood perfusion index.

In a third aspect, an embodiment of the present disclosure provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the microvascular endothelial function detection method described in the first aspect or any embodiment of the first aspect is implemented.

In a fourth aspect, an embodiment of the present disclosure provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the microvascular endothelial function detection method described in the first aspect or any embodiment of the first aspect is implemented.

The microvascular endothelial function detection method provided by the present disclosure obtains the target user's basic blood oxygen saturation, blood oxygen saturation net recovery time and blood perfusion index increase value, determines the abnormal endothelial function index according to the basic blood oxygen saturation, blood oxygen saturation net recovery time and blood perfusion index increase value, and determines that the target user has endothelial dysfunction when the abnormal endothelial function index is greater than the abnormal index threshold. It can be seen that the embodiment of the present disclosure can automatically determine whether the target user has endothelial dysfunction through the computer through the inspection information after obtaining the inspection information of the target user, that is, obtaining the basic blood oxygen saturation, blood oxygen saturation net recovery time and blood perfusion index increase value, without using the EndoPAT instrument, thereby improving the detection efficiency.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

FIG1 is a schematic diagram of a process for detecting microvascular endothelial function in an embodiment of the present disclosure;

FIG2 is a schematic diagram of the structure of a microvascular endothelial function detection device in an embodiment of the present disclosure;

FIG. 3 is a schematic diagram of the structure of an electronic device according to an embodiment of the present disclosure.

DETAILED DESCRIPTION

In order to more clearly understand the above-mentioned objectives, features and advantages of the present disclosure, the scheme of the present disclosure will be further described below. It should be noted that the embodiments of the present disclosure and the features in the embodiments can be combined with each other without conflict.

In the following description, many specific details are set forth to facilitate a full understanding of the present disclosure, but the present disclosure may also be implemented in other ways different from those described herein; it is obvious that the embodiments in the specification are only part of the embodiments of the present disclosure, rather than all of the embodiments.

Relational terms such as “first” and “second” in the description and claims of the present disclosure are merely used to distinguish one entity or operation from another entity or operation, but do not necessarily require or imply any such actual relationship or order between these entities or operations.

In the embodiments of the present disclosure, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present disclosure should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a concrete way. In addition, in the description of the embodiments of the present disclosure, unless otherwise specified, the meaning of "multiple" refers to two or more.

Terminology explanation:

EndoPAT: A device that uses PAT peripheral arterial tension signal technology to perform non-invasive endothelial function testing of microcirculation.

RHI (Reactive Hyperemia index): Peripheral artery reactive hyperemia index. During the measurement of microvascular endothelial function using EndoPAT, RHI reflects the endothelial cell-mediated relaxation effect. If RHI ≤ 1.67, it indicates endothelial dysfunction.

：Blood oxygen saturation refers to the ratio of oxygen combined with hemoglobin in the blood, usually expressed as a percentage.

PI (Perfusion Index): Blood perfusion index refers to the ratio of blood flow in skin tissue to the volume of skin tissue. The higher the PI value, the greater the blood flow in the skin tissue and the more adequate the blood supply.

In the prior art, EndoPAT software is used to automatically analyze the ratio of signal amplitudes before and after occlusion to obtain the Reactive Hyperemia Index (RHI). Peripheral artery tension measurement measures the change in fingertip tension before and after blocking the brachial artery blood flow through the pressure receptors of the finger probe to reflect the degree of microvascular reactive hyperemia. EndoPAT quantifies the change in endothelial-mediated vascular tension and obtains this change information through a 5-minute short-term occlusion of the brachial artery (using a standard blood pressure cuff). When the cuff is released, the blood flow shock causes endothelium-dependent relaxation. This expansion manifests as reactive hyperemia, which can be captured by EndoPAT and manifested as an increase in the amplitude of the PAT signal. EndoPAT software is used to automatically analyze the ratio of signal amplitudes before and after occlusion to obtain the Reactive Hyperemia Index (RHI). The specific operation of EndoPAT is as follows: At room temperature of 21-24°C, turn on the EndoPAT system and preheat for at least 20 minutes. The patient lies or sits quietly for 15 minutes to allow the cardiovascular system to return to steady state and adjust to room temperature. The EndoPAT sensor is embedded in the front end of the index finger of both hands, one side is used to detect endothelial function, and the other side is used as a control to monitor systemic vascular changes. The standard cuff is tied 2 cm above the brachial artery on the same side of the arm where the endothelial function is tested. At this time, there is no congestion. First, 5 minutes of baseline tension data are collected. Then the cuff is inflated to block the brachial artery blood flow for 5 minutes and the data is collected. Finally, the cuff is quickly deflated to use the shear force of blood flow on the vessel wall to cause endothelial-dependent vasodilation. At the same time, the tension signal increased in this process is collected for 5 minutes (manifested as an increase in the amplitude of the PAT signal). Finally, the computer EndoPAT software calculates the ratio of the signal amplitude before and after the blockade, and then corrects the test results according to the control data on the other side to obtain the RHI. The entire test process takes 15 minutes. The higher the RHI value, the better the endothelial function. When RHI ≤ 1.67, it indicates endothelial dysfunction. However, the EndoPAT instrument used in the existing technology for testing microvascular endothelial function is expensive, requires additional consumables, is not portable, and the entire testing process is time-consuming, resulting in low testing efficiency. Therefore, how to improve testing efficiency and reduce testing costs is an urgent problem to be solved.

In view of the above problems, the embodiment of the present disclosure provides a microvascular endothelial function detection method, which obtains the basic blood oxygen saturation, the net recovery time of blood oxygen saturation and the increase of blood perfusion index of the target user, determines the abnormal endothelial function index according to the basic blood oxygen saturation, the net recovery time of blood oxygen saturation and the increase of blood perfusion index, and determines that the target user has endothelial dysfunction when the abnormal endothelial function index is greater than the abnormal index threshold. It can be seen that the embodiment of the present disclosure can automatically determine whether the target user has endothelial dysfunction through the detection information after obtaining the inspection information of the target user, that is, obtaining the basic blood oxygen saturation, the net recovery time of blood oxygen saturation and the increase of blood perfusion index, thereby avoiding the use of EndoPAT instrument to cause the entire detection process to be more time-consuming, thereby improving the detection efficiency. At the same time, since the entire detection process does not use the expensive EndoPAT instrument to measure the reactive hyperemia index, the detection cost can be reduced.

In one embodiment, as shown in FIG1 , a method for detecting microvascular endothelial function is provided, comprising the following steps S11-S13:

S11. Obtain the target user's basic blood oxygen saturation, blood oxygen saturation net recovery time, and blood perfusion index increase value.

Among them, the basic blood oxygen saturation refers to the target user sitting in an empty stomach state, with one arm naturally relaxed and flat on the table, and the blood pressure cuff tied 2-3cm above the elbow of the upper arm on the same side, with the palm facing down. The hand and wrist remain motionless during the entire test, and the finger oximeter is used to measure the blood oxygen saturation of the finger on the same side ( ). Under normal circumstances, the reference value of arterial blood oxygen saturation is 95%-100%. If arterial blood flow is blocked, blood oxygen saturation will gradually decrease due to tissue oxygen consumption.

The net recovery time of blood oxygen saturation refers to the time required for blood oxygen saturation to return to normal levels after a period of low oxygen.

The perfusion index (PI) is a value measured by a pulse oximeter, which reflects the ratio of pulsating blood flow to non-pulsating blood flow in peripheral tissues, that is, the perfusion capacity of arterial blood flow. Under normal circumstances, the PI value is usually between 4 and 5. The PI value is affected by many factors, including the measurement method, measurement site, ambient temperature, etc. The increase in the perfusion index can be calculated by the perfusion index. Similarly, the target user sits in a fasting state, with one arm naturally relaxed and flat on the table, the blood pressure cuff is tied 2-3 cm above the elbow of the upper arm on the same side, with the palm facing down, and the hand and wrist remain motionless during the entire test. The perfusion index can be obtained by measuring the finger on the same side with the oximeter.

Measurement method of blood perfusion index (PI): To obtain blood perfusion index (PI), it can usually be measured by pulse oximetry monitoring equipment. PI is a measure of the blood perfusion index ( ) readings, which reflects the pulse strength at the sensor site and is an indicator of blood flow at the monitoring site, which can help assess the body's circulatory efficiency. The PI calculation formula is PI = (PS/NS) × 100, where PS represents the pulsating signal (AC) and NS represents the non-pulsating signal (DC).

In some embodiments, the above step S11 (obtaining the net recovery time of blood oxygen saturation) can be implemented in the following manner:

(1) Recording the time it takes for the target user's blood oxygen saturation to recover from the first blood oxygen saturation to the second blood oxygen saturation as a first duration.

The first blood oxygen saturation is used to represent the blood oxygen saturation of the target user when the brachial artery blood flow is blocked for a preset time, and the second blood oxygen saturation is obtained based on the basic blood oxygen saturation multiplied by a preset coefficient.

Among them, the preset coefficient can be 95%.

(2) Recording the time from when the brachial artery blood flow of the target user is blocked to when the pulse is restored as the second time duration.

Specifically, complete blockage of brachial artery blood flow was determined by rapid inflation of the cuff to a pressure higher than 60 mmHg of systolic blood pressure or disappearance of the blood oxygen saturation reading. When the brachial artery blood flow was completely blocked for 5 minutes, the cuff was deflated and the pulse time detected by the oximeter was recorded (i.e., the second duration). The time to recover to 95% (i.e. the first duration) and the maximum value of PI. When the brachial artery blood flow is completely blocked, theoretically the blood oxygen saturation in that area will drop significantly, because the blockage will interrupt the blood flow to that area, resulting in the tissue in that area not getting enough oxygen. However, the specific value of blood oxygen saturation will be affected by many factors, including the length of time of blockage, the individual's health status, and whether there are other circulation pathways.

(3) Performing a difference operation on the first time duration and the second time duration to obtain the net recovery time of the blood oxygen saturation.

Specifically, the blood oxygen saturation net recovery time is used to represent the difference between the time when the target user's blood oxygen saturation recovers from the first blood oxygen saturation to the second blood oxygen saturation and the time when the pulse of the target user is detected after the brachial artery blood flow is blocked for a preset time. The blood oxygen saturation net recovery time is calculated by the formula blood oxygen saturation net recovery time t = (first time - second time).

In some embodiments, the above step S11 (obtaining the blood perfusion index increase value) can be implemented in the following manner:

a. Obtaining a basic blood perfusion index and a first blood perfusion index of the target user.

The first blood perfusion index is the maximum blood perfusion index during the process from when the brachial artery blood flow of the target user is blocked to when the pulse is restored.

b. Determine the blood perfusion index increase value according to the first blood perfusion index and the basic blood perfusion index.

By formula , and the increased value of blood perfusion index is calculated. Among them, Indicates the increase in blood perfusion index.

S12. Determine a vascular endothelial dysfunction index according to the basal blood oxygen saturation, the blood oxygen saturation net recovery time, and the blood perfusion index increase value.

In some embodiments, the vascular endothelial dysfunction index can be calculated according to the following formula: ;

in, Represents the endothelial dysfunction index. Indicates the net recovery time of blood oxygen saturation, Indicates the basic blood oxygen saturation, Indicates the increase in blood perfusion index.

Specifically, the pilot experiment included multiple patients. It should be noted that these multiple patients were randomly selected from the entire population and were not screened for a specific population. That is, when the target user does not belong to a specific population, the endothelial dysfunction index can be calculated according to the above formula. Based on EndoPAT measurement of reactive hyperemia index (RHI), RHI ≤ 1.67 was used as the gold standard for endothelial dysfunction. Through multivariate logistic regression, , , Endothelial dysfunction was jointly predicted and the endothelial dysfunction score (ED score) was calculated based on the results of logistic regression.

For example, the pilot study included 98 patients with an average age of 60 years and a male ratio of 47.2%. The EDscore was not normally distributed, with a median and interquartile range of -0.24 (-0.57, 0.27), a minimum EDscore of -1.87, and a maximum EDscore of 2.78. By calculating the EDscore to predict vascular endothelial dysfunction, the area under the ROC curve (AUC) was 0.7, and the optimal cutoff value was -0.38. EDscore>-0.38 indicates endothelial dysfunction, and the sensitivity of judging endothelial dysfunction is 82.6% and the specificity is 61.5%.

In some embodiments, when the age of the target user is greater than or equal to the first preset age, the above step S12 (determining the vascular endothelial dysfunction index according to the basic blood oxygen saturation, the blood oxygen saturation net recovery time, and the blood perfusion index increase value) can be implemented as follows:

According to the formula , calculate the endothelial dysfunction index;

in, Represents the endothelial dysfunction index. Indicates the net recovery time of blood oxygen saturation, Indicates the basic blood oxygen saturation, Indicates the increase in blood perfusion index.

In the embodiment of the present disclosure, the first preset age is 60 years old for example. A preliminary experiment includes 98 patients, 52 of whom are elderly people over 60 years old. Through multivariate logistic regression, , , The combined prediction of endothelial dysfunction was calculated based on the results of Logistic regression. EDscore was not normally distributed, with a median and interquartile range of 0.120 (-0.474, 0.623), a minimum EDscore of -1.43, and a maximum EDscore of 3.02. The AUC for predicting endothelial dysfunction by EDscore was 0.716, with an optimal cutoff value of -0.029. The sensitivity of judging endothelial dysfunction was 77.8%, and the specificity was 68%.

In some embodiments, when the age of the target user is greater than or equal to the second preset age and less than the first preset age, the above step S12 (determining the vascular endothelial dysfunction index according to the basic blood oxygen saturation, the blood oxygen saturation net recovery time, and the blood perfusion index increase value) can be implemented as follows:

According to the formula , calculate the endothelial dysfunction index;

in, Represents the endothelial dysfunction index. Indicates the net recovery time of blood oxygen saturation, Indicates the basic blood oxygen saturation, Indicates the increase in blood perfusion index.

In the embodiment of the present disclosure, the first preset age is 60 years old and the second preset age is 45 years old. The pilot experiment includes 98 patients, of which 38 are between 45 and 60 years old. Through multivariate logistic regression, the , , The combined prediction of endothelial dysfunction was calculated based on the results of Logistic regression. EDscore was not normally distributed, with a median and interquartile range of -0.885 (-1.360, -0.447), a minimum EDscore of -2.38, and a maximum EDscore of 2.03. The AUC for predicting endothelial dysfunction by EDscore was 0.705, with an optimal cutoff value of -0.735. The sensitivity of judging endothelial dysfunction was 66.7%, and the specificity was 73.1%.

In some embodiments, when the target user is a male, the above step S12 (determining the vascular endothelial dysfunction index according to the basic blood oxygen saturation, the blood oxygen saturation net recovery time, and the blood perfusion index increase value) can be implemented as follows:

According to the formula , calculate the endothelial dysfunction index;

in, Represents the endothelial dysfunction index. Indicates the net recovery time of blood oxygen saturation, Indicates the basic blood oxygen saturation, Indicates the increase in blood perfusion index.

In the present embodiment, the pilot experiment included 98 patients, of which 63 were males. Through multivariate logistic regression, , , The combined prediction of endothelial dysfunction was calculated based on the results of logistic regression. EDscore was not normally distributed, with a median and interquartile range of -0.386 (-0.877, 0.020), a minimum EDscore of -2.18, and a maximum EDscore of 3.79. The AUC for predicting endothelial dysfunction by EDscore was 0.728, with an optimal cutoff value of -0.495. The sensitivity of judging endothelial dysfunction was 85.2%, and the specificity was 61.1%.

In some embodiments, when the target user is a female, the above step S12 (determining the vascular endothelial dysfunction index according to the basic blood oxygen saturation, the blood oxygen saturation net recovery time, and the blood perfusion index increase value) can be implemented as follows:

According to the formula , calculate the endothelial dysfunction index;

in, Represents the endothelial dysfunction index. Indicates the net recovery time of blood oxygen saturation, Indicates the basic blood oxygen saturation, Indicates the increase in blood perfusion index.

In the present embodiment, the pilot experiment included 98 patients, of which 35 were female. Through multivariate logistic regression, , , The combined prediction of endothelial dysfunction was calculated based on the results of Logistic regression. EDscore was not normally distributed, with a median and interquartile range of 0.322 (-0.207, 0.636), a minimum EDscore of -2.69, and a maximum EDscore of 1.43. The AUC for predicting endothelial dysfunction by EDscore was 0.628, with an optimal cutoff value of -0.090. The sensitivity of judging endothelial dysfunction was 89.5%, and the specificity was 50.0%.

In some embodiments, when the target user is a patient with hypertension, the above step S12 (determining the vascular endothelial dysfunction index according to the basic blood oxygen saturation, the blood oxygen saturation net recovery time, and the blood perfusion index increase value) can be implemented as follows:

According to the formula , calculate the endothelial dysfunction index;

in, Represents the endothelial dysfunction index. Indicates the net recovery time of blood oxygen saturation, Indicates the basic blood oxygen saturation, Indicates the increase in blood perfusion index.

In the present embodiment, the pilot experiment included 98 patients, of whom 63 had hypertension. Through multivariate logistic regression, , , The combined prediction of endothelial dysfunction was calculated based on the results of Logistic regression. EDscore was not normally distributed, with a median and interquartile range of -0.464 (-0.959, 0.232), a minimum EDscore of -2.00, and a maximum EDscore of 3.08. The AUC for predicting endothelial dysfunction by EDscore was 0.736, with an optimal cutoff value of -0.282. The sensitivity of judging endothelial dysfunction was 69.2%, and the specificity was 81.1%.

In some embodiments, when the target user is a non-hypertensive patient, the above step S12 (determining the vascular endothelial dysfunction index according to the basal blood oxygen saturation, the blood oxygen saturation net recovery time, and the blood perfusion index increase value) can be implemented as follows:

According to the formula , calculate the endothelial dysfunction index;

in, Represents the endothelial dysfunction index. Indicates the net recovery time of blood oxygen saturation, Indicates the basic blood oxygen saturation, Indicates the increase in blood perfusion index.

In the present embodiment, the pilot experiment included 98 patients, of whom 35 did not suffer from hypertension. Through multivariate logistic regression, , , The combined prediction of endothelial dysfunction was calculated based on the results of Logistic regression. EDscore was not normally distributed, with a median and interquartile range of 0.259 (-0.147, 0.871), a minimum EDscore of -1.31, and a maximum EDscore of 2.62. The AUC for predicting endothelial dysfunction by EDscore was 0.707, and the optimal cutoff value was 0.186. The sensitivity of judging endothelial dysfunction was 75.0%, and the specificity was 60.0%.

In some embodiments, when the target user is a diabetic patient, the above step S12 (determining the vascular endothelial dysfunction index according to the basal blood oxygen saturation, the blood oxygen saturation net recovery time, and the blood perfusion index increase value) can be implemented as follows:

According to the formula , calculate the endothelial dysfunction index;

in, Represents the endothelial dysfunction index. Indicates the net recovery time of blood oxygen saturation, Indicates the basic blood oxygen saturation, Indicates the increase in blood perfusion index.

In the present embodiment, the pilot experiment included 98 patients, of whom 35 had diabetes. Through multivariate logistic regression, , , The combined prediction of endothelial dysfunction was calculated based on the results of Logistic regression. EDscore was not normally distributed, with a median and interquartile range of -0.058 (-0.553, 0.102), a minimum EDscore of -1.41, and a maximum EDscore of 1.71. The AUC for predicting endothelial dysfunction by EDscore was 0.661, and the optimal cutoff value was 0.138. The sensitivity of judging endothelial dysfunction was 75.0%, and the specificity was 57.9%.

In some embodiments, when the target user is a non-diabetic patient, the above step S12 (determining the vascular endothelial dysfunction index according to the basal blood oxygen saturation, the blood oxygen saturation net recovery time, and the blood perfusion index increase value) can be implemented as follows:

According to the formula , calculate the endothelial dysfunction index;

in, Represents the endothelial dysfunction index. Indicates the net recovery time of blood oxygen saturation, Indicates the basic blood oxygen saturation, Indicates the increase in blood perfusion index.

In the present embodiment, the pilot experiment included 98 patients, of whom 63 did not have diabetes. Through multivariate logistic regression, , , The combined prediction of endothelial dysfunction was calculated based on the results of Logistic regression. EDscore was not normally distributed, with a median and interquartile range of -0.324 (-0.634, 0.448), a minimum EDscore of -2.03, and a maximum EDscore of 2.94. The AUC for predicting endothelial dysfunction by EDscore was 0.776, with an optimal cutoff value of -0.475. The sensitivity of judging endothelial dysfunction was 90.0%, and the specificity was 69.7%.

In some embodiments, when the target user is a smoker, the above step S12 (determining the vascular endothelial dysfunction index according to the basal blood oxygen saturation, the blood oxygen saturation net recovery time, and the blood perfusion index increase value) can be implemented as follows:

According to the formula , calculate the endothelial dysfunction index;

in, Represents the endothelial dysfunction index. Indicates the net recovery time of blood oxygen saturation, Indicates the basic blood oxygen saturation, Indicates the increase in blood perfusion index.

In the present embodiment, the pilot experiment included 98 patients, of whom 41 were smokers. Through multivariate logistic regression, , , The combined prediction of endothelial dysfunction was calculated based on the results of Logistic regression. EDscore was not normally distributed, with a median and interquartile range of -0.253 (-0.734, 0.057), a minimum EDscore of -1.96, and a maximum EDscore of 2.41. The AUC for predicting endothelial dysfunction by EDscore was 0.684, with an optimal cutoff value of -0.135. The sensitivity of judging endothelial dysfunction was 55.6%, and the specificity was 78.3%.

In some embodiments, when the target user is a non-smoker, the above step S12 (determining the vascular endothelial dysfunction index according to the basic blood oxygen saturation, the blood oxygen saturation net recovery time, and the blood perfusion index increase value) can be implemented as follows:

According to the formula , calculate the endothelial dysfunction index;

in, Represents the endothelial dysfunction index. Indicates the net recovery time of blood oxygen saturation, Indicates the basic blood oxygen saturation, Indicates the increase in blood perfusion index.

In the present embodiment, the pilot experiment included 98 patients, of whom 57 were non-smokers. Through multivariate logistic regression, , , The combined prediction of endothelial dysfunction was calculated based on the results of Logistic regression. EDscore was not normally distributed, with a median and interquartile range of -0.123 (-0.602, 0.555), a minimum EDscore of -2.02, and a maximum EDscore of 2.41. The AUC for predicting endothelial dysfunction by EDscore was 0.724, with an optimal cutoff value of -0.350. The sensitivity of judging endothelial dysfunction was 89.3%, and the specificity was 62.1%.

In some embodiments, before executing the above step S13 (when the vascular endothelial dysfunction index is greater than the abnormal index threshold, determining that the target user has vascular endothelial dysfunction), the following steps may also be executed:

Classifying the target user population according to the attributes of the target user population;

For different target user groups, determine the abnormal index thresholds corresponding to different target user groups.

Among them, the attributes of the target user group can be gender, age, whether or not they suffer from a certain chronic disease, etc.

Specifically, through the Logistic regression analysis method, the patient's important clinical characteristics are converted into risk scores, so as to determine the risk probability of a certain disease condition based on the score. The multi-factor Logistic regression model is evaluated based on the ROC curve (receiver operating characteristics curve), the ROC curve is drawn, and the optimal cutoff value (in the present embodiment, the optimal cutoff value is the abnormal index threshold) is determined. Among them, the closer the AUC (Area Under Curve, the area under the curve, is the area under the ROC curve and the coordinate axis) is to 1.0, the higher the authenticity of the detection method. The closer the ROC curve is to the upper left corner, the higher the accuracy of the model. The point on the ROC curve closest to the upper left corner is the best threshold with the least classification error, and its total number of false positives and false negatives is the least. By drawing the ROC curve, a point can be found, and the sum of the sensitivity and specificity corresponding to the point is the largest. This point is usually considered to be the optimal cutoff value. The balance between sensitivity (true positive rate) and specificity (true negative rate) is measured by calculating the Youden Index (calculated by adding the sensitivity and specificity of the test and then subtracting 1 from the sum), and the point with the maximum Youden Index is the optimal cutoff value. The optimal cutoff value is determined to maximize the correct identification of positive results while avoiding misclassification of negative results as positive.

Exemplarily, the false positive rate (i.e., 1-specificity in the disclosed embodiment) and the true positive rate (i.e., sensitivity in the disclosed embodiment) of each threshold cut-off point in the Logistic regression model are plotted in a vector graph to obtain the ROC curve of the specific model. That is, at each selected threshold cut-off point, a false positive rate and a true positive rate can be calculated, and then the false positive rate (x-axis) and the true positive rate (y-axis) are plotted in a vector graph.

S13: When the vascular endothelial dysfunction index is greater than the abnormal index threshold, it is determined that the target user has vascular endothelial dysfunction.

Specifically, for different target user groups, the abnormal index thresholds corresponding to the different target user groups are determined, so as to determine whether the target users have endothelial dysfunction according to the abnormal index thresholds corresponding to the different target user groups.

For example, when the target population is not clearly classified, the abnormal index threshold of the patient is calculated according to the formula, and if the abnormal index threshold EDscore>-0.38, it indicates endothelial dysfunction. When the target user is a hypertensive patient, the abnormal index threshold of the patient is calculated according to the formula, and if the abnormal index threshold EDscore>-0.282, it indicates endothelial dysfunction.

The microvascular endothelial function detection method provided by the present disclosure obtains the target user's basic blood oxygen saturation, blood oxygen saturation net recovery time and blood perfusion index increase value, determines the abnormal endothelial function index according to the basic blood oxygen saturation, blood oxygen saturation net recovery time and blood perfusion index increase value, and determines that the target user has endothelial dysfunction when the abnormal endothelial function index is greater than the abnormal index threshold. It can be seen that the embodiment of the present disclosure can automatically determine whether the target user has endothelial dysfunction through the detection information after obtaining the target user's inspection information, that is, obtaining the basic blood oxygen saturation, blood oxygen saturation net recovery time and blood perfusion index increase value, thereby improving the detection efficiency. At the same time, since the steps of the entire process are all executed by a computer, there is no need to use expensive EndoPAT instruments, so the detection cost can be reduced.

In one embodiment, as shown in FIG2 , a microvascular endothelial function detection device 200 is provided, comprising:

An acquisition module 210 is used to acquire the target user's basic blood oxygen saturation, blood oxygen saturation net recovery time, and blood perfusion index increase value;

A calculation module 220, configured to determine a vascular endothelial dysfunction index according to the basal blood oxygen saturation, the blood oxygen saturation net recovery time, and the blood perfusion index increase value;

The determination module 230 is used to determine that the target user has endothelial dysfunction when the endothelial dysfunction index is greater than an abnormality index threshold.

As an optional implementation of the embodiment of the present disclosure, the acquisition module is specifically used to:

The time for the target user's blood oxygen saturation to recover from the first blood oxygen saturation to the second blood oxygen saturation is recorded as a first duration; the first blood oxygen saturation is used to represent the blood oxygen saturation of the target user when the brachial artery blood flow is blocked for a preset duration, and the second blood oxygen saturation is obtained based on the basic blood oxygen saturation multiplied by a preset coefficient;

Recording the time from when the brachial artery blood flow of the target user is blocked to when the pulse is restored as the second duration;

A difference operation is performed between the first time length and the second time length to obtain the blood oxygen saturation net recovery time.

As an optional implementation of the embodiment of the present disclosure, the acquisition module is specifically used to:

Acquire a basic blood perfusion index and a first blood perfusion index of the target user; the first blood perfusion index is the maximum blood perfusion index of the target user during the process from when the brachial artery blood flow is blocked to when the pulse is restored;

The blood perfusion index increase value is determined according to the first blood perfusion index and the basic blood perfusion index.

As an optional implementation of the embodiment of the present disclosure, the device further includes:

A classification module, used to classify the target user population according to the attributes of the target user population;

The threshold determination module is used to determine the abnormal index thresholds corresponding to different target user groups.

As an optional implementation of the embodiment of the present disclosure, the computing module is specifically used for:

According to the formula , calculate the endothelial dysfunction index;

in, Represents the endothelial dysfunction index. Indicates the net recovery time of blood oxygen saturation, Indicates the basic blood oxygen saturation, Indicates the increase in blood perfusion index.

As an optional implementation of the embodiment of the present disclosure, when the age of the target user is greater than or equal to a first preset age, the calculation module is specifically configured to:

According to the formula , calculate the endothelial dysfunction index;

in, Represents the endothelial dysfunction index. Indicates the net recovery time of blood oxygen saturation, Indicates the basic blood oxygen saturation, Indicates the increase in blood perfusion index.

As an optional implementation of the embodiment of the present disclosure, when the age of the target user is greater than or equal to a second preset age and less than the first preset age, the calculation module is specifically configured to:

According to the formula , calculate the endothelial dysfunction index;

in, Represents the endothelial dysfunction index. Indicates the net recovery time of blood oxygen saturation, Indicates the basic blood oxygen saturation, Indicates the increase in blood perfusion index.

The microvascular endothelial function detection device provided by the present disclosure obtains the target user's basic blood oxygen saturation, blood oxygen saturation net recovery time and blood perfusion index increase value, and determines the abnormal endothelial function index according to the basic blood oxygen saturation, blood oxygen saturation net recovery time and blood perfusion index increase value. When the abnormal endothelial function index is greater than the abnormal index threshold, it is determined that the target user has endothelial dysfunction. It can be seen that after obtaining the inspection information of the target user, that is, obtaining the basic blood oxygen saturation, blood oxygen saturation net recovery time and blood perfusion index increase value, the computer can automatically determine whether the target user has endothelial dysfunction through the inspection information, without using the EndoPAT instrument, thereby improving the detection efficiency.

The specific definition of the microvascular endothelial function detection device can be found in the definition of the microvascular endothelial function detection method above, which will not be repeated here. Each module in the above-mentioned microvascular endothelial function detection device can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor of the electronic device in the form of hardware, or can be stored in the processor of the electronic device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

The embodiment of the present disclosure also provides an electronic device, and FIG3 is a schematic diagram of the structure of the electronic device provided by the embodiment of the present disclosure. As shown in FIG3, the electronic device provided by the present embodiment includes: a memory 31 and a processor 32, the memory 31 is used to store a computer program; the processor 32 is used to execute the steps performed by any embodiment of the microvascular endothelial function detection method provided by the above method embodiment when calling the computer program. The electronic device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the electronic device is used to provide computing and control capabilities. The memory of the electronic device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. When the computer program is executed by the processor, a microvascular endothelial function detection method is implemented. The display screen of the electronic device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the electronic device can be a touch layer covered on the display screen, or a key, trackball or touchpad set on the housing of the computer device, or an external keyboard, touchpad or mouse.

Those skilled in the art will understand that the structure shown in FIG. 3 is merely a block diagram of a partial structure related to the scheme of the present disclosure, and does not constitute a limitation on the computer device to which the scheme of the present disclosure is applied. The specific electronic device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

In one embodiment, the battery leakage monitoring system provided by the present disclosure can be implemented in the form of a computer, and the computer program can be run on the electronic device shown in Figure 3. The memory of the electronic device can store various program modules constituting the microvascular endothelial function detection device of the electronic device, such as the acquisition module 210, the calculation module 220 and the determination module 230 shown in Figure 2. The computer program composed of various program modules enables the processor to execute the steps of the microvascular endothelial function detection method of the electronic device of each embodiment of the present disclosure described in this specification.

The embodiment of the present disclosure further provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the microvascular endothelial function detection method provided by the above method embodiment is implemented.

Those skilled in the art will appreciate that the embodiments of the present disclosure may be provided as methods, systems, or computer program products. Therefore, the present disclosure may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present disclosure may take the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program code.

The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and/or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

Computer readable media include permanent and non-permanent, removable and non-removable storage media. Storage media can be implemented by any method or technology to store information, and the information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

The above description is only a specific embodiment of the present disclosure, so that those skilled in the art can understand or implement the present disclosure. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present disclosure. Therefore, the present disclosure will not be limited to the embodiments described herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims (10)

1. A method for detecting microvascular endothelial function, characterized in that the method comprises: Obtain the target user's basic blood oxygen saturation, blood oxygen saturation net recovery time, and blood perfusion index increase value; Determining a vascular endothelial dysfunction index according to the basal blood oxygen saturation, the blood oxygen saturation net recovery time, and the blood perfusion index increase value; When the vascular endothelial dysfunction index is greater than the abnormal index threshold, it is determined that the target user has vascular endothelial dysfunction. 2. The method according to claim 1, characterized in that the step of obtaining the target user's basic blood oxygen saturation net recovery time comprises: The time for the target user's blood oxygen saturation to recover from the first blood oxygen saturation to the second blood oxygen saturation is recorded as a first duration; the first blood oxygen saturation is used to represent the blood oxygen saturation of the target user when the brachial artery blood flow is blocked for a preset duration, and the second blood oxygen saturation is obtained based on the basic blood oxygen saturation multiplied by a preset coefficient; Recording the time from when the brachial artery blood flow of the target user is blocked to when the pulse is restored as the second duration; A difference operation is performed between the first time length and the second time length to obtain the blood oxygen saturation net recovery time. 3. The method according to claim 1, wherein obtaining the blood perfusion index increase value of the target user comprises: Acquire a basic blood perfusion index and a first blood perfusion index of the target user; the first blood perfusion index is the maximum blood perfusion index of the target user during the process from when the brachial artery blood flow is blocked to when the pulse is restored; The blood perfusion index increase value is determined according to the first blood perfusion index and the basic blood perfusion index. 4. The method according to claim 1, characterized in that when the vascular endothelial dysfunction index is greater than the abnormal index threshold, before determining that the target user has vascular endothelial dysfunction, the method further comprises: Classifying the target user population according to the attributes of the target user population; For different target user groups, determine the abnormal index thresholds corresponding to different target user groups. 5. The method according to claim 1, characterized in that the determining of the vascular endothelial dysfunction index according to the basal blood oxygen saturation, the blood oxygen saturation net recovery time, and the blood perfusion index increase value comprises: According to the formula , calculate the endothelial dysfunction index; in, Represents the endothelial dysfunction index. Indicates the net recovery time of blood oxygen saturation, Indicates the basic blood oxygen saturation, Indicates the increase in blood perfusion index. 6. The method according to claim 1, characterized in that when the age of the target user is greater than or equal to a first preset age, determining the vascular endothelial dysfunction index according to the basal blood oxygen saturation, the blood oxygen saturation net recovery time, and the blood perfusion index increase value comprises: According to the formula , calculate the endothelial dysfunction index; in, Represents the endothelial dysfunction index. Indicates the net recovery time of blood oxygen saturation, Indicates the basic blood oxygen saturation, Indicates the increase in blood perfusion index. 7. The method according to claim 6, characterized in that when the age of the target user is greater than or equal to a second preset age and less than the first preset age, determining the vascular endothelial dysfunction index according to the basal blood oxygen saturation, the blood oxygen saturation net recovery time, and the blood perfusion index increase value comprises: According to the formula , calculate the endothelial dysfunction index; in, Represents the endothelial dysfunction index. Indicates the net recovery time of blood oxygen saturation, Indicates the basic blood oxygen saturation, Indicates the increase in blood perfusion index. 8. A microvascular endothelial function detection device, characterized in that the device comprises: An acquisition module is used to obtain the target user's basic blood oxygen saturation, blood oxygen saturation net recovery time, and blood perfusion index increase value; A calculation module, used for determining a vascular endothelial dysfunction index according to the basic blood oxygen saturation, the blood oxygen saturation net recovery time, and the blood perfusion index increase value; The determination module is used to determine that the target user has endothelial dysfunction when the endothelial dysfunction index is greater than an abnormal index threshold. 9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, wherein the processor implements the microvascular endothelial function detection method according to any one of claims 1 to 7 when executing the computer program. 10. A computer-readable storage medium, characterized in that a computer program is stored thereon, and when the computer program is executed by a processor, the microvascular endothelial function detection method according to any one of claims 1 to 7 is implemented.