Processing unit, computer program, and monitoring system

Abstract

This makes it possible to understand the relationship between blood oxygen saturation and arterial oxygen partial pressure for each individual. [Solution] The input interface 111 receives first data D1 corresponding to the measured values ​​of arterial blood oxygen partial pressure and arterial blood oxygen saturation of the subject 20, and at least one of second data D2 corresponding to at least one of the subject 20's arterial blood carbon dioxide partial pressure, arterial blood pH, body temperature, and 2,3-DPG concentration in the blood. The processor 112 determines a rule for converting the values ​​of arterial blood oxygen partial pressure and arterial blood oxygen saturation of the subject 20 to each other based on at least one of the first data D1 and second data D2, and visualizes the rule on the visualization device 12.

Description

[Technical Field]

[0001] This disclosure relates to a processing device for monitoring arterial blood oxygen partial pressure, an indicator of a subject's respiratory function. This disclosure also relates to a computer program executable by a processor mounted on the processing device. This disclosure also relates to a monitoring system including the processing device and a visualization device. [Background technology]

[0002] For example, in acute care, managing the respiratory function of the patient is a crucial element. The P / F ratio is a well-known representative indicator of the oxygenation capacity of patients with respiratory failure. The P / F ratio is calculated by dividing the arterial oxygen partial pressure (PaO2) by the inspired oxygen concentration (FiO2). Patent Document 1 discloses a system that also monitors arterial oxygen partial pressure in order to optimize mechanical ventilation. [Prior art documents] [Patent Documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2017-538553 [Overview of the project] [Problems that the invention aims to solve]

[0004] There is a need to be able to understand the relationship between blood oxygen saturation and arterial oxygen partial pressure for each individual. [Means for solving the problem]

[0005] One example of an embodiment that may be provided by this disclosure is an apparatus, An interface that accepts at least one of the following: first data corresponding to the measured arterial blood oxygen partial pressure and arterial blood oxygen saturation of the subject, and second data corresponding to at least one of the following values: arterial blood carbon dioxide partial pressure, arterial blood pH, body temperature, and 2,3-DPG concentration in the blood of the subject; A processor that determines a rule for mutually converting the arterial blood oxygen partial pressure value and arterial blood oxygen saturation value of the subject based on at least one of the first data and the second data, and causes the rule to be visualized on a visualization device, It is equipped with.

[0006] One possible embodiment of what this disclosure may provide is a computer program executable by a processor mounted on a processing unit, By being executed, the processing device will The system accepts at least one of the following: first data corresponding to the measured arterial blood oxygen partial pressure and arterial blood oxygen saturation of the subject, and second data corresponding to at least one of the following values: arterial blood carbon dioxide partial pressure, arterial blood pH, body temperature, and 2,3-DPG concentration in the blood of the subject. Based on at least one of the first data and the second data, a rule is determined to convert between the arterial blood oxygen partial pressure value and the arterial blood oxygen saturation value of the subject. The aforementioned rules are made visible using a visualization device.

[0007] One example of what this disclosure may provide is a monitoring system, Processing device and Visualization device, It includes, The aforementioned processing apparatus is An interface that accepts at least one of the following: first data corresponding to the measured arterial blood oxygen partial pressure and arterial blood oxygen saturation of the subject, and second data corresponding to at least one of the following values: arterial blood carbon dioxide partial pressure, arterial blood pH, body temperature, and 2,3-DPG concentration in the blood of the subject; A processor that determines a rule for mutually converting the arterial blood oxygen partial pressure value and arterial blood oxygen saturation value of the subject based on at least one of the first data and the second data, and visualizes the rule on the visualization device, It is equipped with.

[0008] Measuring PaO2 requires arterial blood sampling, making it impossible to continuously monitor PaO2 and the P / F ratio. On the other hand, arterial oxygen saturation (SaO2) can be continuously measured as transcutaneous arterial oxygen saturation (SpO2), and PaO2 and SaO2 values ​​are represented by the oxygen dissociation curve, a function that allows for mutual conversion. As an alternative indicator, the S / F ratio, which replaces the numerator of the P / F ratio with the SpO2 value, is sometimes used, but usually the oxygenation state is assessed by converting the SpO2 value to the PaO2 value. However, the oxygen dissociation curve, which represents this correspondence, is represented by a nonlinear function that is difficult to calculate mentally. Therefore, healthcare professionals actually rely on experience and memorization to perform conversions, such as memorizing the values ​​of representative points on the oxygen dissociation curve and stating that "if SpO2 is 90%, then PaO2 is approximately 60 mmHg." Furthermore, this oxygen dissociation curve is generalized using standard biological parameter values ​​and does not reflect the individual circumstances of each subject.

[0009] According to the configurations described in each of the above examples, a rule is determined for converting between the arterial blood oxygen saturation value and the arterial blood oxygen partial pressure value of a subject based on the measurements obtained from that subject, and the corresponding relationship can be visualized. This allows the user to obtain the correspondence between blood oxygen saturation and arterial blood oxygen partial pressure for each subject without relying on experience or memorization.

[0010] In particular, when a second set of data is accepted, at least one of the factors that shift the oxygen dissociation curve—the subject's arterial carbon dioxide partial pressure, arterial blood pH, body temperature, and 2,3-DPG concentration in the blood—is reflected in the conversion rule, thus suppressing the potential problems that may arise from relying on a generalized correspondence. [Brief explanation of the drawing]

[0011] [Figure 1] This illustrates the functional configuration of a monitoring system according to one embodiment. [Figure 2] This illustrates the oxygen dissociation curve. [Figure 3] This illustrates factors that can cause deviations in the oxygen dissociation curve. [Figure 4] The conversion function and the reference function visualized by the visualization device of FIG. 1 are illustrated. [Figure 5] An example in which the range that the conversion function can take is visualized is shown. [Figure 6] The appearance of the user interface of FIG. 1 is illustrated. [Figure 7] An example in which the calibrated or updated conversion function is visualized is shown. [Figure 8] An example in which an estimated value of PaO2 is visualized based on the measured value of SpO2 is shown. [Figure 9] An example in which the error of the measured value of SpO2 is visualized is shown. [Figure 10] The time series of each of the measured value of SpO2, the estimated value of PaO2, the value of FiO2, and the estimated value of the P / F ratio is illustrated.

Best Mode for Carrying Out the Invention

[0012] Examples of embodiments will be described in detail below while referring to the accompanying drawings.

[0013] FIG. 1 illustrates the functional configuration of a monitoring system 10 according to an embodiment. The monitoring system 10 includes a configuration for monitoring the partial pressure of arterial oxygen (PaO2) of a subject 20. PaO2 is a value indicating the partial pressure of oxygen contained in arterial blood, and is used as an index indicating the oxygenation state of blood in the lungs as a respiratory function.

[0014] FIG. 2 illustrates the relationship between PaO2 and the measured arterial oxygen saturation (SaO2). This characteristic curve is known as the oxygen dissociation curve. SaO2 is a value indicating the ratio of hemoglobin contained in arterial blood that is bound to oxygen. SaO2 can be expressed using a percentage. In this example, it is shown to take values from 0 corresponding to 0% to 1 corresponding to 100%. The oxygen dissociation curve is an example of a rule for mutually converting the value of the partial pressure of arterial oxygen of the subject 20 and the value of the arterial oxygen saturation.

[0015] Furthermore, as shown by the thin solid line in Figure 2, it is known that the entire oxygen dissociation curve shifts to the left or right in response to changes in various biological parameters. Figure 3 illustrates the effect of changes in biological parameters on the shift of the oxygen dissociation curve.

[0016] Examples of biological parameters that can shift the oxygen dissociation curve include the affinity of oxygen to hemoglobin in arterial blood, the partial pressure of carbon dioxide in arterial blood (PaCO2), the pH of arterial blood, body temperature (blood temperature), and the concentration of 2,3-DPG (2,3-Diphosphoglycerate) in the blood. Blood temperature may be estimated based on body temperature measured at other body parts, such as surface temperature or rectal temperature.

[0017] The following equation (Hill's equation) is known as a model that reproduces the oxygen dissociation curve. SaO2 = (PaO2 / P50) n / [ 1 + (PaO2 / P50) n ] …(1) As illustrated in Figure 2, P50 represents the PaO2 value that yields 50% SaO2. A standard value of P50 is known to be 26.8. If the oxygen dissociation curve shifts to the left, P50 decreases, and if the oxygen dissociation curve shifts to the right, P50 increases. In other words, if P50 can be identified as a constant, a transformation function that reflects the state of subject 20 can be determined.

[0018] As illustrated in Figure 1, the monitoring system 10 includes a processing unit 11. An example of a method for determining the conversion function using the processing unit 11 will be described.

[0019] The processing unit 11 is equipped with an input interface 111. The input interface 111 is configured as a hardware interface that receives first data D1 corresponding to the PaO2 and SaO2 measurements of the subject 20. The PaO2 and SaO2 measurements are obtained by subjecting arterial blood collected from the subject 20 to analysis by a blood gas analyzer (not shown). The first data D1 may be transmitted from the blood gas analyzer or manually entered by the user through a user interface (not shown).

[0020] As used herein, the expression "data corresponding to a measurement" includes both cases where the data represents the measurement itself, and cases where the data represents a value obtained by applying a predetermined transformation to the measurement, or an estimated value of the measurement.

[0021] The first data D1 may be in analog or digital data form, depending on the specifications of the input source. If the first data D1 is in analog data form, the input interface 111 includes an appropriate conversion circuit, including an A / D converter. This description also applies to other data that the input interface 111 can accept, as described later.

[0022] The processing unit 11 includes a processor 112. The processor 112 is configured to perform a calculation to determine P50 by substituting the measured values ​​of PaO2 and SaO2 corresponding to the first data D1 received by the input interface 111 into equation (1). This calculation corresponds to the calibration of the oxygen dissociation curve in light of the "affinity between oxygen and hemoglobin" in the arterial blood of the subject 20 exemplified in Figure 3.

[0023] As illustrated in Figure 1, the processing unit 11 includes storage 113. The processor 112 is configured to store data corresponding to the conversion function determined by the above calculation in the storage 113. The storage 113 can be implemented by semiconductor memory, hard disk drive, magnetic tape drive, etc.

[0024] The SaO2 measurement value entered as the first data D1 can be replaced with an SpO2 measurement value. However, it is preferable to obtain the SaO2 measurement value because it is obtained along with PaO2 from a single arterial blood sample and more directly represents the oxygen saturation of arterial blood.

[0025] The input interface 111 of the processing unit 11 is configured as a hardware interface that can also accept second data D2 corresponding to at least one measurement value of the subject 20's PaCO2, arterial blood pH, body temperature, and 2,3-DPG concentration in the blood. The second data D2 may be accepted in addition to the first data D1, or it may be accepted in place of the first data D1.

[0026] PaCO2 and pH measurements are obtained by analyzing arterial blood collected from subject 20 using a blood gas analyzer (not shown). In this case, the second data D2 may be transmitted from the blood gas analyzer or manually entered by the user through a user interface (not shown).

[0027] Body temperature can be obtained through a temperature sensor (not shown) attached to the subject 20. Second data D2 may be transmitted from the temperature sensor or manually entered by the user through a user interface (not shown). Note that body temperature does not necessarily have to be a measured value. 37°C, known as the standard blood temperature Ts, may be used as the body temperature value.

[0028] 2,3-DPG concentration is obtained by measuring blood collected from the subject using a measurement kit (not shown) that employs, for example, ultraviolet absorbance spectroscopy. In this case, the second data D2 may be transmitted from the blood gas analyzer or manually entered by the user through a user interface (not shown). Note that the 2,3-DPG concentration does not necessarily have to be a measured value. The standard value Ds for 2,3-DPG concentration is known to be 4.65 × 10⁻⁶. -3The mole may be used as the value of the 2,3-DPG concentration.

[0029] The specification of P50 in Equation (1) based on the second data D2 can be made using the following equation. P50 = [ P50s ( P50c / P50s ) ( P50p / P50s ) ] (P50t / P50s ) ( P50d / P50s ) …(2) P50c = P50s + 1.273 x 10 -1 ( Pc - Pcs ) + 1.083 x 10 -4 ( Pc - Pcs ) 2 …(3) P50p = P50s - 25.535 ( ph - phs ) + 10.646 ( ph - phs ) 2 - 1.764 ( ph - phs ) 3 …(4) P50t = P50s + 1.435 ( T - Ts ) + 4.163 x 10 -2 ( T - Ts ) 2 + 6.86 x 10 -4 [[ID=​​​​​​​​​​​​​​​​​​​​​​​​​​​​Ds: Standard value of 2,3-DPG concentration (4.65 × 10⁻⁶) -3 Mol) That is the case.

[0030] Note that the coefficient values ​​in the above equations, and the specific standard values ​​shown for some biological parameters, are merely examples. For biological parameters not referenced, the standard values ​​for those parameters are substituted as the measured values ​​in each equation.

[0031] As described above, P50 is identified, and a conversion function is determined in consideration of various biological parameters. The processor 112 can store the data corresponding to the determined conversion function in the storage 113.

[0032] When both the first data D1 and the second data D2 are received by the input interface 111, the value of P50 used to determine the conversion function can be calculated by the following formula. P50 = k1 P50d1 + k2 P50d2 …(7) k1 + k2 = 1 …(8) Here P50d1: The value of P50 identified using the first data point D1. P50d2: The value of P50 identified using the second data point, D2. k1 and k2 are coefficients representing the contribution of each term to the ultimately identified P50, and can be determined by the user as appropriate. k1 and k2 are positive real numbers.

[0033] The monitoring system 10 includes a visualization device 12. The visualization device 12 is configured to make the transformation function determined as described above visible to the user. Examples of the visualization device 12 include a device for displaying images, a device for projecting images, and a device for printing images. The processing unit 11 may be a device independent of the visualization device 12, or it may be part of the visualization device 12. If the processing unit 11 and the visualization device 12 are independent devices, the visualization device 12 may be located or installed at a distance from the processing unit 11.

[0034] The processing unit 11 is equipped with an output interface 114. The processor 112 is configured to output control data CT from the output interface 114, which causes the determined transformation function to be visualized by the visualization device 12.

[0035] The output interface 114 is configured as a hardware interface. The control data CT may be in analog data form or digital data form, depending on the specifications of the visualization device 12. When the control data CT is in analog data form, the output interface 114 includes an appropriate conversion circuit, including a D / A converter. This description also applies to other data that the output interface 114 can output, as described later.

[0036] Figure 4 illustrates the conversion function F1 visualized by the visualization device 12. The dashed line represents the reference function F0. The reference function F0 corresponds to the conversion function when P50 is the standard value. In other words, the reference function F0 is a function that converts the arterial oxygen saturation value to the standard estimate of arterial oxygen partial pressure when arterial carbon dioxide partial pressure, arterial pH, body temperature, and 2,3-DPG concentration in the blood are all at standard values.

[0037] Measuring PaO2 requires arterial blood sampling, making it impossible to continuously monitor PaO2 and the P / F ratio. On the other hand, arterial oxygen saturation (SaO2) can be continuously measured as transcutaneous arterial oxygen saturation (SpO2), and PaO2 and SaO2 values ​​are represented by the oxygen dissociation curve, a function that allows for mutual conversion. As an alternative indicator, the S / F ratio, which replaces the numerator of the P / F ratio with the SpO2 value, is sometimes used, but usually the oxygenation state is assessed by converting the SpO2 value to the PaO2 value. However, the oxygen dissociation curve, which represents this correspondence, is represented by a nonlinear function that is difficult to calculate mentally. Therefore, healthcare professionals actually rely on experience and memorization to perform conversions, such as memorizing the values ​​of representative points on the oxygen dissociation curve and stating that "if SpO2 is 90%, then PaO2 is approximately 60 mmHg." In addition, this oxygen dissociation curve is a generalized representation corresponding to the above-mentioned reference function and does not reflect the individual circumstances of each subject.

[0038] According to the configuration of this embodiment, a rule is determined for converting between the arterial blood oxygen saturation value and the arterial blood oxygen partial pressure value of a subject based on the measurement values ​​obtained from that subject, and the corresponding relationship can be visualized. As a result, the user can obtain the correspondence between blood oxygen saturation and arterial blood oxygen partial pressure for each subject without relying on experience or memorization.

[0039] In particular, when a second set of data is accepted, at least one of the factors that shift the oxygen dissociation curve—the subject's arterial carbon dioxide partial pressure, arterial blood pH, body temperature, and 2,3-DPG concentration in the blood—is reflected in the conversion rule, thus suppressing the potential problems that may arise from relying on a generalized correspondence.

[0040] As illustrated in Figure 4, the processor 112 of the processing unit 11 can visualize the determined conversion function F1 together with the reference function F0 on the visualization device 12. The reference function F0 and the conversion function F1 are visualized in a manner that makes them distinguishable. Examples of such manners include differences in line type, line color, line thickness, and the presence or absence of blinking.

[0041] This configuration allows users to visually perceive the deviation of the transformation function F1 from the reference function F0, which may occur for each individual. This enables users to visually recognize the degree of deviation of each patient's respiratory function from the standard state.

[0042] As illustrated in Figure 5, the processor 112 of the processing unit 11 can cause the visualization device 12 to visualize the range of a transformation function F1 that changes depending on the range of at least one value of the subject 20 associated with the second data D2, such as PaCO2, arterial blood pH, body temperature, and 2,3-DPG concentration in the blood.

[0043] In this example, the range of possible values ​​for the conversion function F1 when PaCO2 is 60.6 [mmHg], arterial blood pH is 7.10, body temperature is in the range of 37.5 to 39.5 [°C], and blood 2,3-DPG concentration is in the range of 3.67 to 5.01 [μmol / ml RBC] is visualized as a band.

[0044] As illustrated in Figure 1, the monitoring system 10 may include a user interface 13. The user interface 13 may be configured to present the user with values ​​for several parameters related to the second data D2 described above. In other words, the user interface 13 may be part of the visualization device 12.

[0045] Figure 6 illustrates the appearance of a user interface 13 having such functionality. The user interface 13 includes a parameter display area 131 for presenting the user with the values ​​of several parameters related to the second data D2.

[0046] The visualization of the range of possible values ​​for the transformation function F1, as illustrated in Figure 5, may be based on the range of at least one of several parameters related to the second data D2, which is automatically determined by the processor 112 of the processing unit 11, or it may be done by the user inputting assumed values ​​for the range of at least one of the said parameters into the user interface 13.

[0047] As illustrated in Figure 6, the user interface 13 includes an input selection area 132. The input selection area 132 includes a "Range" button image 132a for each of the multiple parameters related to the second data D2. In addition, the parameter display area 131 includes a slider image 131a for setting the assumed value range for each of the multiple parameters related to the second data D2.

[0048] When the "Range" button image 132a is selected via a pointing device or touch operation, two knob images appear on the slider image 131a. By inputting an operation to slide each knob image, the upper and lower limits of the assumed value range for the corresponding parameter are set.

[0049] The user interface 13 may include a standard range selection area 133. In this example, the standard range selection area 133 includes a "male" button image 133a and a "female" button image 133b.

[0050] When the "Male" button image 133a is selected, the range of possible standard values ​​for male subjects is automatically set for each of the multiple parameters related to the second data D2. Similarly, when the "Female" button image 133b is selected, the range of possible standard values ​​for female subjects is automatically set for each of the multiple parameters related to the second data D2. In other words, the range of standard values ​​corresponding to the gender of the subject 20 may be set as the range of assumed values. Gender is one example of the subject's attribute information.

[0051] Although not shown in the diagram, a suitable graphical user interface (GUI) may be provided that allows setting a range of standard values ​​as a range of assumed values, depending on the subject's other attribute information. Examples of other attribute information include age group, physical constitution, and medical history.

[0052] As illustrated in Figure 1, instruction data IS corresponding to the set range of assumed values ​​is output from the user interface 13. When the instruction data IS is received by the input interface 111 of the processing unit 11, the processor 112 identifies the range in which the conversion function F1 may change based on the set range of assumed values, and outputs control data CT from the output interface 114 to visualize that range on the visualization device 12.

[0053] Compared to SaO2 and PaO2 associated with the first data D1, it can be difficult to obtain measurements for all of the multiple parameters associated with the second data D2. However, with the configuration described above, even if measurements are not available for all of the multiple parameters associated with the second data D2, it is possible to visualize the range in which the transformation function F1 determined for each subject may change due to the factors that shift the oxygen dissociation curve.

[0054] In particular, if the user can input hypothetical values ​​for at least one of several parameters related to the second data, the way the transformation function F1 changes according to the input value is also visualized, thus providing a simulation function for the changes that may occur in the subject's respiratory function due to the elements that shift the oxygen dissociation curve.

[0055] In particular, if a standard range is set according to the subject's attributes as the range in which at least one of several parameters related to the second data can take place, the way in which the transformation function F1 changes according to the attributes is also visualized, so it is possible to provide a simulation function for the changes that may occur in respiratory function that differ for each subject's attributes.

[0056] As illustrated in Figure 6, the input selection area 132 includes a "fixed value" button image 132b and a "no calibration" button image 132c for each of the multiple parameters related to the second data D2.

[0057] When the "Fixed Value" button image 132b is selected, a single knob image is displayed on the slider image 131a. By inputting an operation to slide this knob image, a specific assumed value for the corresponding parameter can be set.

[0058] When the "No Calibration" button image 132c is selected, the ability to set assumed values ​​for the corresponding parameter is removed, and the values ​​used in determining the transformation function F1 become valid.

[0059] Instruction data IS corresponding to a set specific assumption is output from the user interface 13, and the effect of this assumption is reflected in the transformation function F1 visualized in the visualization device 12. In this case as well, the way in which the transformation function F1 changes with a change in the value of at least one of several parameters related to the second data is visualized, so a simulation function can be provided for changes that may occur in the respiratory function of the subject due to the element that shifts the oxygen dissociation curve.

[0060] If the range settings for the assumed values ​​are removed for all of the multiple parameters related to the second data D2, the visualization device 12 will visualize a calibrated transformation function F2 without ranges, as illustrated in Figure 7. The calibrated transformation function F2 may be visualized together with at least one of the reference function F0 and the transformation function F1.

[0061] In this case as well, the transformation function F1 changes in response to changes in at least one of the multiple parameters related to the second data, thus providing a simulation function for the changes that may occur in the respiratory function of the subject due to the elements that shift the oxygen dissociation curve.

[0062] As illustrated in Figure 1, the monitoring system 10 may include a pulse oximetry probe 14. The pulse oximetry probe 14 is attached to the body of the subject 20. The pulse oximetry probe 14 has a well-known configuration for measuring the subject 20's SpO2.

[0063] Specifically, the pulsed oximetry probe 14 is equipped with multiple light sources that emit light of multiple wavelengths, each having different absorption characteristics for oxygenated hemoglobin. For example, a first light with a central wavelength in the red region and a second light with a central wavelength in the infrared region are irradiated onto the biological tissue, including the arteries, of the subject 20. The pulsed oximetry probe 14 is equipped with a photodetector. The photodetector is configured to detect the amount of light from the first and second lights that have passed through the biological tissue and to output a signal corresponding to that amount of light.

[0064] The degree of attenuation A1 of the first light due to arterial blood is determined from the difference between the amount of light emitted from the light source and the amount of light detected by the photodetector. Similarly, the degree of attenuation A2 of the first light due to arterial blood is determined from the difference between the amount of light emitted from the light source and the amount of light detected by the photodetector. If Φ is the ratio of the change in the degree of attenuation ΔA1 of the first light and the change in the degree of attenuation ΔA2 of the second light due to arterial blood pulsation, then SpO2 can be given as a function of Φ by the following equation. SpO2 = f (Φ) …(9)

[0065] The input interface 111 of the processing unit 11 is configured as a hardware interface capable of receiving third data D3 corresponding to the SpO2 measurement value of the subject 20. The signal output from the pulse oximetry probe 14 is used for SpO2 calculation processing by a pulse oximeter (not shown). The third data D3 may be transmitted from the pulse oximeter or manually entered by the user through a user interface (not shown).

[0066] The processor 112 reads the data corresponding to the calibrated oxygen dissociation curve stored in the storage 113 and substitutes the measured value of SpO2 corresponding to the third data D3 for the SaO2 value in equation (1). This allows for the calculation of an estimated value of PaO2 based on the calibrated oxygen dissociation curve.

[0067] By using the oxygen dissociation curve, if the SaO2 value can be obtained, the PaO2 value can be estimated. However, since SaO2 is obtained invasively, the obtained PaO2 value is inevitably time-discrete. In addition, because SaO2 is obtained invasively, obtaining PaO2 values ​​multiple times is burdensome for the subject.

[0068] With the configuration described above, once the conversion function F1 is determined using at least one of the first data D1 and the second data D2, the PaO2 estimate can be calculated continuously over time from SpO2 measurements obtained non-invasively and continuously over time by using this conversion function. This makes it possible to continuously monitor the PaO2 estimate of subject 20 without imposing the burden associated with the invasiveness of blood collection. In addition, the conversion function F1 for converting SpO2 measurements to PaO2 estimates is determined through the minimum necessary number of blood gas analyses (including zero analyses) based on the values ​​of subject 20's biological parameters that may affect the deviation of the oxygen dissociation curve. Therefore, it is possible to obtain a PaO2 estimate that reflects the subject 20's biological state while further reducing the burden on subject 20.

[0069] As illustrated in Figure 8, the processor 112 of the processing unit 11 can visualize the estimated PaO2 value calculated as described above on the visualization device 12. Specifically, control data CT configured to realize visualization of the estimated value in a predetermined manner is output from the output interface 114.

[0070] As an example, SpO2 measurements may be displayed along with a conversion function F1. In this example, SpO2 measurements are visualized as straight lines parallel to the horizontal axis. The estimated PaO2 values ​​corresponding to the intersection of this line and the curve representing the conversion function F1 may be visualized either as callouts directly indicating the numerical values, or as straight lines parallel to the vertical axis directly indicating the values ​​on the horizontal axis.

[0071] With this configuration, users can visually recognize the basis for the PaO2 value estimated from the SpO2 measurement.

[0072] In addition to or instead of the PaO2 value estimated based on the conversion function F1, the processor 112 of the processing unit 11 may cause the visualization device 12 to visualize the PaO2 value estimated based on the reference function F0.

[0073] With this configuration, users can visually recognize the difference between the PaO2 value estimated based on the actual bioparameter values ​​obtained from the subjects 20 and the PaO2 value estimated using standard values.

[0074] As illustrated in Figure 9, the processor 112 of the processing unit 11 can make the visualization device 12 visualize a marker E indicating the measurement error of the SpO2 value corresponding to the third data D3, together with a conversion function F1. Specifically, control data CT configured to realize the visualization of the marker in a predetermined manner is output from the output interface 114.

[0075] In this example, band-shaped markers E are visualized, indicating upper and lower limits of SpO2 measurements with added or subtracted errors. The intersection of the upper edge of the band corresponding to the upper limit of SpO2 and the transformation function F1 corresponds to the upper limit of the assumed PaO2 estimate. The intersection of the lower edge of the band corresponding to the lower limit of SpO2 and the transformation function F1 corresponds to the lower limit of the assumed PaO2 estimate. These estimates may be visualized in various ways as described with reference to Figure 8.

[0076] The indicator E may be visualized together with a transformation function F1 whose range of variation is visualized, as illustrated in Figure 5. In addition to or instead of the transformation function F1, the indicator E may be visualized together with a reference function F0.

[0077] Since SpO2 measurements are input to the conversion function F1 instead of SaO2 measurements, the possibility of errors in the SaO2 measurements cannot be ruled out. In addition, since SpO2 is generally presented as an integer value, the actual SpO2 values ​​can be distributed within a certain range. For example, if the presented SpO2 measurement is 95%, the actual SpO2 values ​​will be distributed within the range of 94.5% to 95.4%. Therefore, the PaO2 value estimated from a specific SpO2 measurement can also be distributed within a certain range. However, with the configuration described above, the range of possible PaO2 estimates, taking such errors into account, can be made visible to the user.

[0078] Furthermore, the error range indicated by label E may be updated by comparing the SaO2 measurement value with the SpO2 measurement value each time the SaO2 measurement value is obtained discretely over time from the subjects 20.

[0079] In addition to or instead of this, the range of possible PaO2 estimates may be updated each time PaO2 measurements are obtained from the subjects 20 in a time-discrete manner.

[0080] As illustrated in Figure 1, the input interface 111 of the processing unit 11 may be configured as a hardware interface capable of receiving fourth data D4 corresponding to the FiO2 value of the subject 20. The FiO2 value may be a measured value, a set value, or an estimated value. The fourth data D4 may be transmitted from an oxygen inhalation device (not shown) connected to the subject 20, or it may be manually entered by the user through a user interface (not shown).

[0081] In this case, the processor 112 is configured to obtain an estimated P / F ratio (PaO2 / FiO2) based on the estimated PaO2 obtained as described above and the FiO2 value corresponding to the fourth data D4. The P / F ratio is one example of an indicator showing the oxygenation capacity of the subject 20.

[0082] Conventionally, PaO2 values ​​obtained through blood gas analysis were used, so the calculated P / F ratio values ​​were inevitably discrete in time. However, with the above configuration, the P / F ratio value of subject 20 can be estimated using SpO2 measurements that can be obtained continuously in time and non-invasively. Therefore, continuous time monitoring of the oxygenation capacity of subject 20 can be achieved without imposing the burden associated with the invasiveness of blood collection.

[0083] If based on PaO2, the indicator of oxygenation capacity for subject 20 is not limited to the P / F ratio. Other examples of such indicators include A-aDO2, which corresponds to the difference between PAO2 (partial pressure of alveolar oxygen calculated from the alveolar gas formula) and PaO2; the ratio of A-aDO2 to PaO2 (A-aDO2 / PaO2); the ratio of PaO2 to PAO2 (PaO2 / PAO2); and the oxygenation index (OI). OI is obtained by multiplying the value of (FiO2 / PaO2) by the value of mean airway pressure (MAP). Note that PAO2 can be an example of information on inhaled oxygen.

[0084] The processor 112 may visualize, in addition to or instead of, the estimated value of PaO2 in each of the multiple visualization examples described with reference to Figures 4, 5, and 7 to 9, the estimated value of the P / F ratio.

[0085] Figure 10 illustrates the time series changes of the measured values ​​of SpO2, estimated values ​​of PaO2, values ​​of FiO2, and estimated values ​​of the P / F ratio, as described above. The processor 112 of the processing unit 11 can visualize at least the time series of the estimated values ​​of PaO2 on the visualization device 12, in addition to or instead of visualizing the conversion function described with reference to Figures 4, 5, and 7 to 9. Specifically, control data CT configured to realize the visualization of the time series in a predetermined manner is output from the output interface 114. In addition to or instead of PaO2, the time series of the estimated values ​​of the P / F ratio may also be visualized.

[0086] This configuration allows users to visualize the continuous time-dependent changes in estimated values ​​of PaO2 and P / F ratio for the 20 subjects.

[0087] The processor 112 of the processing unit 11 can visualize the time-series change in the estimated range of PaO2, which varies depending on the range (range in which the oxygen dissociation curve changes) that can be taken by at least one of the multiple parameters related to the second data D2 as explained with reference to Figure 5, on the visualization device 12. When data with measurement errors, such as SpO2 as explained with reference to Figure 9, is used as input, the visualized "range of estimated values" also takes into account the effect of these measurement errors. Specifically, control data CT configured to realize visualization of the time series of a range in a predetermined manner is output from the output interface 114. In addition to or instead of PaO2, the time series of the estimated range of the P / F ratio may also be visualized.

[0088] In Figure 10, the time series R1 representing the range of possible values ​​for the estimated PaO2 is visualized around the time series V1, which is shown as a solid line. Similarly, the time series R2 representing the range of possible values ​​for the estimated P / F ratio is visualized around the time series V2, which is shown as a solid line.

[0089] With this configuration, the user can visualize the time-continuous changes in the estimated values ​​of PaO2 and P / F ratio for subject 20, which may change due to factors that shift the oxygen dissociation curve.

[0090] At least one of the first data D1 and the second data D2 may be updated through periodic or irregular measurements. The processor 112 of the processing unit 11 may be configured to update the data corresponding to the conversion function F1 stored in the storage 113 when at least one of the updated first data D1 and the second data D2 is received by the input interface 111.

[0091] If the first data D1 is updated, the processor 112 re-identifies P50 using the method described with reference to equation (1), and updates the transformation function F1 with the re-identified value of P50. The data corresponding to the updated transformation function F3 is stored in the storage 113. Subsequently, PaO2 estimation based on SpO2 measurements corresponding to the third data D3 received by the input interface 111 is performed based on the updated transformation function F3.

[0092] If the second data D2 is updated, the processor 112 re-identifies P50 using the method described with reference to equations (2) to (6), and updates the transformation function F1 with the re-identified value of P50. The data corresponding to the updated transformation function F3 is stored in the storage 113. Subsequently, PaO2 estimation based on SpO2 measurements corresponding to the third data D3 received by the input interface 111 is performed based on the updated transformation function F3.

[0093] As illustrated in Figure 7, the processor 112 of the processing unit 11 can make the visualization device 12 visualize the conversion function F1 before the update and the conversion function F3 after the update. Specifically, control data CT configured to realize the visualization of the conversion function F3 is output from the output interface 114.

[0094] This configuration allows the latest status of subject 20 to be reflected in the estimated PaO2 value. In addition, the user can visualize the changes in the conversion function that accompany the updates of the bioparameters obtained from subject 20.

[0095] The processor 112 of the processing unit 11 having the various functions described above can be realized by at least one general-purpose microprocessor operating in cooperation with at least one general-purpose memory. Examples of general-purpose microprocessors include CPUs, MPUs, and GPUs. Examples of general-purpose memory include ROMs and RAMs. In this case, the ROM may store a computer program that performs the above-described processing. ROM is an example of a non-temporary computer-readable medium in which a computer program is stored. The general-purpose microprocessor selects at least a portion of the program stored in the ROM and loads it onto the RAM, and then performs the above-described processing in cooperation with the RAM. The computer program may be pre-installed in the general-purpose memory, or it may be downloaded from an external server device via a communication network and then installed in the general-purpose memory. In this case, the external server device is an example of a non-temporary computer-readable medium in which a computer program is stored.

[0096] The processor 112 may be implemented by at least one dedicated integrated circuit capable of executing the above-described computer program. Examples of dedicated integrated circuits include microcontrollers, ASICs, FPGAs, etc. In this case, the above-described computer program is pre-installed in a memory element included in the dedicated integrated circuit. This memory element is an example of a computer-readable medium in which the computer program is stored. The processor 112 can also be implemented by a combination of a general-purpose microprocessor and a dedicated integrated circuit.

[0097] Each of the configurations referenced in the preceding explanation is merely an example to facilitate understanding of this disclosure. Each configuration example may be modified or combined with other configuration examples as appropriate within the scope of this disclosure.

[0098] In the above embodiment example, a model that reproduces the oxygen dissociation curve based on Hill's formula is given as an example of a rule for mutually converting the arterial blood oxygen partial pressure value and arterial blood oxygen saturation value for subject 20. In addition, a conversion function when the index "P50" used in the model is a standard value is exemplified as a reference function. However, when a model that does not use the index "P50" is treated as a conversion rule, the reference function can be defined as a function that mutually converts the standard estimate of arterial blood oxygen partial pressure and arterial blood oxygen saturation value when arterial blood carbon dioxide partial pressure, arterial blood pH, body temperature, and 2,3-DPG concentration in the blood are all standard values.

[0099] The information illustrated in Figures 4, 5, 7 through 10 does not need to be continuously available for visualization by the visualization device 12. This information can be made available for visualization in response to appropriate instructions input through the user interface 13.

[0100] In the above embodiment, the processing device 11 is provided as a device independent of the pulse oximeter that measures the SpO2 of the subject 20. However, the processing device 11 may be built into the pulse oximeter.

[0101] The configurations listed below also constitute part of this disclosure. Item 1: An interface that accepts at least one of the following: first data corresponding to the measured arterial blood oxygen partial pressure and arterial blood oxygen saturation of the subject, and second data corresponding to at least one of the following values: arterial blood carbon dioxide partial pressure, arterial blood pH, body temperature, and 2,3-DPG concentration in the blood of the subject; A processor that determines a rule for mutually converting the arterial blood oxygen partial pressure value and arterial blood oxygen saturation value of the subject based on at least one of the first data and the second data, and causes the rule to be visualized on a visualization device, It is equipped with Processing device. Item 2: The processor causes the visualization device to visualize the rule along with a reference function corresponding to the rule when P50, which represents the arterial oxygen saturation value that gives 50% arterial oxygen saturation, is the standard value. The processing device described in item 1. Item 3: The processor causes the visualization device to visualize the range of the rule, which changes according to the range of the at least one value corresponding to the second data that can take. The processing apparatus described in item 1 or 2. Item 4: The aforementioned processor, When the interface receives a hypothetical value of at least one value corresponding to the second data, the visualization device visualizes the rule that is modified based on the hypothetical value. The processing apparatus described in item 1 or 2. Item 5: The assumed value is a standard range of at least one value corresponding to the second data. The processing device described in item 4. Item 6: The aforementioned standard range is determined according to the attribute information of the subject. The processing apparatus described in item 5. Item 7: The aforementioned processor, When the interface receives third data corresponding to the subject's transcutaneous arterial oxygen saturation, it performs at least one of the following: calculates an estimated value of the arterial oxygen partial pressure based on the third data and the rule, or calculates an estimated value of an index indicating the subject's oxygenation capacity from the estimated value of the arterial oxygen partial pressure and fourth data corresponding to the subject's inspired oxygen concentration. The calculated estimated value is made visible on the visualization device. The processing apparatus described in any one of items 1 to 6. Item 8: The processor visualizes the estimated arterial oxygen partial pressure obtained by converting the transcutaneous arterial oxygen saturation value corresponding to the third data using a reference function corresponding to the rule where P50, which represents the arterial oxygen saturation value that gives 50% arterial oxygen saturation, is the standard value, on the visualization device. The processing apparatus described in item 7. Item 9: The processor causes the visualization device to visualize, together with at least one of the reference function and the rule, the reference function corresponding to the rule when P50, which represents the arterial oxygen saturation value that gives 50% arterial oxygen saturation, is the standard value, and the rule itself. The processing apparatus described in item 7 or 8. Item 10: The processor causes the visualization device to visualize the change in the estimated value over time. The processing apparatus described in any one of items 7 to 9. Item 11: The processor causes the visualization device to visualize the time-dependent change in the range of the estimated value, which changes according to the range of the at least one value corresponding to the second data that can take. The processing apparatus described in item 10. Item 12: The aforementioned processor, The rule is updated based on at least one of the updated first data and the second data, The aforementioned rules before and after the update are made visible on the visualization device. The processing apparatus described in any one of items 1 through 11. [Explanation of Symbols]

[0102] 10: Monitoring system, 11: Processing unit, 111: Input interface, 112: Processor, 12: Visualization device, 20: Subject, D1: First data, D2: Second data, D3: Third data, F0: Reference function, F1: Transformation function, F2: Calibrated transformation function, F3: Updated transformation function, R1: Time series of PaO2 estimate range, V1: Time series of PaO2 estimate

Claims

1. An interface that accepts at least one of the following: first data corresponding to the measured arterial blood oxygen partial pressure and arterial blood oxygen saturation of the subject, and second data corresponding to at least one of the following values: arterial blood carbon dioxide partial pressure, arterial blood pH, body temperature, and 2,3-DPG concentration in the blood of the subject; A processor that determines a rule for mutually converting the arterial blood oxygen partial pressure value and arterial blood oxygen saturation value of the subject based on at least one of the first data and the second data, and causes the rule to be visualized on a visualization device, It is equipped with Processing device.

2. The processor causes the visualization device to visualize the rule along with a reference function corresponding to the rule when P50, which represents the arterial oxygen saturation value that gives 50% arterial oxygen saturation, is the standard value. The apparatus according to claim 1.

3. The processor causes the visualization device to visualize the range of the rule, which changes according to the range of the at least one value corresponding to the second data that can take. The apparatus according to claim 1.

4. The aforementioned processor, When the interface receives a hypothetical value of at least one value corresponding to the second data, the visualization device visualizes the rule that is modified based on the hypothetical value. The apparatus according to claim 1.

5. The assumed value is a standard range of at least one value corresponding to the second data. The apparatus according to claim 4.

6. The aforementioned standard range is determined according to the attribute information of the subject. The apparatus according to claim 5.

7. The aforementioned processor, When the interface receives third data corresponding to the subject's transcutaneous arterial oxygen saturation, it performs at least one of the following: calculates an estimated value of the arterial oxygen partial pressure based on the third data and the rule, or calculates an estimated value of an index indicating the subject's oxygenation capacity from the estimated value of the arterial oxygen partial pressure and fourth data corresponding to the subject's inspired oxygen concentration. The calculated estimated value is made visible on the visualization device. The apparatus according to claim 1.

8. The processor visualizes the estimated arterial oxygen partial pressure obtained by converting the transcutaneous arterial oxygen saturation value corresponding to the third data using a reference function corresponding to the rule where P50, which represents the arterial oxygen saturation value that gives 50% arterial oxygen saturation, is the standard value, on the visualization device. The apparatus according to claim 7.

9. The processor causes the visualization device to visualize, together with at least one of the reference function and the rule, the rule, which is the standard value when P50, which represents the arterial oxygen saturation value that gives 50% arterial oxygen saturation, is the standard value. The apparatus according to claim 7.

10. The processor causes the visualization device to visualize the change in the estimated value over time. The apparatus according to claim 7.

11. The processor causes the visualization device to visualize the time-dependent change in the range of the estimated value, which changes according to the range of the at least one value corresponding to the second data that can take. The apparatus according to claim 10.

12. The aforementioned processor, The rule is updated based on at least one of the updated first data and the second data, The aforementioned rules before and after the update are made visible on the visualization device. The apparatus according to claim 1.

13. A computer program that can be executed by a processor mounted on a processing unit, By being executed, the processing device will The system accepts at least one of the following: first data corresponding to the measured arterial blood oxygen partial pressure and arterial blood oxygen saturation of the subject, and second data corresponding to at least one of the following values: arterial blood carbon dioxide partial pressure, arterial blood pH, body temperature, and 2,3-DPG concentration in the blood of the subject. Based on at least one of the first data and the second data, a rule is determined to convert between the arterial blood oxygen partial pressure value and the arterial blood oxygen saturation value of the subject. The aforementioned rules are made visible on the visualization device. Computer program.

14. Processing device and Visualization device, It includes, The aforementioned processing apparatus is An interface that accepts at least one of the following: first data corresponding to the measured arterial blood oxygen partial pressure and arterial blood oxygen saturation of the subject, and second data corresponding to at least one of the following values: arterial blood carbon dioxide partial pressure, arterial blood pH, body temperature, and 2,3-DPG concentration in the blood of the subject; A processor that determines a rule for mutually converting the arterial blood oxygen partial pressure value and arterial blood oxygen saturation value of the subject based on at least one of the first data and the second data, and visualizes the rule on the visualization device, It is equipped with A monitoring system.

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