The following relates generally to the capnography arts, medical monitoring arts, and related arts.
A capnography device monitors the concentration or partial pressure of carbon dioxide (CO2) in respiratory gases. Capnography is commonly used in conjunction with mechanically ventilated patients in order to assess respiratory system status. A skilled anesthesiologist can usually evaluate the capnogram (that is, the CO2 trend line as measured by a capnograph device) to assess respiratory health.
Capnography is increasingly used as a more generic vital sign for assessing patient health. For example, capnography may be used to monitor a patient who is breathing spontaneously and not undergoing mechanical ventilation, using a side stream capnograph device configuration in which respired air is sampled via a nasal cannula in conjunction with a dedicated sampling pump. In these broader contexts, medical personnel with limited expertise in anesthesiology are required to assess respiratory health on the basis of capnograph data. To facilitate this, it is common for the capnograph device to be programmed to output standard derived parameters, particularly respiration rate (RR) and end-tidal CO2 (etCO2). The RR is the breathing rate, quantified as the (quasi-)periodicity of the capnogram waveform. The etCO2 is the partial pressure at the end of the exhalation phase. However, since the expired CO2 is usually highest at the end of the exhalation phase, etCO2 is commonly defined as the maximum observed CO2 partial pressure over the breathing cycle.
While RR and etCO2 are useful parameters, they do not capture the rich informational content of the capnogram waveform. To this end, it is also known to perform automated capnogram waveform analyses, designed to mimic clinical analyses that might be performed by a skilled anesthesiologist. For example, Colman et al., U.S. Pat. No. 8,412,655 and Colman et al., U.S. Pat. No. 8,414,488 disclose capnogram waveform analyses such as correlating pauses with apnea events, correlating a long downward slope of the capnogram waveform with possible partial airway obstruction, correlating a low capnogram waveform with possible low cardiac output, correlating a rounded capnogram waveform with a possible problem with the nasal cannula, or so forth. Based on such waveform analyses, the capnograph device may provide informational messages such as “open airway”, “check airway”, “possible low cardiac output”, “check cannula interface”, or so forth.
Capnogram waveform analyses provide richer information from the capnogram, but entail complex processing such as detecting the breath cycling, amplitude and period normalization, and segmenting regions of the capnogram waveform within each breath cycle. These complex analyses introduce numerous possible error mechanisms such as incorrect waveform segmentation or information loss during the normalization operations.
Some additional background references include the following.
WO 2016/108121 A1 published Jul. 7, 2016 discloses, among other aspects, a gas concentration monitoring system that may include a processor configured to detect a concentration of a selected gas in a sample gas flow obtained from a physical interface to a patient. A dataset is formed, including a plurality of data points, each data point corresponding to the detected concentration of the selected gas within the sample gas flow during a sampling time. The data set may be variously employed. For example, the data points may be grouped according to a frequency of occurrence of the data points within the sampling time. A signal confidence and/or signal quality may be determined based on relative characteristics between the groups of data points. WO 2016/108121 A1 claims priority to U.S. Ser. No. 62/098,367 filed Dec. 31, 2014. WO 2016/108121 A1 and U.S. Ser. No. 62/098,367 are each incorporated herein by reference in its entirety.
WO 2016/108127 A1 published Jul. 7, 2016 discloses, among other aspects, a capnography system. A controller is configured to obtain a sample gas flow from a physical interface for a patient. A change is determined in a characteristic of the sample gas flow during a sampling time interval. It is determined whether the change in the characteristic of the sample gas flow during the sampling time interval is equal to or greater than a corresponding threshold value. It is determined that supplemental oxygen is provided when it is determined that the change in the characteristic of the sample gas flow is equal to or greater than the threshold value. It is determined that supplemental oxygen is not provided when it is determined that the change in the characteristic of the sample gas flow is less than the threshold value. WO 2016/108127 A1 claims priority to U.S. Ser. No. 62/097,946 filed Dec. 30, 2014. WO 2016/108127 A1 and U.S. Ser. No. 62/097,946 are each incorporated herein by reference in its entirety.
U.S. Ser. No. 62/203,416 titled “Capnography with Decision Support System Architecture” filed Aug. 11, 2015 is incorporated herein by reference in its entirety. U.S. Ser. No. 62/203,416 discloses, among other aspects, a capnograph device that includes a carbon dioxide measurement component and an electronic processor programmed to generate a capnogram comprising carbon dioxide level sample values measured as a function of time. End-tidal carbon dioxide (etCO2) is determined from the capnogram, and an etCO2 parameter quality index (etCO2 PQI) is computed using one or more quantitative capnogram waveform metrics computed from the capnogram. A respiration rate (RR) value is also determined from the capnogram, and a RR PQI is computed using the RR value and the etCO2 PQI. A respiratory well-being index (RWI) may be computed from the etCO2 and RR values and the etCO2 and RR PQI values. In some embodiments the one or more capnogram waveform metrics are computed from a capnogram histogram generated from the capnogram.
The following discloses a new and improved systems and methods that address the above referenced issues, and others.
In one disclosed aspect, a patient monitoring device comprises a capnograph device, a pulse oximeter, and an electronic processor programmed to: generate a capnography index indicative of patient well-being from a capnogram measured by the capnograph device; generate an arterial blood oxygen saturation (SpO2) index indicative of patient well-being from SpO2 measured by the pulse oximeter; compute a patient safety index from the capnography index and the SpO2 index; and compute one or more clinical warnings determined based at least in part on the patient safety index. A display component may be configured to display at least one of the computed one or more clinical warnings.
In another disclosed aspect, a non-transitory storage medium stores instructions readable and executable by an electronic processor to perform patient monitoring comprising: generating a capnography index indicative of patient well-being from a capnogram measured by a capnograph device; generating an arterial blood oxygen saturation (SpO2) index indicative of patient well-being from SpO2 (72) measured by a pulse oximeter; and computing a patient safety index from the capnography index and the SpO2 index.
One advantage resides in providing a capnograph device whose output more effectively assesses patient respiratory health.
Another advantage resides in providing a capnograph device outputting derived parameters characterizing the detailed capnogram waveform without requiring breath detection or segmentation of the capnogram waveform.
Another advantage resides in more accurate respiratory system status information from capnogram data.
Another advantage resides in providing clinical decision support that synergistically combines capnography information with pulse oximetry information.
Another advantage resides in providing clinical decision support employing both capnography information with pulse oximetry information, which provides a ranked list of clinical warnings generated by each constituent monitoring modality.
A given embodiment may provide none, one, two, more, or all of the foregoing advantages, and/or may provide other advantages as will become apparent to one of ordinary skill in the art upon reading and understanding the present disclosure.
The invention may take form in various components and arrangements of components, and in various steps and arrangements of steps. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention.
In some embodiments disclosed herein, parameter quality indices are computed to quantitatively assess the reliability of the respiratory rate (RR) and end-tidal CO2 (etCO2) evaluated from the capnogram. A respiratory well-being index (RWI) may also be computed, based in part on the etCO2 parameter quality index (etCO2 PQI) and the RR parameter quality index (RR PQI). These parameter quality indices enable medical personnel to interpret the capnogram using conventional tools, especially the RR and etCO2, but provide metrics (the quality control indices) to assist medical personnel in assessing whether the RR and etCO2 are reliable data for making clinical decisions.
Further, in some embodiments the parameter quality indices are computed at least in part using a histogram of CO2 value counts versus (binned) CO2 level. This histogram is computed over a time interval encompassing several breaths. For example, the histogram is acquired over a 30 second time interval in one illustrative embodiment, which corresponds to about 6-10 breaths for a normal adult patient respiration interval of 3-5 seconds/breath (12-20 breaths per minute), up to 30 breaths for a rapidly respiring infant (respiration rate of 60 breaths per minute).
Advantageously, the capnogram histogram is computed without segmenting the waveform into different regions (e.g. inspiration, expiration) and without segmenting individual breath cycles (that is, without a breath detector). The capnogram histogram advantageously has a “standard” shape for a normally respiring patient, due to the typical capnogram pattern in which the CO2 level is close to zero during the inspiration phase and close to its maximum (i.e. close to etCO2 for the patient) during the expiration phase. These two phases define respective low and high regions of the disclosed capnogram histogram, with a third transitional histogram region in-between. Rich information about the capnogram waveform can be extracted from the capnogram histogram, without reliance upon the difficult and often imprecise task of segmenting the capnogram waveform into breath cycles which are then further segmented into inspiration and expiration time intervals.
In particular, the etCO2 parameter quality index (PQI) is computed primarily or entirely using the histogram. In some embodiments the etCO2 PQI is computed further based on capnogram characteristics that can be quantified without segmenting the capnogram into inspiration and expiration regions. Illustrative embodiments of the etCO2 PQI do rely upon breath detection and capnogram waveform segmentation, as the RR is intimately associated with (indeed defined by) the breath cycle. However, the RR PQI is optionally further based on the etCO2 PQI thereby incorporating waveform information from the capnogram histogram.
The RWI is computed based on the etCO2 and RR values, and further based on the etCO2 PQI and RR PQI. Incorporating the PQI values into the RWI captures the recognition herein that a poor capnogram waveform is often an indication of poor respiratory health, rather than being an indicator of a capnograph measurement problem.
With reference to
The illustrative capnograph device 10 has a sidestream configuration in which respired air is drawn into the capnograph device 10 using the pump 22, and the CO2 measurement cell 20 is located inside the capnograph device 10. That is, the sidestream capnograph device 10 includes, as a unit, the carbon dioxide measurement component 20, the electronic processor 30, and the pump 22 connected to draw respired air though the carbon dioxide measurement component 20. The sidestream configuration is suitably used for a spontaneously breathing patient, i.e. a patient who is breathing on his or her own without assistance of a mechanical ventilator. In an alternative configuration, known as a mainstream configuration (not illustrated), the CO2 measurement cell is located externally from the capnograph device housing, typically as a CO2 measurement cell patient accessory that is inserted into the “mainstream” airway flow of the patient. Such a mainstream configuration may, for example, be employed in conjunction with a mechanically ventilated patient in which the CO2 measurement cell patient accessory is designed to mate into an accessory receptacle of the ventilator unit, or is installed on an airway hose feeding into the ventilator. The disclosed approaches for quantitatively assessing parameter quality and patient respiratory well-being are readily applied either in conjunction with a sidestream capnograph device (as in the illustrative example of
With continuing reference to
The capnograph electronics 30 may be variously implemented, such as by a suitably programmed electronic processor, e.g. a microprocessor or microcontroller of the capnograph 10. While a single electronics unit 30 is illustrated, it is alternatively contemplated to employ various combinations of electronics, for example different electronic components may be operatively interconnected to implement a pump, power supply, infrared light source and detector, power supply (for the CO2 measurement cell 20), analog-to-digital conversion circuitry (to sample the infrared light detector of the CO2 measurement cell 20), and so forth. Still further, it is contemplated for the electronics that perform the capnograph data processing to be disposed outside of the capnograph device itself. For example, the capnograph data processing may be performed by electronics in another device (for example, the computer of a nurses' station that receives the CO2 signal from the measurement cell 20, or that receives a capnogram generated by the capnograph device and performs further processing). It will be still further appreciated that the capnograph data processing disclosed herein as being performed by the capnograph electronics 30 may be embodied by a non-transitory storage medium storing instructions that are readable and executable by the microprocessor, microcontroller, or other electronic processor to perform the disclosed capnograph data processing. Such non-transitory storage media may, by way of non-limiting illustration, include a hard disk drive or other magnetic storage medium, a flash memory, read-only memory (ROM) or other electronic storage medium, an optical disk or other optical storage medium, various combinations thereof, or so forth.
With continuing reference to
With continuing reference to
The capnogram histogram of a typical capnogram has certain characteristics. The histogram for a typical capnogram will have a higher number of occurrences of CO2 sample values in the bins of Region R1 and Region R3, and the number of occurrences in the bins of Region R2 should be lower than the number of occurrences in Regions R1 and R3. That is, the capnogram histogram 42 has a peak in lower Region R1 and a peak in upper Region R3, and a valley in the intermediate Region R2. Further, the peak in upper Region R3 is typically more spread-out than the peak in Region R1, as seen in the idealized capnogram histogram 42 of
The capnogram histogram 42 is computed from the capnogram 40 in the sliding window, with a new histogram computed every few seconds, e.g. every 5 seconds in one illustrative example employing a 30 second window. There is no attempt to synchronize the window with an integer number of breaths, but the window is preferably large enough to encompass several breaths (e.g. for a normal adult patient respiration interval of 3-5 seconds/breath the illustrative 30 sec window encompasses 6-10 breaths). By re-computing the histogram on a shorter time interval than the window size (e.g. every 5 sec using a 30 sec window) the successive histogram windows significantly overlap providing for a smoothing effect as a function of time. Since there is no synchronization with the breath cycling, there is no need to employ a breath detector in constructing the capnogram histogram 42, and the determination of the histogram 42 is a very fast CO2 sample binning process.
An end-tidal carbon dioxide (etCO2) value and a respiratory rate (RR) value are determined from the capnogram signal 40. Substantially any technique to detect a signal maximum can be used to detect the etCO2 value. For example, in some embodiments, the etCO2 value is determined from the capnogram signal 40 by analysis of the histogram 42 derived from the capnogram signal 40. In this approach, the CO2 level of the highest CO2 level bin having a non-zero sample count provides an etCO2 value. Similarly, substantially any technique to determine periodicity of a signal can be used to detect the RR value. For example, the RR value can be determined by detecting breaths using the breath detector 48 and thereby determining breath intervals (the RR being the inverse of the average breath interval). Alternatively, a Fast Fourier Transform (FFT) can be applied to determine the RR value in the frequency domain.
With continuing reference to
The metric of the portion of the histogram 42 that is above the baseline characterizes the portion of the histogram that is in Region R3 as compared with Region R1. This metric is large for a normal capnogram, but may be low in the case of a poor capnogram waveform having an inconsistent expiratory plateau.
The metric of the difference between the maximum CO2 in Region R3 and the CO2 level in Region R3 having the highest histogram counts is expected to be small because the end-tidal point should have the largest CO2 value and a CO2 level bin at or close to etCO2 should also have a large number of counts since the expiratory plateau usually flattens as it approaches the end-tidal point. This metric may be computed from the difference between the CO2 level of the bin of Region R3 having a non-zero count and the CO2 level of the bin of Region R3 storing the highest count.
The metric comparing the upper Region R3 count versus the intermediate Region R2 count quantifies the expectation that a sharp transition should be present from the inspiratory phase to the expiratory phase in the capnogram 40. In such a case, the intermediate Region R2 count is low and the upper Region R3 count is high. However, since there are more bins in intermediate Region R2 than in upper Region R3, this metric may preferably be quantified using the average count over all bins of Region R2, and likewise using the average count over all bins of Region R3.
The metric of the fraction of the total counts in upper Region R3 should be high since a large portion of the capnogram waveform consists of the expiratory phase. This metric may be computed using the ratio of the total counts in upper Region R3 to the total counts in the capnogram histogram 42.
With brief reference to
It will be noted that the CO2 fall time can be determined without performing breath detection, and without segmenting the capnogram waveform into inspiratory and expiratory phases. For example, in the illustrative example the CO2 fall time is computed by identifying when a high CO2 level falls below Tupper and then when it falls below Tlower.
With returning reference to
where the index i ranges over the metrics contributing to etCO2 PQI 44, Si is the score (i.e. value) of the ith metric, and Wi is a weight for the ith metric. The weights may be generated manually (e.g. based on assessment by a skilled pulmonologist, anesthesiologist, respiratory therapist or other expert of the relative importance of the various metrics) or by performing machine learning using a training set of representative capnograms each labeled by a skilled pulmonologist, anesthesiologist, or other expert as to reliability of the etCO2 value obtained from the training capnogram.
The five metrics contributing etCO2 PQI in the example are merely illustrative. More generally, it will be appreciated that the capnogram histogram 42 is expected to exhibit a large narrow peak in a lower Region R1 corresponding to the inspiration phase of the respiratory cycle, a large slightly broader peak in an upper Region R3 corresponding to the expiratory phase, and a deep valley in an intermediate Region R2 corresponding to transitions from inspiration-to-expiration and from expiration-to-inspiration. Deviations from this basic histogram shape are expected when the capnogram waveform is degraded, and consequently etCO2 values are expected to be less reliable. Various metrics can be constructed and optimized using histograms constructed for training capnograms in order to quantitatively characterize metrics to assess the histogram shape and hence the capnogram waveform. The optimal choice of metrics, and their weights, depends on the capnograph device and its connection to the patient, the demographic being monitored, the desired sensitivity (e.g. how “bad” should the capnogram waveform be before the etCO2 PQI starts to significantly decrease), and so forth. In some embodiments the metrics may be optimized for different patient connections (e.g. nasal cannula versus airway adaptor), different patient breathing conditions (e.g. spontaneous breathing versus various mechanical ventilation modes), or so forth. The capnogram histogram shape reflects the capnogram waveform, so quantitative metrics of the histogram provide assessment of the capnogram waveform quality without the need to detect breath intervals in the capnogram and without the need to segment the capnogram into inspiration and expiration phases. In the illustrative example, one metric (CO2 fall time) is extracted directly from the capnogram 40 rather than from the capnogram histogram 42, but this is still done without performing breath detection or segmenting the capnogram into breathing phases. The computations are fast, and can be performed in real-time (that is, with a delay of a few tens of seconds, a few seconds, or less).
With continuing reference to
In the illustrative embodiment of
The RR PQI 46 is again suitably computed as a weighted sum of the contributing metrics:
where the index i ranges over the metrics contributing to RR PQI 46, Si is the score (i.e. value) of the ith metric, and Wi is a weight for the ith metric. The weights again may be generated manually or by performing machine learning using a training set of representative capnograms labeled as to RR reliability. The metrics contributing RR PQI in the example are again merely illustrative, and additional or other metrics are contemplated.
In some embodiments, a respiratory well-being index (RWI) 50 is also computed, which represents a quality score to assess the respiratory well-being of a patient using the capnogram 40. The RWI 50 is designed to help medical personnel evaluate the overall respiratory well-being of the patient. RWI 50 may also be used to identify non-intubated patients who are at risk for hypoventilation due to central or obstructive apnea, such as during procedural sedation. In a suitable embodiment, metrics that serve as weighted inputs to the RWI 50 include the measured RR and etCO2 and the corresponding RR PQI 44 and etCO2 PQI 46. In general, if either the RR or etCO2 are outside their respective normal ranges then this lowers the RWI 50. A lower RR PQI 44 or lower etCO2 PQI 46 also lowers the RWI 50. In some embodiments, a time-since-last-breath metric is also incorporated into the RWI 50 in order to facilitate its use in detecting airway obstruction or apnea episodes. For example, the time-since-last-breath may be quantified from the capnogram 40 by a block 52 assessing the time since last elevated CO2 level.
The indices 44, 46, 50 are suitably re-calculated each time the capnogram histogram 42 is updated, e.g. every 5 seconds in the illustrative example. Since the illustrative histogram calculation window is 30 seconds, the first calculation of the indices 44, 46, 50 is performed after 30 seconds of the capnogram 40 are acquired.
If the capnograph device 10 is programmed to provide informational messages based on the RR and etCO2 values, then the indices 44, 46, 50 may optionally be used to suppress these informational messages when the underlying RR or etCO2 is unreliable as indicated by the corresponding PQI. By way of non-limiting illustration, in one contemplated embodiment the messaging scheme of Table 1 is employed, with the outputs only being displayed when RWI is lower than some threshold value.
In this illustrative messaging scheme, the “patient anxious” message is suppressed if the RR PQI 46 is below a threshold value.
In addition to (or in place of) computing and displaying (on the display component 32) values of probative parameters such as etCO2, RR, etCO2 PQI 44, RR PQI 46, and/or RWI 50, it is contemplated to display on the display component 32 the capnogram histogram 42 itself. As previously discussed, the capnogram histogram 42 embodies substantial information about the capnogram waveform in a format that may be more readily perceived by medical personnel as compared with reading a display of the capnogram 40 (which may optionally also be displayed on the display 32, e.g. as a trend line). One advantage of displaying the capnogram histogram 42 as compared with displaying a trend line of the capnogram 40 is that the trend line is typically scrolled horizontally, whereas the capnogram histogram 42 does not scroll and is updated, e.g. every 5 seconds with substantial overlap between successive updates due to the large window overlap between successive updates (e.g. with a 30 second window and 5 sec updates, each successive histogram is derived from 25 seconds of the same capnogram data that was used to generate the immediately previous histogram and only 5 seconds of new capnogram data).
The foregoing embodiments advantageously provide capnography monitoring with output that is more readily comprehended and acted upon by medical personnel. In some embodiments which follow, the capnography monitoring is synergistically combined with blood hemoglobin oxygen saturation information, for example arterial blood oxygen saturation (SpO2) measured by a pulse oximeter which measures the pulsatile part of blood in the finger or other tissue at which the SpO2 measurement is made. While venous blood is the majority of the blood in the finger, venous blood does not pulse significantly, and hence is not considered in the SpO2 measurement. Only the arterial blood pulsates strongly, and hence the pulse oximeter measures the arterial blood oxygen saturation. The term “arterial” refers to blood that has not yet participated in gas exchange (causing loss of O2 captured in the lungs and collection of CO2 from the tissues). It may be noted that the arterial blood may be located in arteries or in capillaries (including small capillaries)—such blood is nonetheless arterial blood even if located in the capillaries, so long as it has not yet participated in gas exchange. The SpO2 measurement thus measures oxygenation of arterial blood in the fingertip or other tissue being measured, whether that arterial blood is in arteries, capillaries, or is in both blood vessel types.
It is recognized herein that medical professionals often have a tendency to rely primarily on the SpO2 vital sign to the exclusion of capnography data. This is due both to greater familiarity of many clinicians with SpO2 as compared with capnography, and the recognition by clinicians that a low SpO2 level is a direct clinical measure of an urgent medical problem, namely that the patient is not being sufficiently oxygenated. By contrast, interpretation of the capnography data, such as the etCO2, is more complex, and may be more difficult for some medical professionals.
However, it is recognized herein that capnography is complementary to SpO2 monitoring because capnometry can serve as a leading indicator by detecting a respiration problem before it manifests as reduced SpO2 level. The capnography measures a direct product of blood-gas exchange in the lungs; whereas, SpO2 measures a lagging metric of this blood-gas exchange and provides a clinical warning only after an insufficiency in transfer of oxygen to blood in the lungs occurring over an extended period of time produces a cumulative reduction in blood oxygenation.
Another way that capnography can be complementary to SpO2 monitoring is in the case of a patient who is receiving supplemental oxygen. Here, the supplemental oxygen facilitates a high SpO2 level, but in so doing may mask an underlying blood-gas exchange problem in the lungs or respiration rate and/or volume is low. Capnography, by directly measuring the CO2 product of this blood-gas exchange in the lungs, can detect respiratory problems that may be masked in the SpO2 measurement by the additional oxygenation provided by the supplemental oxygen.
In approaches disclosed herein, SpO2 and capnography are synergistically combined to provide patient monitoring that more rapidly detects respiratory problems, and can detect respiratory problems that may otherwise be masked by supplemental oxygen, while still providing life-critical blood oxygenation monitoring via SpO2 monitoring. In some embodiments, the disclosed approaches further provide synergistic clinical decision support. The SpO2 and capnography information are analyzed separately to identify one or more clinical warnings, and these warnings are displayed in a ranked fashion based on urgency.
The RWI, by itself, does not consider blood oxygenation (or, more generally, the cardiac condition of the patient). In the following illustrative embodiments, the arterial oxygen saturation level (SpO2) of the patient is combined with the RWI to calculate an index of the overall patient safety, referred to herein as a patient safety index (PSI). The illustrative PSI is a value in the range of 1 to 10, where 1 is the lowest score (patient needs immediate attention) and 10 is the highest score (healthy ventilation and oxygenation). It is possible for a patient to simultaneously have both inadequate oxygen saturation in the blood, indicated by low hemoglobin oxygen saturation, and adequate respiration, indicated by normal respiration rate and end-tidal CO2 concentration.
With reference to
The illustrative embodiment of
A multi-parameter patient monitor 80 receives as inputs the RWI 50 and the etCO2 value 60, and also optionally receives other physiological parameters such as RR 62 from the capnograph device 10, HR 74 from the pulse oximeter 70, blood pressure from a blood pressure monitor (components not shown), and/or so forth. The illustrative patient monitor 80 includes a display 82 and an electronic processor 84. As is conventional in patient monitoring, the electronic processor 84 is optionally programmed to display one or more of the received physiological parameters 60, 62, 72, 74 on the display 82, e.g. as a trend line and/or as numerical values, optionally averaged over an averaging time window. Physically, the patient monitor 80 may be variously embodied, e.g. as a bedside patient monitor, a nurses' station monitor, a wearable patient monitoring device, or so forth. Some illustrative examples of patient monitors include the various IntelliVue™ patient monitors available from Koninklijke Philips N.V., Eindhoven, the Netherlands. In other embodiments, the patient monitor 80 may be integrated with some other medical device—for example, the patient monitor 80 may be a component of a mechanical ventilator (not shown).
The electronic processor 84 of the illustrative patient monitor 80 of
In the following, an illustrative example of one suitable formulation of the PSI 92 is set forth.
In the illustrative example of the SpO2 index 90, the arterial blood oxygen saturation (SpO2) measurement 72 is input into a scoring function which outputs a score between +10 and −10. If the arterial blood oxygen saturation 72 is above an upper threshold (e.g. 94%), then the scoring function outputs the maximum scoring value of 10. For lower values of the oxygen saturation 72, the score decreases. If the arterial blood oxygen saturation 72 is below a lower threshold (e.g. 80%), then the scoring function outputs the minimum scoring value of −10.
In the illustrative example of calculating the PSI 92, a weighting factor is applied to the oxygen saturation score 90 and to the calculated RWI 50 from the capnography device 10. The weighted sum of these scores is the resulting PSI value. For example if the arterial blood oxygen saturation is 92% then the corresponding score may be 3. If the corresponding RWI is 5 and if the weights for both inputs is 0.5, the output PSI is 4, indicating that the patient may potentially be at risk. In the illustrative example, the choice of a scale in the range [−10,10] for the SpO2 score ensures that a low SpO2 value will draw down the combined PSI to ensure that it captures the clinically urgent situation in which the patient's blood oxygenation is low.
A variant embodiment of the arterial blood oxygen saturation scoring adjusts the SpO2 score 90 for the SpO2 when the patient is receiving supplemental oxygen. This adjustment captures the clinical reality that an arterial blood oxygen saturation that would be considered near normal (i.e. 94%) when the patient is breathing air would be considered low if the same patient is receiving supplemental oxygen through a nasal cannula, mask or endotracheal tube. To account for this difference in expected normal range, function generating the SpO2 index 90 is shifted to lower value by a small amount (i.e. 2%) when it is known that the patient is receiving supplemental oxygen. This variant embodiment allows the PSI 92 to be more sensitive to low oxygen saturation values when the patient is receiving supplemental oxygen and saturation values are expected to be a little higher.
The determination that the patient is on supplemental oxygen may be based on a user input to the patient monitor 80 (e.g., when setting up the patient profile the nurse or other medical professional may select a radial input button indicating the patient is on supplemental oxygen). Alternatively, an automated mechanism for detecting that the patient is on supplemental oxygen may be utilized—for example, if the patient monitor 80 is integral with a mechanical ventilator or is connected to receive data from a mechanical ventilator, and the available data include fraction of inspired oxygen (FiO2), then the patient monitor 80 may automatically detect whether the patient is on supplemental oxygen based on the FiO2 value. In such embodiments, it is further contemplated to adjust the aforementioned small shift to lower value of the SpO2 index 90 based on the supplemental oxygen level, e.g. a larger downward shift in the index value may be applied for higher FiO2 value (as a higher fraction of inspired oxygen indicates more supplemental oxygen).
With reference to
In combining the SpO2 index 90 and the RWI 50 to generate the PSI 92, the RWI and the SpO2 values should reflect physiologic conditions corresponding to the same point in time. If these two input signals are misaligned in time, they may not work in concert to indicate patient safety. Because the RWI and the SpO2 are derived from different physiologic signals, one measured by the capnography device 10 and the other by the pulse oximeter 70, there is a possibility that one may reflect an event or conditions that occurred before or after the other. In other words, the data streams from the two different devices 10, 70 may not be synchronized in time. Another cause of misalignment may be signal averaging. It may be beneficial to average the input signals to improve variability of the inputs. However, signal averaging delays the response of the signals, so that one or the other of the two signals may be delayed relative to the other signal (SpO2 or capnometry). Various approaches can be used to synchronize the SpO2 and capnography signals, e.g. using a common clock signal output to the two devices 10, 70 from the patient monitor 80, transmitting a synchronizing clock signal from one of the two devices 10, 70 to the other, or so forth. In another approach, an identifiable landmark in the signals can be used, for example if the capnography device 10 is a multifunction patient monitoring device that also measures heart rate then this heart rate may be used to synchronize with the HR 74 measured by the pulse oximeter 70 to synchronize the signals from the two devices 10, 70. These are merely illustrative synchronization approaches.
With reference to
The PSI 92 may be displayed, e.g. as another patient data stream on the patient monitor 80. However, in the illustrative example of
An illustrative monitoring process performed using the embodiment of
Optionally, the PSI signal may be averaged over an extended time or over a number of breaths. For example, if the PSI is calculated every 5 seconds, it may be beneficial to display the average PSI calculated during the prior minute rather than display the resulting PSI as calculated every 5 seconds. This can help to avoid producing false alarms due to noise in the PSI data stream.
The illustrative example of
As further contemplated variants, the disclosed RWI is to be understood to be a non-limiting illustrative example of a capnography index which represents the patient's well-being as indicated by the capnogram measured by the capnograph device 10. More generally, other of capnography index formulations may be employed. As another illustrative example, the end-tidal CO2 (etCO2) may be used as the capnography index, optionally scaled between minimum and maximum index values similarly to the disclosed scaling operation for SpO2 (e.g. the illustrative examples of
The approach of
Filing Document | Filing Date | Country | Kind |
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PCT/EP2018/050799 | 1/15/2018 | WO | 00 |
Number | Date | Country | |
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62446608 | Jan 2017 | US |