JP2016202837A - Vaso-vagal response (vvr) occurrence prediction system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a VVR occurrence prediction system capable of suppressing an occurrence of a vaso-vagal response (VVR).SOLUTION: A VVR occurrence prediction system includes acquisition means 31 for acquiring information, over time, on blood pressure of a blood collection object, setting means 32 for setting a threshold on a variation in blood pressure of the blood collection object between before-blood collection and during-blood collection, and prediction means 33 for predicting that a VVR is to occur based on the comparison between the variation in blood pressure of the blood collection object during blood collection and the threshold.SELECTED DRAWING: Figure 3

Description

  The present invention relates to a vasovagal response (VVR) occurrence prediction system.

  For example, in blood donation for securing blood for blood transfusion, in some rare cases, a sudden drop in blood pressure accompanied by bradycardia may be observed along with discomfort. This is a physiological response called the vasovagal response (VVR). VVR can be the biggest cause of blood collection side effects, and its incidence accounts for about 1% of blood transfusion blood collection persons.

  The severity of VVR includes, for example, various stages ranging from a transient attack accompanied by facial pallor to loss of consciousness or a fall accompanying such loss of consciousness. When VVR develops, it takes time to recover.

  As conventional blood pressure monitoring devices, for example, those using pulse wave transmission time (PWTT) measuring means and those using non-invasive blood pressure (NIBP) measuring means are known. (For example, Patent Document 1).

JP 2011-50438 A

  However, the blood pressure monitoring device described in Patent Document 1 can only monitor changes in blood pressure, and cannot suppress the occurrence of VVR.

  The present invention has been made in view of the above problems, and an object thereof is to provide a VVR occurrence prediction system capable of suppressing the occurrence of VVR.

  As a result of the inventor's extensive research in the face of the above problems, the inventor has obtained the knowledge that the occurrence of VVR is caused by a decrease in venous blood return due to abnormal sympathetic nerve regulation at the time of blood collection. That is, the inventor has found that VVR may occur when the blood pressure at the time of blood collection is reduced to some extent as compared with the blood pressure at rest before blood collection, for example.

  Based on the above-described viewpoints, the present invention provides an acquisition unit that acquires information related to blood pressure of a blood collection subject over time, and a setting that sets a threshold value related to fluctuations in blood pressure of the blood collection subject before and during blood collection. VVR generation comprising: means for predicting a vascular vagus nerve reaction (VVR) to occur based on a comparison between a change in blood pressure of the blood collection subject during blood collection and the threshold value A prediction system is provided (Invention 1).

  According to this invention (Invention 1), since it can be predicted that VVR will occur based on a comparison between the blood pressure fluctuation of the blood collection subject during blood collection and a threshold value, for example, when the occurrence of VVR is predicted Can suppress the occurrence of VVR by taking measures such as promoting venous return by exercise of the lower limbs and abdomen, reducing the blood collection speed, or stopping or stopping blood collection.

  In the said invention (invention 1), the said setting means sets the 1st threshold value regarding the fluctuation | variation of the average blood pressure of the said blood-collection subject before and during blood collection, The said prediction means is the said blood collection during blood collection. Based on the comparison between the fluctuation of the average blood pressure of the subject and the first threshold value, it may be predicted that VVR will occur (Invention 2).

  According to this invention (Invention 2), based on the degree of change in the average blood pressure of the blood collection subject before and during blood collection, for example, venous return is promoted by exercise of the lower limbs or abdomen, or the blood collection speed is increased. The occurrence of VVR can be suppressed by reducing or taking measures such as stopping or stopping blood collection.

  In the said invention (invention 1-2), the said setting means sets the 2nd threshold value regarding the fluctuation | variation of the diastolic blood pressure of the said blood collection subject before blood collection and during blood collection, The said prediction means is collecting blood It may be predicted that VVR will occur based on a comparison between the change in diastolic blood pressure of the blood collection subject and the second threshold (Invention 3).

  According to this invention (Invention 3), based on the degree of change in the diastolic blood pressure of the blood collection subject before and during blood collection, for example, venous return is promoted by exercise of the lower limbs or abdomen, or the blood collection speed The occurrence of VVR can be suppressed by taking measures such as reducing or stopping blood collection.

  In the said invention (invention 1-3), the said setting means sets the 3rd threshold value regarding the fluctuation | variation of the systolic blood pressure of the said blood-collection subject before and during blood collection, The said prediction means is collecting blood It may be predicted that VVR will occur based on a comparison between the change in systolic blood pressure of the blood collection subject and the third threshold (invention 4).

  According to this invention (Invention 4), based on the degree of change in the systolic blood pressure of the blood collection subject before and during blood collection, for example, the venous return is promoted by exercise of the lower limbs or the abdomen, or the blood collection speed The occurrence of VVR can be suppressed by taking measures such as reducing or stopping blood collection.

  In the said invention (invention 1-4), when the said prediction means estimates generation | occurrence | production of VVR, you may provide the presentation means which presents predetermined information (invention 5).

  According to this invention (invention 5), since the predetermined information is presented when the occurrence of VVR is predicted, it is possible to know in advance that VVR can occur. For example, a doctor, a nurse, or the like can be promptly encouraged to take measures such as promoting reflux, reducing the blood collection rate, or stopping or stopping blood collection.

  According to the VVR occurrence prediction system of the present invention, the occurrence of VVR can be suppressed. The VVR occurrence prediction system of the present invention can be suitably used not only for blood collection but also for surgical operations in cardiac surgery, orthopedic surgery, obstetrics and gynecology, for example.

It is a figure which shows roughly the basic composition of the VVR generation | occurrence | production prediction system which concerns on one Embodiment of this invention. It is a block diagram which shows the structure of a prediction apparatus. It is a functional block diagram for demonstrating the function which plays a main role in a VVR generation | occurrence | production prediction system. It is a figure explaining the relationship between the time-dependent change of blood pressure, and generation | occurrence | production prediction of VVR. It is a flowchart which shows an example of a process of the VVR generation | occurrence | production prediction system before blood collection. It is a flowchart which shows an example of a process of the VVR generation | occurrence | production prediction system during blood collection. It is a figure explaining an example of a VVR generation | occurrence | production prediction result at the time of setting average blood pressure as an index. It is a figure explaining an example of a VVR generation | occurrence | production prediction result at the time of using diastolic blood pressure as an index. It is a figure explaining an example of a VVR generation | occurrence | production prediction result at the time of using systolic blood pressure as a parameter | index.

  Hereinafter, a VVR occurrence prediction system according to an embodiment of the present invention will be described in detail with reference to the accompanying drawings. However, this embodiment is an exemplification, and the present invention is not limited to this.

(1) Basic Configuration of VVR Occurrence Prediction System FIG. 1 is a diagram schematically showing the basic configuration of a VVR occurrence prediction system according to an embodiment of the present invention. As shown in FIG. 1, the VVR occurrence prediction system according to the present embodiment includes a sphygmomanometer 10 and a prediction device 20 that predicts the occurrence of VVR based on the blood pressure measured by the sphygmomanometer 10. The sphygmomanometer 10 is a wireless LAN (for example, Wi-Fi (registered trademark)), Bluetooth (registered trademark), USB (Universal Serial Bus), IEEE (The Institute of Electrical and Electronics Engineers, Inc.) 1394 or the like. Using a wired communication method, the prediction device 20 is communicably connected.

  The sphygmomanometer 10 is a device that continuously or intermittently measures the blood pressure of a blood collection subject before and during blood collection. The sphygmomanometer 10 may be a well-known one, for example, an auscultation method (Korotkoff sound method), an oscillometric method, a pressure pulse wave method, a pulse wave velocity method, or a non-invasive method using these methods. The sphygmomanometer may be used. In addition, the blood pressure monitor 10 may be one that can be used while wearing, such as a wristband type, an armband type, or a finger type. Furthermore, the sphygmomanometer 10 may be configured to be able to transmit information related to the measured blood pressure and information indicating that blood collection has started (for example, bit data of a predetermined length) to the prediction device 20.

  In the present embodiment, the sphygmomanometer 10 continuously or intermittently measures the fingertip blood pressure of the blood collection subject using the pressure pulse method, and converts the blood pressure waveform data of the upper arm converted from the measured fingertip blood pressure ( Information on blood pressure) is transmitted to the prediction device 20 continuously or intermittently. In addition, the method currently employ | adopted, for example with the blood pressure meter currently marketed etc. may be used for the method of converting fingertip blood pressure into the blood pressure of the upper arm.

(2) Configuration of Prediction Device The prediction device 20 will be described with reference to FIG. FIG. 2 is a block diagram illustrating an internal configuration of the prediction device 20. As shown in FIG. 2, the prediction device 20 includes a CPU (Central Processing Unit) 21, a ROM (Read Only Memory) 22, a RAM (Random Access Memory) 23, an HDD (Hard Disk Drive) 24, and display processing. A unit 25, a display unit 26, an input unit 27, and a communication interface unit 28 are provided, and a bus 29 for transmitting a control signal or a data signal between the units is provided. The prediction device 20 may be a general-purpose personal computer, for example.

  When the power is turned on to the prediction device 20, the CPU 21 loads various programs stored in the ROM 22 or the HDD 24 onto the RAM 23 and executes them. In the present embodiment, the CPU 21 reads out and executes a program stored in the ROM 22 or the HDD 24, thereby performing functions of an acquisition unit 31, a setting unit 32, a prediction unit 33, and a presentation unit 34 (shown in FIG. 3) described later. Realize.

  The HDD 24 is a non-volatile storage device, and stores an operating system (OS) and a program executed on the OS. The HDD 24 may store blood pressure data acquired from the sphygmomanometer 10.

  The display processing unit 25 displays the display data given from the CPU 21 on the display unit 26. The display unit 26 is, for example, an LCD (Liquid Cristal Display) monitor including thin film transistors arranged in units of pixels in a matrix, and drives the thin film transistors based on the display data to display the displayed data on the display screen. indicate.

  The input unit 27 is an information input device such as a mouse or a keyboard. Here, information indicating that blood collection has started may be input using the input unit 27. The communication interface unit 28 includes an interface circuit for communicating with the sphygmomanometer 10.

(3) Overview of Functions in VVR Occurrence Prediction System Functions realized in the VVR occurrence prediction system of this embodiment will be described with reference to FIG. FIG. 3 is a functional block diagram for explaining functions that play a major role in the VVR occurrence prediction system of the present embodiment. In the functional block diagram of FIG. 3, the acquisition unit 31, the setting unit 32, and the prediction unit 33 correspond to the main configuration of the present invention. The presenting means 34 is not an essential component, but is a component for making the present invention more preferable.

  The acquisition means 31 has a function of acquiring information related to blood pressure of a blood collection subject over time. The function of the acquisition means 31 is implement | achieved as follows, for example.

  For example, when the sphygmomanometer 10 starts measuring the blood pressure of the blood collection subject, the CPU 21 of the prediction device 20 transmits blood pressure waveform data (information related to blood pressure) transmitted from the sphygmomanometer 10 continuously or intermittently to the communication interface unit. Receive (acquire) via 29. Further, the CPU 21 stores the received blood pressure waveform data in the RAM 23, for example.

  The setting means 32 has a function of setting a threshold value related to fluctuations in blood pressure of a blood collection subject before and during blood collection. Here, the setting means 32 may have a function of setting a first threshold value relating to a change in the average blood pressure of the blood collection target person before and during blood collection.

  The function of the setting means 32 is implement | achieved as follows, for example. Here, an example will be described in which a threshold value related to the fluctuation rate of the average blood pressure of a blood collection target person between before and during blood collection is set. First, the CPU 21 of the prediction device 20 calculates the average blood pressure of the blood collection subject before blood collection every beat using the blood pressure waveform data of the blood collection subject before blood collection. Here, the average blood pressure for each beat may be calculated by a method using an average value of pressure pulse waves, or may be calculated by a method using diastolic blood pressure and systolic blood pressure.

式（１）中、Ｔ_ｘは一拍毎の間隔であり、ＦＰ（ｘ，ｉ）は圧脈波であり、ｘは１以上Ｎ（Ｎ：血圧計測期間における総脈拍数）以下の整数である。 When the average blood pressure for each beat is calculated by the method using the average value of the pressure pulse wave, the average blood pressure MP1 _{(x) for} each beat can be calculated using the following equation (1).

In the formula (1), T _x is an interval for each beat, FP (x, i) is a pressure pulse wave, and x is an integer of 1 or more and N (N: total pulse rate in blood pressure measurement period) or less. is there.

式（２）中、ＨＰ（ｘ）は収縮期血圧であり、ＬＰ（ｘ）は拡張期血圧である。 In addition, when the average blood pressure for each beat is calculated by the method using the diastolic blood pressure and the systolic blood pressure, the average blood pressure MP2 _{(x) for} each beat can be calculated using the following equation (2). .

In equation (2), HP (x) is systolic blood pressure and LP (x) is diastolic blood pressure.

When the CPU 21 receives information indicating that blood collection has started from the sphygmomanometer 10 or when the information is input using the input unit 27, the average blood pressure of a predetermined number of pulses in the blood pressure measurement period before blood collection ( That is, the average value of MP1 _(x) or MP2 _(x ) is calculated. Here, the predetermined number may be, for example, a total pulse rate in a blood pressure measurement period before blood collection, or an arbitrary pulse rate (for example, 120). Then, the CPU 21 sets a predetermined ratio (variation rate) relating to the calculated average blood pressure as a threshold (first threshold), and stores the set threshold in, for example, the RAM 23. The predetermined ratio can be arbitrarily set within a range of 0% to 100%, for example.

  The predicting means 33 has a function of predicting that a vascular vagus nerve reaction (VVR) will occur based on a comparison between a change in blood pressure of a blood collection subject during blood collection and the threshold value. Here, the predicting means 33 may have a function of predicting that VVR will occur based on a comparison between the fluctuation of the average blood pressure of the blood collection subject during blood collection and the first threshold value. In this case, based on the degree of change in the average blood pressure of the subject before and during blood collection, for example, venous return is promoted by exercise of the lower limbs or abdomen, blood collection speed is reduced, or blood collection is performed. The occurrence of VVR can be suppressed by taking measures such as stopping or stopping.

  Here, with reference to FIG. 4, the relationship between the temporal change in blood pressure (average blood pressure per beat in the example of FIG. 4) of the VVR onset person (the person who has experienced onset of VVR) and the occurrence prediction of VVR is shown. explain. As shown in FIG. 4, the average blood pressure for each beat changes with time before and after the blood collection start timing (time t0 in the example of FIG. 4). The average blood pressure for each beat of a VVR-onset person gradually decreases from the start timing of blood collection, and the fluctuation rate of the average blood pressure during blood collection with respect to the reference blood pressure (average blood pressure before blood collection (indicated by a dotted line in FIG. 4)) at time t1. Is equal to or less than the blood pressure). Then, VVR occurs at time t2 after time t1.

  The function of the prediction means 33 is implement | achieved as follows, for example. Here, a case will be described as an example in which the predicting unit 33 predicts that VVR will occur when the fluctuation rate of the average blood pressure becomes greater than or equal to the threshold during blood collection. The CPU 21 of the prediction device 20 receives information indicating that blood collection has started from the sphygmomanometer 10 or, after the information is input using the input unit 27, for one beat based on the function of the acquisition unit 31. Each time the blood pressure waveform data is received from the sphygmomanometer 10 continuously or intermittently, the average blood pressure of the blood collection subject during blood collection is calculated for each beat. Here, the average blood pressure for each beat may be calculated using the method described above.

  Next, when the CPU 21 calculates the average blood pressure for each beat of the blood collection subject during blood collection, the CPU 21 compares the fluctuation rate of the average blood pressure between the average blood pressure before blood collection and the calculated average blood pressure with a threshold value. . And CPU21 discriminate | determines (predicts) that VVR will generate | occur | produce, when the fluctuation rate of average blood pressure becomes more than a threshold value (1st threshold value).

  The presentation unit 34 has a function of presenting predetermined information when the prediction unit 33 predicts the occurrence of VVR. In this case, since predetermined information is presented when the occurrence of VVR is predicted, it can be known in advance that VVR can occur. For example, venous return is promoted by exercise of the lower limbs or abdomen, blood sampling For example, it is possible to promptly prompt a doctor, a nurse, or the like to take measures such as reducing the speed or stopping or stopping blood collection.

  The function of the presentation means 34 is implement | achieved as follows, for example. When predicting the occurrence of VVR based on the function of the prediction means 33, the CPU 21 of the prediction device 20 displays the message to display on the display unit 26, for example, a message for notifying that the VVR is generated. To the unit 25.

  Further, when the CPU 21 predicts the occurrence of VVR based on the function of the predicting means 33, for example, audio data for notifying that VVR is generated is output from an audio output unit (not shown) such as a buzzer or a speaker. You may let them.

(4) Flow of main processing of the VVR occurrence prediction system of the present embodiment Next, an example of the flow of main processing performed by the VVR occurrence prediction system of the present embodiment will be described with reference to the flowcharts of FIGS. I will explain.

  First, an example of processing of the VVR occurrence prediction system before blood collection will be described with reference to FIG. For example, when the sphygmomanometer 10 starts measuring the blood pressure of the blood collection subject, the CPU 21 of the prediction device 20 transmits blood pressure waveform data (information related to blood pressure) transmitted from the sphygmomanometer 10 continuously or intermittently to the communication interface unit. 29 (step S100). Further, the CPU 21 stores the received blood pressure waveform data in the RAM 23, for example.

  Next, the CPU 21 sets a threshold value related to fluctuations in the blood pressure of the blood collection subject before and during blood collection (step S102). Specifically, the CPU 21 first calculates the average blood pressure of the blood collection subject before blood collection for each beat using the blood pressure waveform data of the blood collection subject before blood collection. Then, when the CPU 21 receives information indicating that blood collection has started from the sphygmomanometer 10 or when the information is input using the input unit 27, the average of a predetermined number of pulses in the blood pressure measurement period before blood collection. Blood pressure is calculated. Further, the CPU 21 sets a predetermined ratio (variation rate) relating to the calculated average blood pressure as a threshold value, and stores the set threshold value in, for example, the RAM 23.

  Next, an example of processing of the VVR occurrence prediction system during blood collection will be described with reference to FIG. The CPU 21 of the prediction device 20 receives information indicating that blood collection has started from the sphygmomanometer 10, or after the information is input using the input unit 27, the blood pressure waveform data for one beat is converted into the sphygmomanometer 10. Is received (step S110), the average blood pressure for each beat of the blood collection subject during blood collection is calculated. And CPU21 will compare the fluctuation rate of the average blood pressure between the average blood pressure before blood collection and the calculated average blood pressure, and a threshold, if the average blood pressure for every beat of the blood collection subject who is collecting blood is calculated, When the fluctuation rate of the average blood pressure is equal to or higher than the threshold (step S112: YES), it is determined (predicted) that VVR occurs. In addition, CPU21 transfers to the process of step S110, when the fluctuation rate of average blood pressure is less than a threshold value (step S112: NO).

  Next, when predicting the occurrence of VVR, the CPU 21 presents predetermined information (step S114). Specifically, the CPU 21 transmits the message to the display processing unit 25 in order to display, for example, a message for notifying that the VVR is generated on the display unit 26.

  As described above, according to the VVR occurrence prediction system of the present embodiment, it can be predicted that a VVR will occur based on a comparison between a blood pressure change of a blood collection subject during blood collection and a threshold value. If the occurrence of blood loss is predicted, the VVR is suppressed by taking measures such as promoting venous return by lower limb or abdominal exercise, reducing blood collection speed, or stopping or stopping blood collection. be able to.

  The embodiment described above is described for facilitating understanding of the present invention, and is not described for limiting the present invention. Therefore, each element disclosed in each of the embodiments is intended to include all design changes and equivalents belonging to the technical scope of the present invention.

Hereinafter, modifications of the above-described embodiment will be described.
(Modification 1)
In the above-described embodiment, the case where the occurrence of VVR is predicted using the average blood pressure of the blood collection subject as an index has been described as an example.

  In this case, the setting means 32 in the present modification may set a second threshold value related to a change in the diastolic blood pressure of the blood collection target person before and during blood collection. Further, the predicting means 33 in the present modification may predict that a VVR will occur based on a comparison between the variation of the diastolic blood pressure of the blood collection subject who is collecting blood and the second threshold value. According to the VVR occurrence prediction system according to this modification, based on the degree of change in the diastolic blood pressure of the blood collection subject before and during blood collection, for example, venous return is promoted by exercise of the lower limbs or abdomen, The occurrence of VVR can be suppressed by reducing the blood collection rate or taking measures such as stopping or stopping blood collection.

  The function of the setting means 32 in this modification is implement | achieved as follows, for example. Here, an example will be described in which a threshold value related to the variation rate of the diastolic blood pressure of a blood collection target person between before and during blood collection is set. First, the CPU 21 of the prediction device 20 obtains the minimum blood pressure (diastolic blood pressure) for each beat of the blood collection subject before blood collection using the blood pressure waveform data of the blood collection subject before blood collection. And CPU21 sets the predetermined ratio (variation rate) regarding the lowest diastolic blood pressure among the diastolic blood pressure for every beat as a threshold value (2nd threshold value), and memorize | stores the set threshold value in RAM23, for example.

  Moreover, the function of the prediction means 33 in this modification is implement | achieved as follows, for example. Here, a case will be described as an example in which the predicting unit 33 predicts that VVR will occur when the rate of change in diastolic blood pressure becomes greater than or equal to a threshold during blood collection. The CPU 21 of the prediction device 20 receives, for example, information indicating that blood collection has started from the sphygmomanometer 10, or after the information is input using the input unit 27, the CPU 21 of the prediction device 20 determines whether the information has been acquired. Each time the blood pressure waveform data for the beat is received from the sphygmomanometer 10, the diastolic blood pressure for each beat of the blood collection subject who is collecting blood is obtained. Next, the CPU 21 compares the fluctuation rate of the diastolic blood pressure between the diastolic blood pressure before blood collection and the diastolic blood pressure for each beat with a threshold value (second threshold value), and the fluctuation rate of the diastolic blood pressure. Is determined (predicted) when VVR occurs.

  Thus, according to the VVR occurrence prediction system according to the present modification, it is possible to exhibit the same operational effects as those of the above-described embodiment.

(Modification 2)
In the above embodiment, the case where the occurrence of VVR is predicted using the average blood pressure of the blood collection subject as an index has been described as an example, but the occurrence of VVR may be predicted using the systolic blood pressure of the blood collection subject as an index.

  In this case, the setting means 32 in the present modification may set a third threshold value regarding the fluctuation of the systolic blood pressure of the blood collection subject before and during blood collection. Further, the predicting means 33 in the present modification may predict that a VVR will occur based on a comparison between the variation of the systolic blood pressure of the blood collection subject during blood collection and the third threshold value. According to the VVR occurrence prediction system according to this modification, based on the degree of change in the systolic blood pressure of the blood collection subject before and during blood collection, for example, venous return is promoted by exercise of the lower limbs or abdomen, The occurrence of VVR can be suppressed by reducing the blood collection rate or taking measures such as stopping or stopping blood collection.

  The function of the setting means 32 in this modification is implement | achieved as follows, for example. Here, an example will be described in which a threshold value regarding the rate of change in systolic blood pressure of a blood collection subject between blood collection before and during blood collection is set. First, the CPU 21 of the prediction device 20 obtains the maximum blood pressure (systolic blood pressure) for each beat of the blood collection subject before blood collection using the blood pressure waveform data of the blood collection subject before blood collection. And CPU21 sets the predetermined ratio (variation rate) regarding the highest systolic blood pressure among the systolic blood pressure for every beat as a threshold value (3rd threshold value), and memorize | stores the set threshold value in RAM23, for example.

  Moreover, the function of the prediction means 33 in this modification is implement | achieved as follows, for example. Here, a case will be described as an example where the predicting means 33 predicts that VVR will occur when the rate of change in systolic blood pressure becomes greater than or equal to a threshold during blood collection. The CPU 21 of the prediction device 20 receives information indicating that blood collection has started from the sphygmomanometer 10 or, after the information is input using the input unit 27, for one beat based on the function of the acquisition unit 31. Each time the blood pressure waveform data is received from the sphygmomanometer 10, the systolic blood pressure is obtained for each beat of the blood collection subject who is collecting blood. Next, the CPU 21 compares the variation rate of the systolic blood pressure between the systolic blood pressure before blood collection and the systolic blood pressure for each beat with a threshold value (third threshold value), and the variation rate of the systolic blood pressure. Is determined (predicted) when VVR occurs.

  Thus, according to the VVR occurrence prediction system according to the present modification, it is possible to exhibit the same operational effects as those of the above-described embodiment.

(Other)
In the above embodiment, the case where the blood pressure monitor 10 and the prediction device 20 are provided separately has been described as an example, but the present invention is not limited to this case. For example, the prediction apparatus 20 may be configured to be integrated into the sphygmomanometer 10.

  In the above-described embodiment, the case where the occurrence of VVR is predicted using the average blood pressure of the blood collection target as an index has been described as an example. For example, three indexes of average blood pressure, diastolic blood pressure, and systolic blood pressure are used. Thus, the occurrence of VVR may be predicted. In this case, VVR may be predicted to occur when the occurrence of VVR is predicted for all three indicators of mean blood pressure, diastolic blood pressure, and systolic blood pressure, and VVR may be predicted for at least one of the three indicators. When the occurrence of VVR is predicted, it may be predicted that VVR will occur.

  Moreover, in the said embodiment, the setting means 32 sets the threshold value regarding the fluctuation rate of the blood pressure of the blood collection subject before and during blood collection, and the prediction means 33 changes the blood pressure of the blood collection subject during blood collection. The case where the VVR is predicted to occur when the rate is equal to or higher than the threshold has been described as an example, but the present invention is not limited to this case.

  For example, the setting unit 32 sets a predetermined ratio of the blood pressure of the blood collection subject before blood collection as a threshold (for example, the reference blood pressure in the above embodiment), and the prediction unit 33 determines that the blood pressure of the blood collection subject during blood collection is It may be predicted that a VVR will occur when the threshold value is reached. Even in this case, it is possible to exhibit the same effect as the above-described embodiment.

  The setting means 32 sets a predetermined ratio (for example, 70%) of the average blood pressure of the blood collection subject before blood collection as the first threshold, and the prediction means 33 sets the average blood pressure of the blood collection subject during blood collection to the first blood pressure. It may be predicted that a VVR will occur when the threshold value is reached.

  Furthermore, the setting means 32 sets a predetermined ratio (for example, 75%) of the diastolic blood pressure of the blood collection subject before blood collection as the second threshold, and the prediction means 33 determines whether the diastolic blood pressure of the blood collection subject during blood collection is It may be predicted that VVR will occur when the second threshold value is reached.

  Furthermore, the setting means 32 sets a predetermined ratio (for example, 70%) of the systolic blood pressure of the blood collection subject before blood collection as a third threshold, and the prediction means 33 sets the systolic blood pressure of the blood collection subject during blood collection. It may be predicted that VVR will occur when the value becomes equal to or smaller than the third threshold.

  The program for realizing the VVR occurrence prediction system of the present invention with a computer may be stored in a computer-readable storage medium. The storage medium storing this program may be the HDD 24 shown in FIG. Further, it may be a CD-ROM that can be read by being inserted into a program reading device such as a CD-ROM drive. Further, the storage medium may be a magnetic tape, a cassette tape, a flexible disk, an MO / MD / DVD, or a semiconductor memory.

  EXAMPLES Hereinafter, although an Example etc. demonstrate this invention further more concretely, the scope of the present invention is not limited to these Examples etc.

(1) Selection of Blood Collection Targets Among blood donation applicants who visited the blood donation room in Morioka-Odori from Iwate Red Cross Blood Center between December 2012 and July 2014, young people who obtained written consent (16-29 A total of 46 blood donors (6 people who developed VVR, 40 people who did not develop VVR) were selected as blood collection subjects.

(2) Blood pressure measurement method After the blood collection subject who passed the pre-collection test is rested in a semi-sitting position on the blood collection bed, the forearm center is disinfected and the midline vein is punctured with a 17-gauge needle. A vein was secured and 200 ml or 400 ml blood was collected at a rate of about 50 cc per minute for 5-10 minutes. Then, after withdrawal of the needle, the blood collection subject was allowed to rest for about 5 minutes. During a period of about 10 to 15 minutes from the rest period before blood collection to 5 minutes after blood collection, a measurement cuff is wrapped around the second middle joint of the arm opposite to the blood collecting arm, The blood pressure was continuously measured and the measurement result was recorded. For this blood pressure measurement, Finometer Model-2 (Finapres Medical Systems; FMS, Netherlands) was used.

(3) Test example 1
A VVR occurrence prediction test was performed using the average blood pressure obtained by analyzing the measurement results using analysis software BeatScope Easy (FMS, Netherlands) as an index. Here, a threshold value is set by changing the fluctuation rate of the average blood pressure during blood sampling from 0% to 100% with respect to the average blood pressure before blood sampling, and the VVR detection rate (VVR onset person generates VVR for each threshold). The probability of detecting this), the misdiagnosis rate (the probability of erroneous detection when a non-symptomatic person generates VVR), and the time until the occurrence of VVR (from when the occurrence of VVR is detected to when the VVR actually occurs) Time). Note that the time until the occurrence of VVR is an average time between VVR onset persons.

  FIG. 7 shows the test results of Test Example 1. As shown in FIG. 7, when the fluctuation rate was 30% or less as a threshold value, the VVR detection rate was 100%. Further, when the fluctuation rate of 30% was used as a threshold, the misdiagnosis rate was 0%, and a good result was obtained. Furthermore, it has been found that the smaller the fluctuation rate, the longer the time until the occurrence of VVR (that is, the occurrence of VVR can be detected at an early stage).

(4) Test example 2
A VVR occurrence prediction test was performed using the diastolic blood pressure obtained by analyzing the measurement results using the analysis software BeatScope Easy as an index. Here, the threshold value is set by changing the fluctuation rate of the diastolic blood pressure during blood collection to 0% to 100% with respect to the diastolic blood pressure before blood collection, and for each threshold value, the VVR detection rate, the misdiagnosis rate, The time until the occurrence of VVR was determined.

  FIG. 8 shows the test results of Test Example 2. As shown in FIG. 8, when the fluctuation rate is 25% or less as a threshold value, the VVR detection rate was 100%. On the other hand, when the variation rate was 25%, the misdiagnosis rate was 12.5%. Further, as in Test Example 1, it was found that the time until the occurrence of VVR becomes longer as the variation rate becomes smaller.

(5) Test example 3
A VVR occurrence prediction test was performed using the systolic blood pressure obtained by analyzing the measurement results using the analysis software BeatScope Easy as an index. Here, the threshold value is set by changing the fluctuation rate of the systolic blood pressure during blood collection to 0% to 100% with respect to the systolic blood pressure before blood collection, and for each threshold value, the VVR detection rate, the misdiagnosis rate, The time until the occurrence of VVR was determined.

  FIG. 9 shows the test results of Test Example 3. As shown in FIG. 9, when the fluctuation rate was 30% or less as the threshold value, the VVR detection rate was 100%. On the other hand, the misdiagnosis rate was 2.5% when the variation rate was 30% as a threshold. Furthermore, as in Test Example 1 and Test Example 2, it was found that the time until the VVR was generated became longer as the variation rate was smaller.

  As can be seen from the results of Test Examples 1 to 3, it is possible to detect the occurrence of VVR in advance by predicting that VVR will occur when the fluctuation rate of the blood pressure of the blood collection subject during blood collection exceeds a threshold value. And, in turn, the occurrence of VVR can be suppressed.

  According to the VVR occurrence prediction system of the present invention as described above, it is possible to suppress the occurrence of VVR, which is suitable not only for blood collection but also for surgery in cardiac surgery, orthopedics, gynecology, etc. Since it can be used, its industrial applicability is extremely large.

31 ... Acquisition means 32 ... Setting means 33 ... Prediction means 34 ... Presentation means

Claims (5)

Acquisition means for acquiring information on blood pressure of a blood collection subject over time;
A setting means for setting a threshold value related to a change in blood pressure of the blood collection subject before and during blood collection;
A VVR occurrence prediction system comprising: prediction means for predicting that a vascular vagus nerve reaction (VVR) occurs based on a comparison between a change in blood pressure of the blood collection subject during blood collection and the threshold value. The setting means sets a first threshold value relating to a change in the average blood pressure of the blood collection subject before and during blood collection,
2. The VVR occurrence prediction system according to claim 1, wherein the predicting unit predicts that a VVR is generated based on a comparison between a change in average blood pressure of the blood collection subject during blood collection and the first threshold value. 3. The setting means sets a second threshold value related to a change in the diastolic blood pressure of the blood collection subject before and during blood collection,
3. The VVR occurrence prediction system according to claim 1, wherein the predicting unit predicts that a VVR is generated based on a comparison between a change in diastolic blood pressure of the blood collection subject during blood collection and the second threshold value. 4. The setting means sets a third threshold value related to fluctuations in the systolic blood pressure of the blood collection subject before and during blood collection,
4. The predictor according to claim 1, wherein the predicting unit predicts that VVR is generated based on a comparison between a change in systolic blood pressure of the blood collection subject during blood collection and the third threshold value. 5. VVR occurrence prediction system.   The VVR occurrence prediction system according to claim 1, further comprising a presentation unit that presents predetermined information when the prediction unit predicts the occurrence of VVR.

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