Monitoring respiratory variation of pulse pressure

A monitoring device may include a display, an input device to receive patient-related data, and logic. The logic may determine the pulse pressure of the patient based on the patient-related data, calculate a respiratory variation of the pulse pressure of the patient, and generate a first value based on the respiratory variation of the pulse pressure of the patient and a mean pulse pressure of the patient. The logic may also output the first value to the display. The logic may update the first value in a continuous, real-time or near real-time manner.

BACKGROUND INFORMATION

Introducing fluids to patients, such as patients in shock, is often the first step in medical treatment. However, not all patients are responsive to fluid. For example, responsiveness to fluid administration may be based on the amount of fluid in the vascular space of the patient. Responsiveness to fluid administration may also be based on how full the heart is before each contraction, referred to as preload or ventricular preload. The relationship between the preload state and contractility of the heart has been described and has been shown graphically via the Starling curve.

For example,FIG. 1illustrates a Starling curve100that depicts the relationship between the ventricular preload state of a patient and stroke volume. Referring toFIG. 1, when the preload state of the patient is relatively low, a small change in preload results in a relatively large increase in stroke volume, as illustrated at position A. In contrast, when the preload state of the patient is relatively high, a small change in preload results in a very small change in stroke volume, as illustrated in position B.

While a patient whose heart is in condition A may benefit from fluid administration, a patient in shock whose heart is in condition B may not benefit and may actually be harmed by fluid administration.

Respiratory variation in the pulse pressure of ventilated patients has been shown to correlate with fluid responsiveness. Current methods to monitor the pre-load sate of the heart and fluid responsiveness include echocardiography and the placement of a Swan-Ganz catheter. The Swan-Ganz catheter is inserted into the patient and is carefully moved to the heart to obtain pressure measurements from different vascular compartments. Thermal dilution is used with the Swan-Ganz catheter to measure cardiac output and stroke volume is calculated by dividing cardiac output by the pulse rate. Stroke volume can then be compared before and after fluid administration to determine the preload state of the heart. A problem with using a Swan-Ganz catheter is that the catheter is very invasive and is difficult to place in many patients, such as pediatric patients.

Other monitoring systems track cardiac output and can provide assessments of fluid responsiveness, but require a large central arterial catheter that places the extremity at risk and is unsuitable for use in many patients, such as children. In addition to being very invasive, current methods aimed at quantifying respiratory variation of the pulse pressure are not performed in a continuous manner that enable medical personnel to receive current information regarding the state of the patient.

DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS

Implementations described herein provide for continuously monitoring the respiratory variation of pulse pressure. This information may be used as a measure of the preload state of the patient. Implementations described herein also allow the monitoring to be accomplished in a non-invasive manner or relatively non-invasive manner, thereby resulting in little to no trauma or risk to the patient.

FIG. 2is a block diagram of an exemplary environment in which systems and methods described herein may be implemented. Referring toFIG. 2, environment200may include patient210, catheter220, ventilator230and monitoring device240.

Patient210may represent any person (i.e., an adult or child) that may be in some sort of medical distress, such as in shock or other traumas. Catheter220may be a catheter used to measure blood pressure, as described in detail below. In an exemplary implementation, catheter220may be an arterial catheter that may be inserted in the wrist or foot of patient210. Catheter220may include a sensor used to measure pressure in the artery. Catheter220may also include a transducer to convert the measured pressure into electrical signals corresponding to the measured pressure and provide the electrical signals to monitoring device240.

Ventilator230may be any conventional mechanical ventilator used to assist patient210in breathing. In some implementations, ventilator230may provide data, such as respiratory rate information, to monitoring device240.

Monitoring device240may include a device used to continuously monitor various parameters associated with patient210, such as the respiratory variation of the pulse pressure. In an exemplary implementation, monitoring device240may receive data from catheter220and/or ventilator230and determine the respiratory variation of the pulse pressure. This metric may be used to indicate the preload state of patient210. The respiratory variation of the pulse pressure may be continuously updated to enable medical personnel to monitor the state of patient210in a real-time or near real-time manner. This information may then be used to determine, for example, whether to provide a fluid bolus to patient210. That is, the respiratory variation of the pulse pressure may function to indicate the condition of patient210with respect to the Starling curve (FIG. 1) and whether fluid administration would be beneficial or detrimental given the current condition of patient210.

The exemplary environment200illustrated inFIG. 2is provided for simplicity. It should be understood that a typical environment may include more or fewer devices than illustrated inFIG. 2. For example, catheter220is shown as a separate element from the other devices. In other implementations, catheter220and/or parts of catheter220(e.g., a transducer) may be part of monitoring device240. In addition, in some implementations, the functions described below as being performed by multiple devices in environment200may be performed by a single device. For example, in some implementations, the functions performed by ventilator230and monitoring device240may be combined into a single device. In addition, in an alternative implementation, ventilator230may not be used. That is, patient210may not be mechanically ventilated. In addition, in other implementations, catheter220may not be used. For example, a pulse oximeter may be placed on a finger of patient210to monitor the pulse of patient210instead of using catheter220.

FIG. 3illustrates an exemplary configuration of monitoring device240. Referring toFIG. 3, monitoring device240may include bus310, processor320, main memory330, read only memory (ROM)340, storage device350, input device360, output device370, and communication interface380. Bus310may include a path that permits communication among the elements of monitoring device240.

Processor320may include a processor, microprocessor, application specific integrated circuit (ASIC), field programmable gate array (FPGA) or processing logic that may interpret and execute instructions. Memory330may include a random access memory (RAM) or another type of dynamic storage device that may store information and instructions for execution by processor320. ROM340may include a ROM device or another type of static storage device that may store static information and instructions for use by processor320. Storage device350may include a magnetic and/or optical recording medium and its corresponding drive.

Input device360may include a mechanism that permits an operator to input information to monitoring device240, such as a keyboard, a mouse, a pen, voice recognition and/or biometric mechanisms, etc. Output device370may include a mechanism that outputs information to the operator, including a display, a printer, a speaker, etc. Communication interface380may include any transceiver-like mechanism that enables monitoring device240to communicate with other devices and/or systems. For example, communication interface380may include a modem or an Ethernet interface to a LAN. Alternatively, communication interface380may include other mechanisms for communicating via a network (not shown).

Monitoring device240may perform processing associated with monitoring patient210, as described in detail below. According to an exemplary implementation, monitoring device240may perform these operations in response to processor320executing sequences of instructions contained in a computer-readable medium, such as memory330. A computer-readable medium may be defined as a physical or logical memory device.

The software instructions may be read into memory330from another computer-readable medium, such as data storage device350, or from another device via communication interface380. The software instructions contained in memory330may cause processor320to perform processes that will be described later. Alternatively, hard-wired circuitry may be used in place of or in combination with software instructions to implement processes described herein. Thus, implementations described herein are not limited to any specific combination of hardware circuitry and software.

FIG. 4is a flow diagram illustrating exemplary processing associated with monitoring patient210. In this example, assume that patient210is connected to ventilator230to assist patient210's breathing. Catheter220may be also inserted into an artery of patient210to measure arterial blood pressure. For example, catheter220may be inserted into an artery located in a foot or wrist of patient210. Inserting catheter220into a wrist or foot of patient210, as opposed to inserting catheter220into a large artery, such as a femoral artery or axillary artery, enables catheter220to be used in a manner that is relatively non-invasive to patient210. Inserting catheter220into an artery in an extremity, such as the wrist or foot, also enables monitoring to be performed on a small child without shredding the vessel, which could cause the loss of a limb. In addition, inserting catheter220into the foot or wrist, as opposed to using a Swan-Ganz catheter that must float through the heart to obtain blood pressure measurements, is much safer to patient210, such as in situations where patient210may be in shock. Therefore, catheter220, consistent with aspects described herein, may be used to obtain blood pressure measurements for virtually any patient210(e.g., adult or pediatric), regardless of the physical condition/state of health of patient210. Catheter220, as described previously, may include a pressure sensor and/or a transducer that converts the pressure measurements into electrical signals that may be used by monitoring device240.

Assume that monitoring device240is coupled to catheter220and receives data from catheter220. Monitoring device240may then determine the arterial blood pressure (ABP) of patient210(act410). For example, catheter220may provide electrical signals to monitoring device240corresponding to the ABP of patient210. Processor320may sample the ABP at a frequency ranging from, for example, 50-100 times per second (e.g., 50-100 Hz). This sampling frequency satisfies the Nyquist sampling theorem with respect to the ABP of virtually any patient. Other sampling frequencies may alternatively be used. The sampled ABP information may be cached in memory330.FIG. 5illustrates an ABP waveform500of patient210provided via catheter220. As illustrated, waveform500shows that systolic and diastolic pressure varies over a number of cycles. This variation may be used to generate a pulse pressure value, as described in detail below.

Monitoring device240may also determine the heart rate of patient210(act420). In one implementation, the heart rate may be determined using an electrocardiogram, a pulse rate monitor or another monitoring device (not shown inFIG. 2). However, in instances in which such heart rate monitoring devices, or other devices from which the heart rate is provided, are not available or not usable due to the condition of patient210, monitoring device240may indirectly derive the heart rate using the ABP waveform (e.g., ABP waveform500). For example, processor320may perform a fast fourier transform (FFT) of the ABP waveform500over a window of, for example, 30 seconds. Processor320may then determine the heart rate as being equal to the frequency at the maximum amplitude of the FFT. In this manner, processor320may convert a time domain ABP waveform into a frequency domain waveform that is used to estimate the heart rate of patient210.

Processor320may also continuously update the heart rate calculation as the ABP waveform changes. For example, processor320may calculate the heart rate at least once every five seconds. It should be understood that other periods for updating the heart rate may alternatively be used. Monitoring device240may also pre-store information in ROM340indicating an allowable range for the heart rate, such as 40 beats per minute (bpm) to 240 bpm. If processor320determines that the heart rate of patient210is outside this or any other expected range, this may indicate a problem with patient210and/or indicate that the data is not reliable. In such cases, monitoring device240may output a visual and/or audible alarm via output device370.

Assume that processor320determines that the heart rate is within the allowable range. Monitoring device240may calculate the pulse pressure of patient210(act430). The pulse pressure is generally defined as the difference between the systolic and diastolic pressures. In an exemplary implementation, processor320may determine the pulse pressure by subtracting the minimum ABP from the maximum ABP over a period of time equal to two times the heart rate period. For example, if the heart rate is 60 bpm (i.e., the heart rate period is one second), processor320may subtract the minimum ABP from the maximum ABP over a period of two seconds (i.e., two times the heart rate period of one second).FIG. 5illustrates an exemplary window or period510of two seconds, with point520representing the minimum ABP and point530representing the maximum ABP over window/period510. In this case, processor320subtracts the pressure value at point520from the pressure value at point530to obtain the pulse pressure. Processor320may calculate the pulse pressure in this manner at least once every heart rate period. That is, in this example, the window for calculating the first pulse pressure may be a two second window510depicted inFIG. 5. The next period (i.e., heart rate period) for determining the pulse pressure may overlap with period510such that the pulse pressure is calculated at least once every heart rate period, which in this example is one second.

Monitoring device240may also determine the respiratory rate of patient210(act440). In an exemplary implementation, the respiratory rate (RR) may be calculated using the pulse pressure measurements. For example, processor320may track the pulse pressure over, for example, a 30 second window. Processor320may then perform an FFT of the pulse pressure waveform and determine the frequency of the pulse pressure waveform at the maximum amplitude of the FFT. This value may correspond to the respiratory rate of patient210.

In other instances, monitoring device240may determine the respiratory rate using information obtained from ventilator230. For example, in some instances, ventilator230may provide information indicating the mechanically assisted respiratory rate of patient210.

Processor320may also continuously update the respiratory rate calculation over time. For example, processor320may calculate respiratory rate at least once every five seconds. It should be understood that other periods for updating the respiratory rate may alternatively be used. Monitoring device240may also pre-store information in ROM340indicating an allowable range for the respiratory rate, such as 6 breaths per minute to 40 breaths per minute. If processor320determines that the respiratory rate is outside of the allowable range, this may indicate a problem with patient210and/or indicate that the data is not reliable. In such cases, monitoring device240may output a visual and/or audible alarm via output device370.

Monitoring device240may then calculate the respiratory variation of the pulse pressure (act450). For example, processor320may obtain the pulse pressure measurements made over a period of two times the respiratory rate period. For example, if the respiratory rate is 20 breaths per minute (i.e., respiratory rate period of three seconds), processor320may obtain the pulse pressure measurements over a period of six seconds (i.e., two times the three second respiratory rate period). Processor320may then subtract the minimum pulse pressure (PPmin) from the maximum pulse pressure (PPmax) over this period of time. This respiratory variation of pulse pressure (RVoPP) may also be calculated in a continuous manner at least once every 5 seconds. In this case, the RVoPP period for a subsequent period may overlap with the previous period over which the RVoPP calculation is made.

Monitoring device240may also calculate the mean pulse pressure (act450). For example, processor320may obtain the pulse pressure measurements made over a period of time equal to two times the respiratory rate and calculate the mean or average pulse pressure (MPP) over this time period. In one implementation, processor320may simply sum PPmaxand PPminover the period and divide this value by two to obtain the MPP. In each case, monitoring device240may calculate the MPP in a continuous manner at least once every 5 seconds. Other periods of time for calculating/updating the MPP may alternatively be used.

Monitoring device240may then determine the respiratory variation of the pulse pressure as a measure of the preload state of patient210(act460). For example, in one implementation, processor320may divide the respiratory variation of the pulse pressure by the mean pulse pressure (i.e., RVoPP/MPP) to generate a value that may be used to indicate a preload state of patient210. This value or metric may be expressed as a raw number and/or a percentage. In each case, the metric may correspond to the preload state of patient210.

For example, as described previously with respect to Starling curve100(FIG. 1), patients in a condition corresponding to position A will have a marked variation in stroke volume as a function of ventricular preload. Such patients will also have a corresponding variation in respiratory variation of pulse pressure. For example, a patient having a relatively high RVoPP/MPP value, such as greater than 0.13 or 13%, may correspond to a patient that is in a condition located near position A of the Starling curve inFIG. 1. Therefore, if monitoring device240determines that patient210has a RVoPP/MPP value that meets or exceeds a predetermined value (e.g., 13% in this example), this indicates that patient210may benefit by receiving fluid.

In other instances, if RVoPP/MPP determined at act460is less than a predetermined value (e.g., 13% in this example), this may indicate that patient210is in a condition corresponding to a location near position B of the Starling curve inFIG. 1. In this case, patient210may not benefit from receiving fluid. It should be understood that other threshold values associated with RVoPP/MPP may be used as an indication of a preload state of patient210.

In some implementations, monitoring device240may generate a graphical output for display via output device370. Such a display may include a Starling curve with an indication of where patient210falls with respect to the Starling curve. In an one implementation, the point at which patient210falls may be highlighted or otherwise indicated on the curve. In other instances, the raw number or percentage may be output for display via output device370. In each case, medical personnel may view output device370to determine the preload state of patient210.

Monitoring device240may continuously update the RVoPP/MPP value in real-time or near real-time. This updated RVoPP/MPP value may be output for display via output device370. The display may also display a history of values over a period of time either graphically on a graph, such as a Starling curve, or via text. In each case, performing a continuous updating of the metric that may be used to readily identify the current preload state of patient210enables medical personnel to quickly determine a course of action that is best suited for patient210.

In the implementation described above, arterial blood pressure information was provided to monitoring device240via catheter220. In other instances, as described briefly above, a pulse oximeter may be attached to a finger of patient210to provide pulse-related data from which a pulse pressure may be determined. For example, a pulse oximeter may be connected to a fingertip of patient210to monitor the oxygenation of a patient's blood. Based on the reading associated with the oxygenation of the blood, one of ordinary skill in the art would be able to derive pulse pressure. Respiratory variation of the pulse pressure and mean pulse pressure may then be determined in a manner similar to that described above. In this implementation, measurements made with respect to patient210may be done in a totally non-invasive manner via a pulse oximeter.

In each of the implementations described above, respiratory variation of the pulse pressure may be determined to obtain a metric used to estimate the preload state of patient210, regardless of the heart rate and respiratory rate of the particular patient210. For example, as described above, the pulse pressure is determined at the frequency of the heart rate and the pulse pressure is then analyzed for variability at the frequency of the respiratory rate, while satisfying the Nyquist sampling theorem. Using such parameters with respect to determining pulse pressure and variability of pulse pressure enables monitoring device240to determine a preload state of virtually all patients, including pediatric patients, having an extremely wide range of heart rates and/or respiratory rates.

CONCLUSION

Implementations described herein provide for monitoring respiratory variation of pulse pressure in a continuous manner. Advantageously, the monitoring may be performed in a minimally invasive or non-invasive manner, thereby allowing the monitoring to be performed in virtually any patient, regardless of age and/or condition.

For example, various features have been described above with respect to monitoring device240continuously generating a value that indicates a preload state of patient210. This information has been described as being generated as a function of time. In other instances, the respiratory variation of pulse pressure may be presented as a function of some other variable. For example, in one implementation in which patient210has a catheter in his/her neck that provides central venous pressure information, monitoring device240may map the respiratory variation of pulse pressure to the central venous pressure. This information may then be used to target a desired central venous pressure using fluid management. The respiratory variation of the pulse pressure may similarly be presented as a function of other parameters associated with the particular patient.

In addition, implementations described above mainly refer to obtaining arterial blood pressure information or pulse oximetry information to obtain a pulse pressure and pulse pressure variation information. In other implementations, any pulse-related information in which the strength of the pulse can be gauged and changes in the strength of the pulse determined over the respiratory cycle may be used.

Further, aspects have been mainly described herein with respect to providing an output (e.g., textual, graphical) that indicates a preload state. In other instances, the preload state may be correlated to an amount of fluid that may be beneficial to patient210. For example, in some implementations, monitoring device240may output parameters indicating how much fluid may be suitable for the patient. It should be understood that any such output from monitoring device240would be reviewed and verified by appropriate medical personnel.

In addition, while series of acts have been described with respect toFIG. 4, the order of the acts may be varied in other implementations. Moreover, non-dependent acts may be implemented in parallel.

Further, certain portions of the invention may be implemented as “logic” that performs one or more functions. This logic may include hardware, such as a processor, a microprocessor, an application specific integrated circuit, or a field programmable gate array, software, or a combination of hardware and software.