Hypotension prediction with adjustable hypotension threshold

Abstract

A hemodynamic monitoring system monitors arterial blood pressure of a patient and provides a warning to medical personnel of a predicted future hypotensive event of the patient. Sensed hemodynamic data representative of an arterial pressure waveform of the patient is received by a hemodynamic monitor. The received hemodynamic data is shifted based on a difference between a standard mean arterial pressure (MAP) threshold for hypotension and an adjusted MAP threshold for hypotension to produce adjusted hemodynamic data. A waveform analysis of the adjusted hemodynamic data is performed and a risk score representative of a probability of a future hypotensive event of the patient is determined based on the waveform analysis. In response to the risk score satisfying a predetermined risk criterion, an sensory alert is invoked to produce a sensory signal.

Description

TECHNICAL FIELD

[0001] The present disclosure relates generally to arterial blood pressure monitoring, and more particularly to hypotension prediction with adjustable hypotension threshold. BACKGROUND

[0002] Hypotension, or low blood pressure, can be a serious medical complication and even a harbinger of death for patients undergoing surgery and those in the intensive care unit (ICU) receiving treatment for acute or critical conditions. The danger associated with the occurrence of hypotension in a patient is due to the potential damage caused by hypotension itself and the many serious potential medical conditions that hypotension occurrence can mean.

[0003] Hypotension in a surgical or critical patient is a serious medical condition in itself. For example, in an operating room (OR) environment, hypotension during surgery is associated with increased mortality and organ damage. Even extremely low blood pressure of short duration during surgery is associated with acute kidney injury and myocardial damage. In critical patients, the in-hospital mortality rate can almost double for patients who experience hypotension after emergency intubation. For both surgical and critical patients, hypotension, if not corrected, impairs organ perfusion, leading to irreversible ischemic damage, neurological deficits, cardiomyopathy, and kidney injury.

[0004] In addition to posing a serious risk to surgical and critical patients in itself, hypotension can be a symptom of one or more other serious underlying medical conditions. Examples of potential conditions for which hypotension can be an acute symptom include sepsis, myocardial infarction, arrhythmia, pulmonary embolism, hemorrhage, dehydration, anaphylaxis, acute reaction to medication, hypovolemia, insufficient cardiac output, and vasodilatory shock. Because hypotension is associated with such a variety of serious medical conditions, hypotension is relatively common and is often viewed as one of the first signs of patient deterioration in the OR and ICU.

[0005] Routine patient monitoring for hypotension in OR and ICU environments can include continuous or periodic blood pressure measurements. However, such monitoring, whether continuous or periodic, typically provides only real-time assessment. Thus, hypotension in a surgical or critical patient is typically detected only after it has begun to occur, such that remedial measures and interventions are initiated only after the patient has entered a hypotensive state. Even relatively mild levels of hypotension can presage or contribute to cardiac arrest in patients with limited cardiac reserve, despite the fact that extreme hypotension can have potentially devastating medical consequences quite quickly, as noted above.

[0006] In view of the frequency with which hypotension occurrence is observed in OR and ICU environments, and due to the serious and sometimes immediate medical consequences that can result when hypotension occurs, there is a great need for a solution that enables future hypotension events to be predicted in advance of hypotension occurrence. SUMMARY

[0007] In one example, a method for monitoring arterial pressure of a patient and providing a warning to medical personnel of a predicted future hypotensive event of the patient includes receiving, by a hemodynamic monitor, sensed hemodynamic data representative of an arterial pressure waveform of the patient. The method further includes offsetting, by the hemodynamic monitor, the received hemodynamic data based on a difference between a standard mean arterial pressure (MAP) threshold for hypotension and an adjusted MAP threshold for hypotension to produce adjusted hemodynamic data. The method further includes performing, by the hemodynamic monitor, a waveform analysis of the adjusted hemodynamic data, determining, by the hemodynamic monitor, a risk score representative of a probability of a future hypotensive event of the patient based on the waveform analysis of the adjusted hemodynamic data, and invoking, by the hemodynamic monitor, a sensory alert to produce a sensory signal in response to the risk score satisfying a predetermined risk criterion.

[0008] In another example, a system for monitoring arterial pressure of a patient and providing a warning to medical personnel of a predicted future hypotensive event of the patient includes a hemodynamic sensor, a system memory, a user interface, and a hardware processor. The hemodynamic sensor produces hemodynamic data representative of an arterial pressure waveform of the patient. The system memory stores hypotension prediction software code including a prediction weighting module. The user interface includes a sensory alert that provides a sensory signal to warn the medical personnel of a predicted future hypotensive event prior to the patient entering a hypotensive state.

[0009] The hardware processor is configured to execute the hypotension prediction software code to offset the hemodynamic data representative of the arterial pressure waveform of the patient based on a difference between a standard mean arterial pressure (MAP) threshold for hypotension and an adjusted MAP threshold to produce adjusted hemodynamic data. The hardware processor is further configured to execute the hypotension prediction software code to perform the waveform analysis of the adjusted hemodynamic data, and determine a risk score representative of a probability of a future hypotensive event of the patient using the prediction weighting module and based on the waveform analysis of the adjusted hemodynamic data. The hardware processor is further configured to execute the hypotension prediction software code to invoke the sensory alert of the user interface in response to the risk score satisfying a predetermined risk criterion. BRIEF DESCRIPTION OF DRAWINGS

[0010] Figure 1 is a perspective view of an example hemodynamic monitor that determines a risk score representative of a probability of a future hypotensive event of a patient.

[0011] Figure 2 is a perspective view of an example minimally-invasive pressure sensor for sensing hemodynamic data indicative of arterial pressure of a patient.

[0012] Figure 3 is a perspective view of an example non-invasive sensor for sensing hemodynamic data indicative of arterial pressure of a patient.

[0013] Figure 4 is a block diagram of an example hemodynamic monitoring system illustrating determination of a risk score indicative of a probability of a future hypotension event of a patient based on hemodynamic data adjusted based on a difference between a standard MAP threshold for hypotension and an adjusted MAP threshold for hypotension.

[0014] Figure 5A is a plot illustrating an example trace of an arterial pressure waveform including an example marker corresponding to a probability of future hypotension of a patient.

[0015] Figure 5B is a plot illustrating an example trace of an adjusted arterial pressure waveform shifted based on a difference between a standard MAP threshold for hypotension and an adjusted MAP threshold for hypotension.

[0016] Figure 6 is a flowchart illustrating example operations of a hemodynamic monitoring system determining a risk score indicative of a probability of a future hypotension event using hemodynamic data adjusted based on a difference between a standard MAP threshold for hypotension and an adjusted MAP threshold for hypotension. DETAILED DESCRIPTION

[0017] As described herein, a hemodynamic monitoring system implements a predictive risk model that generates a risk score indicative of a probability of a future hypotension event of a patient. The risk score is determined based on a weighted combination of a plurality of hypotension analysis parameters that predict a future hypotension event. Risk coefficients that implement the weighting are selected based on a standard (or defined) mean arterial pressure (MAP) threshold for hypotension, such as a pressure of 65 millimeters of mercury (mmHg) or other defined pressure threshold. The selection of risk coefficients and / or hypotension analysis parameters can be implemented via training (e.g., offline training) of the predictive risk model using machine learning or other techniques to minimize a cost function indicative of error of the predictive risk model output to true values of a training subset defining hypotension according to the standard MAP threshold for hypotension.

[0018] According to the techniques of the present disclosure, a hemodynamic monitoring system can utilize an adjustable MAP threshold for hypotension to represent a modified hypotension pressure threshold. Rather than modifying a predictive risk model (via retraining or otherwise) to accommodate an adjustable (e.g., user-defined or otherwise adjusted) MAP threshold, the hemodynamic monitoring system adjusts hemodynamic data representing sensed arterial pressure waveforms of a patient. That is, rather than requiring retraining or other modification of a predictive risk model to determine new risk coefficients and / or hemodynamic analysis parameters based on a modified definition of hypotension (i.e., an adjusted MAP threshold), the hemodynamic monitoring system adjusts an input signal (i.e., sensed hemodynamic data representing arterial pressure waveforms of a patient) based on a difference between a standard MAP threshold and an adjusted MAP threshold. Waveform analysis is performed on the adjusted hemodynamic data to determine a risk score representing a probability of a future hypotension event.

[0019] Accordingly, a hemodynamic monitoring system implementing the techniques of the present disclosure can utilize an adjustable pressure threshold for hypotension without requiring retraining or other modification of a predictive risk model, thereby enabling real-time updating of a hypotension threshold during, for example, an operating room (OR), intensive care unit (ICU), or other patient care environment. Accordingly, the system can provide a risk score representing a probability of future hypotension of a patient to enable timely and effective intervention, while also leveraging the training and / or experience of medical personnel that can warrant the use of a modified hypotension threshold, thereby increasing the usability of the system by medical personnel of patient care.

[0020] Figure 1 is a perspective view of a hemodynamic monitor 10 that determines a risk score representing a probability of a future hypotension event of a patient. As shown in Figure 1 the hemodynamic monitor 10 includes a display 12 that, in examples, Figure 1 presents a graphical user interface that includes control elements (e.g., graphical control elements) that enable a user to interact with the hemodynamic monitor 10. The hemodynamic monitor 10 can also include a plurality of input and / or output (I / O) connectors configured for wired connection (e.g., electrical and / or communication connection) with one or more peripheral components, such as one or more hemodynamic sensors, as further described below. For example, as shown in Figure 1 the hemodynamic monitor 10 can include I / O connectors 14. While Figure 1The example illustration shows five individual I / O connectors 14; however, it should be understood that in other examples, the hemodynamic monitor 10 may include fewer than five or more I / O connectors. In other examples, the hemodynamic monitor 10 may not include I / O connectors 14 and may instead communicate wirelessly with various peripheral devices.

[0021] As further described below, the hemodynamic monitor 10 includes one or more processors and a computer-readable storage device storing hypotension prediction software code executable to generate a risk score representing the probability of future hypotension events in the patient. For example, the hemodynamic monitor 10 may receive sensed hemodynamic data representing the patient's arterial pressure waveform, such as via one or more hemodynamic sensors connected to the hemodynamic monitor 10 via I / O connector 14. The hemodynamic monitor 10 executes the hypotension prediction software code to obtain multiple hypotension analysis parameters using the received hemodynamic data, which may include one or more vital sign parameters characterizing the patient's vital sign data, and differential and combination parameters derived from the one or more vital sign parameters, as further described below. The hemodynamic monitor 10 also executes the hypotension prediction software code to apply multiple risk coefficients to the hypotension analysis parameters to generate a weighted combination, resulting in a risk score representing the probability of future hypotension events in the patient. As further described in detail below, the multiple risk coefficients may be determined based on a standard mean arterial pressure (MAP) threshold (such as 65 mmHg) or other defined pressure thresholds.

[0022] As described herein, the hemodynamic monitor 10 may also utilize an adjusted MAP threshold for hypotension, which represents the deviation from a standard MAP threshold, from which a coefficient used by the hypotension prediction software code is determined. For example, the hemodynamic monitor 10 may present a graphical control element (e.g., at a graphical user interface presented on display 12) that allows the user to input the adjusted MAP threshold for hypotension, but input received via physical controls (e.g., buttons, knobs, or other physical input controls) is also possible.

[0023] For example, such as Figure 1 As shown, the hemodynamic monitor 10 can present a graphical user interface on the display 12. The display 12 can be a liquid crystal display (LCD), a light-emitting diode (LED) display, an organic light-emitting diode (OLED) display, or other display devices suitable for providing information to the user in graphical form. In some examples, such as Figure 1In the example shown, display 12 can be a touch-sensitive and / or presence-sensitive display device configured to receive user input in the form of gestures, such as touch gestures, scroll gestures, zoom gestures, swipe gestures, or other gesture input. Hemodynamic monitor 10 presents a control element that enables a user to input an adjusted MAP threshold, such as an absolute pressure (e.g., MAP threshold), a deviation value (e.g., a deviation from a standard MAP threshold), or other indication of an adjusted MAP threshold that can be user-defined, such as defined by medical personnel, in some examples.

[0024] Hemodynamic monitor 10, in response to receiving the adjusted MAP threshold, offsets the hemodynamic data representing the arterial pressure waveform of the patient based on a difference between the standard MAP threshold for hypotension and the adjusted MAP threshold to produce adjusted hemodynamic data, as described further below. Hemodynamic monitor 10 executes hypotension prediction software code to determine a risk score representing a probability of a future hypotension event for the patient using risk coefficients determined based on the standard MAP threshold. Hemodynamic monitor 10 can invoke a sensory alarm, such as an audible alarm, a tactile alarm, or other sensory alarm, in response to determining that the risk score satisfies a predetermined risk criterion.

[0025] Accordingly, hemodynamic monitor 10 can provide a medical personnel with a warning of a predicted future hypotension event for the patient prior to the patient entering a hypotensive state. Moreover, no retraining or other modification of the hypotension prediction software code is required to determine new risk coefficients based on the adjusted MAP threshold, but rather hemodynamic monitor 10 can determine the risk score using risk coefficients determined based on the standard MAP threshold. Accordingly, the techniques of the present disclosure can increase the usability of hemodynamic monitor 10 by enabling dynamic adaptation to an adjusted MAP threshold that can be based on the training and expertise of medical personnel.

[0026] Figure 2 is a perspective view of a hemodynamic sensor 16 that can be attached to a patient for sensing hemodynamic data representing arterial pressure of the patient. Figure 2 The hemodynamic sensor 16 shown is one example of a minimally-invasive hemodynamic sensor that can be attached to a patient via, for example, a radial artery catheter inserted into an arm of the patient. In other examples, hemodynamic sensor 16 can be attached to a patient via a femoral artery catheter inserted into a leg of the patient.

[0027] As Figure 2As shown, the hemodynamic sensor 16 includes a housing 18, a fluid input port 20, a catheter-side fluid port 22, and an I / O cable 24. The fluid input port 20 is configured to be connected to a fluid source, such as a saline bag or other fluid input source, via tubing or other hydraulic connection. The catheter-side fluid port 22 is configured to be connected to a catheter (e.g., a radial artery catheter or a femoral artery catheter) inserted into a patient’s arm (i.e., a radial artery catheter) or a patient’s leg (i.e., a femoral artery catheter) via tubing or other hydraulic connection. The I / O cable 24 is configured to be connected to the hemodynamic monitor 10 via one or more of the I / O connectors 14 Figure 1 ) via, for example, one or more of the I / O connectors 14 Figure 1 ) via, for example, one or more of the I / O connectors 14

[0028] In operation, a fluid column (e.g., a saline solution) is introduced from a fluid source (e.g., a saline bag) through the hemodynamic sensor 16 via the fluid input port 20 toward the catheter-side fluid port 22 to the catheter inserted into the patient. Arterial pressure is transmitted through the fluid column to a pressure sensor located within the housing 16, which senses the pressure of the fluid column. The hemodynamic sensor 16 converts the sensed pressure of the fluid column into an electrical signal via the pressure transducer and outputs the corresponding electrical signal to the hemodynamic monitor 10 Figure 1 ) via the I / O cable 24. Thus, the hemodynamic sensor 16 transmits substantially continuous beat-by-beat monitoring of analog sensor data (or digital representations of analog sensor data) representative of the patient’s arterial pressure to the hemodynamic monitor 10 Figure 1 ) via the I / O cable 24. Thus, the hemodynamic sensor 16 transmits substantially continuous beat-by-beat monitoring of analog sensor data (or digital representations of analog sensor data) representative of the patient’s arterial pressure to the hemodynamic monitor 10

[0029] Figure 3 is a perspective view of a hemodynamic sensor 26 for sensing hemodynamic data representative of a patient’s arterial pressure. Figure 3 The hemodynamic sensor 26 shown is one example of a non-invasive hemodynamic sensor that can be attached to a patient via one or more finger cuffs to sense data representative of the patient’s arterial pressure. As shown, Figure 3 As shown, the hemodynamic sensor 26 includes an inflatable finger cuff 28 and a cardiac reference sensor 30. The inflatable finger cuff 28 includes an inflatable blood pressure bladder configured to inflate and deflate when controlled by a pressure controller (not shown) pneumatically connected to the inflatable finger cuff 28. The inflatable finger cuff 28 also includes an optical (e.g., infrared) emitter and optical receiver electrically connected to the cardiac reference sensor 30 to measure changing volume of an artery in the finger.

[0030] During operation, the pressure controller continuously adjusts the pressure within the finger cuff to maintain a constant volume (i.e., the unloaded volume of the artery) in the finger, as measured by the cardiac reference sensor 30 via the optical transmitter and optical receiver of the inflatable finger cuff 28. The pressure applied by the pressure controller to continuously maintain the unloaded volume represents the blood pressure in the finger and is transmitted by the pressure controller to the cardiac reference sensor 30. The cardiac reference sensor 30 converts the pressure signal representing the blood pressure in the finger into hemodynamic data representing the patient's arterial pressure waveform, which is transmitted via, for example, I / O connector 14 (…). Figure 1 Transmitted to hemodynamic monitor 10 ( Figure 1 Therefore, the hemodynamic sensor 26 transmits sensor data representing essentially continuous beat-by-beat monitoring of the patient's arterial pressure.

[0031] Figure 4 This is a block diagram of a hemodynamic monitoring system 32 that determines a risk score representing the probability of future hypotension events based on hemodynamic data adjusted based on the difference between a standard MAP threshold for hypotension and an adjusted MAP threshold. Figure 4 As shown, the hemodynamic monitoring system 32 includes a hemodynamic monitor 10 and a hemodynamic sensor 34. The hemodynamic monitoring system 32 can be implemented in patient care environments such as ICUs, ORs, or other patient care environments. Figure 4 As shown, the patient care environment may include a patient 36 and healthcare personnel 38 trained to utilize the hemodynamic monitoring system 32.

[0032] As shown above (refer to the reference) Figure 1 The described hemodynamic monitor 10 can be, for example, an integrated hardware unit including a system processor 40, system memory 42, display 12, analog-to-digital (ADC) converter 44, and digital-to-analog (DAC) converter 46. In other examples, any one or more components of the hemodynamic monitor 10 and / or the described functions can be distributed among multiple hardware units. For example, in some examples, the display 12 can be a separate display device that is remote from and operatively coupled to the hemodynamic monitor 10. Typically, although in Figure 4 The example is illustrated and described as an integrated hardware unit, but it should be understood that the hemodynamic monitor 10 may include any combination of devices and components that are electrically connected, communicatively connected, or otherwise operatively connected to perform the functions attributed to the hemodynamic monitor 10 herein.

[0033] like Figure 4As shown, system memory 42 stores hypotension prediction software code 48. Hypotension prediction software code 48 includes a prediction weighting module 50 and hypotension analysis parameters 52. Display 12 provides a user interface 54 that includes control elements 56 that enable a user to interact with hemodynamic monitor 10 and / or other components of hemodynamic monitoring system 32. As Figure 4 User interface 54 as shown also provides a sensory alert 58 to provide a medical professional with a warning of a predicted future hypotension event for patient 36, as further described below.

[0034] Hemodynamic sensor 34 can be attached to patient 36 to sense hemodynamic data representative of an arterial pressure waveform of patient 36. Hemodynamic sensor 34 is operably connected to hemodynamic monitor 10 (e.g., via a wired or wireless connection or both electrically and / or communicatively connected) to provide sensed hemodynamic data to hemodynamic monitor 10. In some examples, hemodynamic sensor 34 provides hemodynamic data representative of an arterial pressure waveform of patient 36 to hemodynamic monitor 10 as an analog signal that is converted to digital hemodynamic data representative of the arterial pressure waveform by ADC 44. In other examples, hemodynamic sensor 34 can provide sensed hemodynamic data to hemodynamic monitor 10 in digital form, in which case hemodynamic monitor 10 can not include or utilize ADC 44. In other examples, hemodynamic sensor 34 can provide hemodynamic data representative of an arterial pressure waveform of patient 36 to hemodynamic monitor 10 as an analog signal that is analyzed by hemodynamic monitor 10 in its analog form.

[0035] Hemodynamic sensor 34 can be a non-invasive or minimally-invasive sensor that is attached to patient 36. For example, hemodynamic sensor 34 can take the form of a minimally-invasive hemodynamic sensor 16 Figure 2 ), a non-invasive hemodynamic sensor 26 Figure 3 ), or other minimally-invasive or non-invasive hemodynamic sensor. In some examples, hemodynamic sensor 34 can be attached non-invasively at a limb of patient 36, such as a wrist, arm, finger, ankle, toe, or other limb of patient 36. Accordingly, hemodynamic sensor 34 can take the form of a small, lightweight, and comfortable hemodynamic sensor that is suitable for being worn by patient 36 for an extended period of time, such as for minutes or hours, to provide substantially continuous beat-to-beat monitoring of arterial pressure of patient 36.

[0036] In certain examples, the hemodynamic sensor 34 can be configured to sense arterial pressure of the patient 36 in a minimally invasive manner. For example, the hemodynamic sensor 34 can be attached to the patient 36 via a radial artery catheter inserted into an arm of the patient 36. In other examples, the hemodynamic sensor 34 can be attached to the patient 36 via a femoral artery catheter inserted into a leg of the patient 36. Such minimally invasive techniques can similarly enable the hemodynamic sensor 34 to provide substantially continuous beat-to-beat monitoring of arterial pressure of the patient 36 over an extended period of time, such as minutes or hours.

[0037] The system processor 40 is configured to execute hypotension prediction software code 48 that implements a prediction weighting module 50 with hypotension analysis parameters 52 to produce a risk score representative of a probability of a future hypotension event for the patient 36. Examples of the system processor 40 can include any one or more of a microprocessor, a controller, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other equivalent discrete or integrated logic circuitry.

[0038] The system memory 42 can be configured to store information within the hemodynamic monitor 10 during operation. In some examples, the system memory 42 is described as a computer-readable storage medium. In some examples, a computer-readable storage medium can include a non-transitory medium. The term “non-transitory” can indicate that the storage medium is not embodied in a carrier wave or a propagated signal. In certain examples, a non-transitory storage medium can store data that can, over time, change (e.g., in RAM or cache). The system memory 42 can include both volatile and non-volatile computer-readable storage media. Examples of volatile computer-readable storage media can include random access memory (RAM), dynamic random access memory (DRAM), static random access memory (SRAM), and other forms of volatile memory. Examples of non-volatile computer-readable storage media can include forms of persistent memory including, for example, magnetic hard disks, optical disks, flash memory, or forms of electrically programmable memory (EPROM) or electrically erasable and programmable (EEPROM) memory.

[0039] Display 12 can be a liquid crystal display (LCD), a light emitting diode (LED) display, an organic light emitting diode (OLED) display, or other display device suitable for providing information to a user in graphical form. User interface 54 can include graphical and / or physical control elements that enable user input to interact with hemodynamic monitor 10 and / or other components of hemodynamic monitoring system 32. In some examples, user interface 54 can take the form of a graphical user interface (GUI) that is presented at graphical control elements presented at a touch-sensitive and / or presence-sensitive display screen of, for example, display 12. In such examples, user input can be received in the form of gesture inputs, such as touch gestures, scroll gestures, zoom gestures, or other gesture inputs. In certain examples, user interface 54 can take the form of and / or include physical control elements, such as physical buttons, keys, knobs, or other physical control elements configured to receive user input to interact with components of hemodynamic monitoring system 32.

[0040] In operation, hemodynamic sensor 34 senses hemodynamic data representative of an arterial pressure waveform of patient 36. Hemodynamic sensor 34 provides the hemodynamic data to hemodynamic monitor 10 (e.g., as analog sensor data). ADC 44 converts the analog hemodynamic data to digital hemodynamic data representative of the arterial pressure waveform of the patient.

[0041] System processor 40 executes hypotension prediction software code 48 to determine a risk score representative of a probability of a future hypotension event of patient 36 using the received hemodynamic data. For example, system processor 40 can execute hypotension prediction software code 48 to obtain a plurality of hypotension analysis parameters 52 using the received hemodynamic data. Hypotension analysis parameters 52 can include one or more vital sign parameters characterizing vital sign data of patient 36, as well as differential and combined parameters derived from the one or more vital sign parameters, as further described below.

[0042] The prediction weighting module 50 of the hypotension prediction software code 48 determines a risk score corresponding to a probability of a future hypotension event for the patient 36 based on a weighted combination of the hypotension analysis parameters 52. That is, the prediction weighting module 50 applies a plurality of risk coefficients stored in the system memory 42 to the hypotension analysis parameters 52 to produce a weighted combination that results in the risk score. The risk coefficients can be determined via a training operation (e.g., offline training) using machine learning or other techniques to minimize a cost function representing an error of the risk score from true values of a training subset (e.g., a collection of data from a plurality of patients) defining hypotension according to a standard MAP threshold for hypotension. That is, the risk coefficients utilized by the prediction weighting module 50 can be selected via the training operation to minimize an error of the predicted risk score determined by the hypotension prediction software code 48 as a prediction of a future hypotension event. The error of the predicted risk score predicting a future hypotension event can be evaluated with respect to a positive training data subset and a negative training data subset defining the occurrence of hypotension with respect to the standard (e.g., defined) MAP threshold, such as 65 mmHg or other pressure threshold.

[0043] As described herein, the hemodynamic monitor 10 can receive an adjusted MAP threshold for hypotension, such as a user-defined MAP threshold, via the control element 56 of the user interface 54. The adjusted MAP threshold can represent a deviation from a standard MAP threshold by which the risk coefficients used by the prediction weighting module 50 are determined. The adjusted MAP threshold provided by, for example, the medical caregiver 38 can take the form of an absolute pressure (e.g., MAP threshold), a deviation value (e.g., a deviation from a standard MAP threshold), or other indication of the adjusted MAP threshold.

[0044] The hypotension prediction software code 48, in response to receiving the adjusted MAP threshold, shifts the hemodynamic data representing the arterial pressure waveform of the patient 36 based on a difference between the standard MAP threshold for hypotension and the adjusted MAP threshold that can be received via the user interface 54 to produce adjusted digital hemodynamic data. For example, the hypotension prediction software code 48 can add the difference between the standard MAP threshold and the adjusted MAP threshold to the received hemodynamic data representing the arterial pressure waveform of the patient 36. The system processor 40 executes the hypotension prediction software code 48 to determine the hypotension analysis parameters 52 based on the adjusted hemodynamic data and determine the predicted risk score as a weighted combination of the hypotension analysis parameters 52 using the risk coefficients determined based on the standard MAP threshold.

[0045] The system processor 40 executes the hypotension prediction software code 48 to invoke the sensory alert 58 via the user interface 54 in response to determining that the risk score satisfies the predetermined risk criteria, as further described below. For example, the hypotension prediction software code 48 can invoke the sensory alert 58 to warn of a predicted impending hypotension event, e.g., in one to five minutes in the future, or up to about thirty minutes in the future. The sensory alert 58 can be implemented as one or more of a visual alert, an audible alert, a tactile alert, or other type of sensory alert. For example, the sensory alert 58 can be invoked as any combination of a flashing and / or colored graphic shown by the user interface 54 on the display 12, a risk score display via the user interface 54 on the display 12, a warning sound such as an alarm or repeating tone, and a tactile alert configured to cause the hemodynamic monitor 10 to vibrate or otherwise deliver a physically perceptible impulse to the medical professional 38 or other user.

[0046] Accordingly, the hemodynamic monitor 10 provides the medical professional with a warning of a predicted future hypotension event for the patient 36, enabling timely and effective intervention to prevent the predicted future hypotension event. Moreover, rather than retraining the predictive risk model to determine new risk coefficients based on the adjusted MAP threshold, the hemodynamic monitor 10 implementing the techniques of the present disclosure offsets the sensed hemodynamic data received from the hemodynamic sensor 34 based on the difference between the standard MAP threshold and the adjusted MAP threshold. The hemodynamic monitor 10 utilizes the adjusted hemodynamic data to determine the risk score using unmodified risk coefficients, thereby enabling real-time updates to the MAP threshold defining hypotension by the medical professional. Accordingly, the techniques described herein increase the usability of the hemodynamic monitor 10 by enabling the hemodynamic monitor 10 to adapt to, e.g., user-defined changes that can be based on the training and expertise of the attending medical professional to predict future hypotension events for the patient 36.

[0047] Figure 5A and Figure 5B is a plot of example traces of an arterial pressure waveform prior to the offset ( Figure 5A ) and after the applied offset ( Figure 5B ). For purposes of clarity and ease of discussion, the following describes Figure 4 the hemodynamic sensing system 32 of FIGS. 1-2 together and with reference to Figure 5A and Figure 5B .

[0048] Figure 5Ais a graph illustrating an example trace of an arterial pressure waveform 60A corresponding to hemodynamic data sensed by the hemodynamic sensor 34 and received by the hemodynamic monitor 10. Figure 5B is a graph representing an example trace of an illustrated arterial pressure waveform 60B of the arterial pressure waveform 60A after an offset is applied by the hypotension prediction software code 48 based on a difference between the standard MAP threshold for hypotension and the adjusted MAP threshold for hypotension.

[0049] As shown in Figure 5A and Figure 5B in this example, the hypotension prediction software code 48 applies an offset of 5 mmHg to the arterial pressure waveform 60A to produce the adjusted arterial pressure waveform 60B. In Figure 5A and Figure 5B this example, the applied offset of 5 mmHg corresponds to a difference of 5 mmHg between the standard MAP threshold for hypotension and the adjusted MAP threshold for hypotension. That is, in Figure 5A and Figure 5B this example, the adjusted MAP threshold for hypotension is provided, for example, via the control element 56 of the user interface 54. The system processor 40 executes the hypotension prediction software code 48 to determine a difference between the standard MAP threshold (e.g., 65 mmHg) and the adjusted MAP threshold (e.g., 60 mmHg), which in this example corresponds to a difference of 5 mmHg, although other differences are possible (e.g., greater than 5 mmHg or less than 5 mmHg). The hypotension prediction software code 48 executed by the system processor 40 applies an offset to the hemodynamic waveform 60A to produce the adjusted hemodynamic waveform 60B, which represents the waveform 60A with the offset of 5 mmHg added consistently throughout the hemodynamic waveform 60A.

[0050] While Figure 5A and Figure 5B the example is described with respect to a positive offset (i.e., an offset of 5 mmHg) applied to the hemodynamic waveform 60A to produce the adjusted hemodynamic waveform 60B, it should be understood that a negative offset is also possible. For example, if the adjusted MAP threshold for hypotension is provided (e.g., by a user) that is greater than the standard MAP threshold for hypotension, then the offset applied is negative. Conversely, as described with respect to Figure 5A and Figure 5B if the adjusted MAP threshold for hypotension is provided (e.g., by a user) that is less than the standard MAP threshold for hypotension, then the offset applied is positive.

[0051] The system processor 40 executes the hypotension prediction software code 48 to determine the hypotension analysis parameters 52 based on the adjusted arterial pressure waveform 60B. The prediction weighting module 50 applies a risk factor determined based on a standard MAP threshold (e.g., 65 mmHg) to determine a risk score representing a probability of a future hypotension event for the patient 36.

[0052] As further shown in Figure 5B As further shown in Figure 5B The example markers 62, 64, 66, and 68 are illustrated as corresponding to the start of a heartbeat for the patient 36 (marker 62), the maximum systolic pressure marking the end of systolic upstroke (marker 64), the presence of a dicrotic notch marking the end of systolic decay (marker 66), and the diastole of the heartbeat (marker 68), respectively. In Figure 6 An example slope “m” of the adjusted arterial pressure waveform 60B is also shown in

[0053] Additional markers predicting future hypotension for the patient 36 can be extracted by the hypotension prediction software code 48 from the adjusted hemodynamic waveform 60B based on behavior of the adjusted hemodynamic waveform 60B in various intervals, such as in the interval from the maximum systolic pressure at marker 64 to the diastolic period at marker 66, and the interval from the start of the heartbeat at marker 62 to the diastolic period at marker 66. Behavior of the adjusted arterial pressure waveform 60B during the following intervals (1) systolic upstroke 62-64, 2) systolic decay 64-66, 3) systolic period 62-66, 4) diastolic period 66-68, 5) interval 64-68, and 6) heartbeat interval 62-68) can be determined by the hypotension prediction software code 48 by determining the area under the curve of the adjusted hemodynamic waveform 60B and the standard deviation of the adjusted hemodynamic waveform 60B in each of the intervals 1-6. The respective areas and standard deviations determined for the intervals 1-6 can be used as additional markers predicting future hypotension for the patient 36.

[0054] Accordingly, the hemodynamic monitor 10 implementing the techniques of the present disclosure can offset the received hemodynamic data sensed by the hemodynamic sensor 34 based on the difference between the standard MAP threshold for hypotension and the adjusted MAP threshold for hypotension to produce adjusted hemodynamic data. Rather than retraining or otherwise modifying the predictive model implemented by the hypotension prediction software code 48 to determine a modified risk coefficient based on the adjusted MAP threshold, the hemodynamic monitor 10 can offset the input signals (i.e., the hemodynamic data from the hemodynamic sensor 34) used with the unmodified risk coefficient based on the standard MAP threshold for hypotension. Accordingly, the hemodynamic monitor 10 can utilize the unmodified risk coefficient while accommodating a user-defined MAP threshold for hypotension to determine a risk score representing a probability of a future hypotension event for the patient 36.

[0055] Figure 4 is a flowchart illustrating example operations to determine a risk score representing a probability of a future hypotension event using hemodynamic data adjusted based on a difference between a standard MAP threshold for hypotension and an adjusted MAP threshold for hypotension. For purposes of clarity and ease of discussion, the example operations are described below in the context of the hemodynamic monitoring system 32 of Figure 6 The example operations are described below in the context of the hemodynamic monitoring system 32 of

[0056] The adjusted MAP threshold for hypotension is received by the hemodynamic monitor 10 (step 70). For example, the hemodynamic monitor 10 can receive the adjusted MAP threshold for hypotension provided by, for example, the medical caregiver 38 via the control element 56 of the user interface 54. The hemodynamic monitor 10 receives sensed hemodynamic data representing an arterial pressure waveform of the patient 36 (step 72). For example, the hemodynamic monitor 10 can receive an analog hemodynamic sensor signal representing an arterial pressure waveform of the patient 36 from the hemodynamic sensor 34.

[0057] The hemodynamic monitor 10 offsets the received hemodynamic data based on the difference between the standard MAP threshold for hypotension and the adjusted MAP threshold for hypotension to produce adjusted hemodynamic data (step 74). For example, the system processor 40 can execute the hypotension prediction software code 48 to determine the difference between the standard MAP threshold and the adjusted MAP threshold. The hypotension prediction software code 48 can offset the hemodynamic data received from the hemodynamic sensor 34 by adding the difference between the standard MAP threshold for hypotension and the adjusted MAP threshold to the received hemodynamic data. In some examples, the hypotension prediction software code 48 can add the difference between the standard MAP threshold for hypotension and the adjusted MAP threshold for hypotension according to the following equation:

[0058] f'(t) = f(t) + (0 - 0') (Equation 1)

[0059] where f'(t) is the adjusted hemodynamic data, f(t) is the received hemodynamic data, 0 is a standard MAP threshold for hypotension, and 0' is an adjusted MAP threshold for hypotension.

[0060] The system processor 40 of the hemodynamic monitor 10 executes the hypotension prediction software code 48 to perform a waveform analysis of the adjusted hemodynamic data (step 76). For example, the system processor 40 can execute the hypotension prediction software code 48 to perform a waveform analysis of the adjusted hemodynamic data to obtain hypotension analysis parameters 52 that predict future hypotension of the patient 36. The hypotension analysis parameters 52 can include one or more of vital sign parameters characterizing vital sign data of the patient 36, differential parameters derived from the vital sign parameters, and combination parameters representing combinations of one or more of the vital sign parameters and the differential parameters.

[0061] The vital sign parameters characterizing the vital sign data can include, for example, stroke volume, heart rate, respiration, myocardial contractility, mean arterial pressure, a measure of baroreflex sensitivity, a hemodynamic complexity measure, a frequency domain hemodynamic feature, or other vital sign parameters. The measure of baroreflex sensitivity quantifies the relationship between complementary physiological processes. For example, a decrease in blood pressure in a healthy patient is typically compensated by an increase in heart rate and / or an increase in peripheral resistance. The measure of baroreflex sensitivity, which can be included in the one or more vital sign parameters characterizing the vital sign data, corresponds to the degree to which the patient 36 responds appropriately to normal physiological changes.

[0062] The hemodynamic complexity measure quantifies an amount of regularity of the cardiac measurements over time, as well as an entropy, e.g., an unpredictability of fluctuations in the cardiac measurements over time. For example, unpredictable cardiac fluctuations are a normal phenomenon associated with health. Very low entropy, i.e., a high regularity of the cardiac measurements over time and a substantial absence of unpredictable fluctuations, can be an important warning sign of an impending hypotension event. The frequency domain hemodynamic feature quantifies various measures of cardiac performance as a function of frequency rather than time.

[0063] The hypotension prediction software code 48 can also determine derivative parameters based on one or more of the vital sign parameters characterizing the vital sign data of the patient 36. The hypotension prediction software code 48 can derive the derivative parameters from the one or more vital sign parameters by determining a change in the one or more vital sign parameters with respect to time, with respect to frequency, or with respect to other parameters from among the one or more vital sign parameters. Thus, each of the one or more vital sign parameters can yield one, two, or several derivative parameters included in the hypotension analysis parameters 52.

[0064] For example, a derivative parameter, stroke volume variation (SVV), can be derived based on a change in the parameter stroke volume (SV) as a function of time and / or as a function of sampling frequency. Similarly, a change in mean arterial pressure (AMAP) can be derived as a derivative parameter with respect to time and / or sampling frequency. As another example, a change in MAP with respect to time can be derived by subtracting an average value of MAP over the past five minutes, ten minutes, or other duration, from a current value of MAP.

[0065] The hypotension prediction software code 48 can use the one or more vital sign parameters and the derived derivative parameters to generate combined parameters included in the hypotension analysis parameters 52. For example, the one or more vital sign parameters and the derivative parameters can be used to generate the combined parameters by generating power combinations of a subset of the one or more vital sign parameters and the derivative parameters. For example, each combined parameter can be generated as a power combination of three parameters, which can be selected randomly or purposefully from among the one or more vital sign parameters and / or the derivative parameters characterizing the vital sign data. Each of the three parameters selected from among the one or more vital sign parameters and / or the derivative parameters can be raised to an exponential power, and can be multiplied or added to the other two parameters similarly raised to an exponential power. The exponential power to which each of the three parameters selected from among the one or more vital sign parameters and / or the derivative parameters is raised can be, but need not be, the same exponential power.

[0066] In some examples, the generation of the combined parameters can be performed using a predetermined and limited range of integer exponents. For example, the exponents used to generate the combined parameters can be integer powers selected from among negative two, negative one, zero, one, and two (-2, -1, 0, 1, 2). Thus, in some examples, each combined parameter can be expressed in accordance with the following equation:

[0067]

[0068] where Y is one of one or more vital sign parameters or one of the one or more differential parameters characterizing the vital sign data, n is any integer greater than 2, and each of a, b, and c can be any one of -2, -1, 0, 1, and 2. In some examples, Equation 2 above can apply to substantially all possible power combinations of the one or more vital sign parameters, differential parameters, and the one or more vital sign parameters, differential parameters are subject to the predetermined constraints described above (i.e., the value of n is any integer greater than 2, and each of a, b, and c is selected from the group consisting of -2, -1, 0, 1, and 2).

[0069] The hypotension analysis parameters 52 include one or more vital sign parameters, differential parameters, and combination parameters characterizing the vital sign data. Thus, the hypotension prediction software code 48 determines the hypotension analysis parameters 52 by identifying one or more vital sign parameters characterizing the vital sign data based on the adjusted hemodynamic data, obtaining differential parameters based on the one or more vital sign parameters, and generating combination parameters using the one or more vital sign parameters and the differential parameters.

[0070] A risk score representing a probability of a future hypotension event for the patient 36 is determined based on a waveform analysis of the adjusted hemodynamic data (step 78). For example, the system processor 40 can execute the hypotension prediction software code 48 to cause the prediction weighting module 50 to determine the risk score as a weighted combination of the hypotension analysis parameters 52. The prediction weighting module 50 can determine the weighted combination of the hypotension analysis parameters 52 including vital sign parameters characterizing the vital sign data for the patient 36, differential parameters derived from the vital sign parameters, and combination parameters by applying a plurality of risk coefficients to the hypotension analysis parameters 52. The plurality of risk coefficients applied by the prediction weighting module 50 can be determined (e.g., via offline training) with respect to a standard MAP threshold for hypotension. Thus, because the hypotension prediction software code 48 determines the risk score based on the hypotension analysis parameters 52 derived from the hemodynamic data sensed by the hemodynamic sensors attached to the patient 36, it should be noted that the hypotension prediction software code 48 determines the risk score for the patient 36 without needing direct comparison to hypotension in other patients and without needing direct reference to a hypotension database that can store information about hypotension in patients other than the patient 36.

[0071] In some examples, the prediction weighting module 50 determines the risk score representing a probability of a future hypotension event for the patient 36 according to the following equation:

[0072] R = 1 / (1 + e -A ) (Equation 3)

[0073] where R is a risk score, and A is represented as:

[0074]

[0075] where

[0076] vi = CWI, cardiac work indexed by body surface area of patient 36, included in low blood pressure analysis parameters;

[0077] v2 = MAPavg, mean average arterial pressure;

[0078] v3 = AMAPavg, change in mean average arterial pressure MAPavg when compared to initial state;

[0079] v4 = avgSysDec, average pressure at decay portion of systole;

[0080] v5 = ASys, change in systolic pressure when compared to initial value;

[0081] v6 = ppAreaNor, normalized area under adjusted arterial pressure waveform;

[0082] v7 = biasDia, bias of diastolic slope;

[0083] v8 = CW, cardiac work;

[0084] v9 = mapDnlocArea, area under adjusted arterial pressure waveform between first instance of MAP and dicrotic notch;

[0085] v 10 = SWcomb, stroke work;

[0086] v 11 = ppArea, area under adjusted arterial pressure waveform;

[0087] v 12 = decAreaNor, normalized area of decay phase;

[0088] v 13 = slopeSys, slope of systole;

[0089] v 14 = Cwk, Winkessel compliance;

[0090] v 15 = sys_rise_area_nor, normalized area under systolic rise phase;

[0091] v 16 = pulsepres, pulse pressure;

[0092] v 17 = avg sys, mean pressure in systole;

[0093] v 18 = dpdt2, maximum value of the second derivative of the adjusted arterial pressure waveform;

[0094] v 19 = dpdt, maximum value of the first derivative of the adjusted arterial pressure waveform; and

[0095] c0, c1,..., c 11 are risk coefficients determined with respect to a standard MAP threshold for hypotension.

[0096] In some examples, the risk score R can be expressed as a score as represented by Equation 3 above. In other examples, the risk score can be converted to a percentage risk score between 0% and 100%.

[0097] The hemodynamic monitor 10 invokes a sensory alert in response to the risk score satisfying a predetermined risk criterion (step 80). For example, the hypotension prediction software code 48 can invoke the sensory alert 58 of the user interface 54 in response to determining that the risk score R determined according to Equation 3 above satisfies a predetermined risk criterion. In some examples, the output of the hypotension prediction software code 48 can be processed using the DAC 46 to convert the digital signal to an analog signal for presentation at the display 12 via the user interface 54.

[0098] The predetermined risk criterion can be based on the value of the risk score, based on a trend of the risk score over a time interval, or both. For example, where the risk score is expressed as a percentage between 0 and 100, the hypotension prediction software code 48 can invoke the sensory alert 58 (e.g., immediately) in response to determining that the risk score exceeds a first predetermined threshold, such as 85%. In some examples, the hypotension prediction software code 48 can invoke the sensory alert 58 in response to determining that the risk score satisfies a second predetermined threshold over an entire first predetermined time period. In such examples, the second predetermined threshold can be lower than the first predetermined threshold.

[0099] Accordingly, the hypotension prediction software code 48 can invoke the sensory alert 58, e.g., immediately, in response to determining that the risk score exceeds a first predetermined threshold (e.g., 85%). The hypotension prediction software code 48 can also invoke the sensory alert 58 in response to determining that the risk score exceeds a second predetermined threshold (e.g., 80%) that is less than the first predetermined threshold for a first predetermined period of time (e.g., ten to thirty seconds) during which the risk score is continuously greater than the second predetermined threshold (80%) and less than the first predetermined threshold (e.g., 85%). In certain examples, the hypotension prediction software code 48 can invoke the sensory alert 58 in response to determining that the risk score is greater than a third predetermined threshold that is less than the second predetermined threshold for a second predetermined period of time (e.g., one or more minutes). In other examples, the hypotension prediction software code 48 can invoke the sensory alert 58 in response to determining that the risk score exceeds a fourth predetermined threshold (e.g., 75%) a threshold number of times (e.g., two, three, or other number of times) for a third predetermined period of time (e.g., one minute, two minutes, or other period of time).

[0100] Although not illustrated in the example operation of FIG. 6, in some examples, the hemodynamic monitor 10 can use the hypotension prediction software code 48 to identify the most likely cause of the predicted future hypotension event of the patient 36. For example, based on the identified markers, the hypotension prediction software code 48 can identify poor vascular tone, low blood volume, reduced cardiac contractility, or other most likely cause of the predicted future hypotension event of the patient 36. ​

[0101] In some examples, the hemodynamic monitor 10 can recommend a medical intervention for preventing the predicted future hypotension event of the patient 36, such as by identifying a recommended medical intervention that corresponds to the most likely cause of the predicted future hypotension event of the patient 36 that was identified. For example, with respect to the most likely cause of poor vascular tone, the hemodynamic monitor 10 can recommend a medical intervention of administering a vasoconstrictor. With respect to the most likely cause of low blood volume, for example, the hemodynamic monitor 10 can recommend a medical intervention of administering saline or whole blood.

[0102] Accordingly, the hemodynamic monitor 10 implementing the techniques of the present disclosure provides a risk score that predicts a future hypotension event of the patient 36, thereby enabling timely and effective intervention to prevent the hypotension event before the patient 36 enters a hypotensive state. Moreover, by enabling adjustment to the defined hypotension threshold without requiring retraining of the predictive risk model, the techniques described herein increase the usability of the hemodynamic monitoring system 32 to accommodate, e.g., the training and experience of medical personnel.

[0103] ​While the application has been described with reference to the example embodiments thereof, it is to be understood that the application is not limited to the example embodiments and that the application is intended to cover any alternatives, modifications, and equivalents that can be included within the scope of the application. Furthermore, although features of the application are described or illustrated as being part of the application, this is not a requirement and the features can be implemented as a stand-alone application or be part of a larger application.

Claims

1. A method for monitoring a patient's arterial pressure and providing medical personnel with a warning of predicted future hypotensive events in the patient, the method comprising: Sensed hemodynamic data representing the patient's arterial pressure waveform is received by a hemodynamic monitor; The hemodynamic monitor offsets the received hemodynamic data based on the difference between the standard mean arterial pressure threshold (MAP threshold) for low blood pressure and the adjusted MAP threshold for low blood pressure, which is different from the standard MAP threshold for low blood pressure. Waveform analysis of the adjusted hemodynamic data is performed by the hemodynamic monitor; The hemodynamic monitor determines a risk score representing the probability of future hypotensive events in the patient based on waveform analysis of the adjusted hemodynamic data; as well as The hemodynamic monitor triggers a sensory alarm to generate a sensory signal in response to the risk score meeting a predetermined risk criterion.

2. The method according to claim 1, The offset received hemodynamic data includes adding the difference between the standard MAP threshold for hypotension and the adjusted MAP threshold to the received hemodynamic data.

3. The method according to claim 2, Adding the difference between the standard MAP threshold for hypotension and the adjusted MAP threshold to the received hemodynamic data includes adding the difference between the standard MAP threshold for hypotension and the adjusted MAP threshold to the received hemodynamic data according to the following equation: in These are the adjusted hemodynamic data; in It is the received hemodynamic data; in θ It is the standard MAP threshold for the aforementioned hypotension; and in θ' It is the adjusted MAP threshold for the aforementioned low blood pressure.

4. The method according to claim 1, The waveform analysis performed on the adjusted hemodynamic data includes performing the waveform analysis on the adjusted hemodynamic data to determine multiple hypotension analysis parameters that predict the patient's future hypotension events.

5. The method according to claim 4, The risk score, which represents the probability of the patient's future hypotension event, includes applying multiple risk coefficients to the multiple hypotension analysis parameters to determine the risk score.

6. The method according to claim 5, The multiple risk coefficients are determined based on the standard MAP threshold.

7. The method according to claim 4, The waveform analysis performed on the adjusted hemodynamic data to determine the plurality of hypotension analysis parameters for predicting the patient's future hypotension events includes: Perform waveform analysis on the adjusted hemodynamic data to obtain vital sign parameters from the adjusted hemodynamic data; Based on one or more derived differential parameters from the vital sign parameters; as well as Generate combined parameters using one or more of the vital sign parameters and / or one or more of the differential parameters; The plurality of hypotension analysis parameters include one or more of the vital sign parameters, the differential parameters, and the combined parameters.

8. The method according to claim 7, The vital signs parameters mentioned therein include one or more of stroke volume, heart rate, respiration, and cardiac contractility.

9. The method according to claim 7, Deriving the differential parameter based on one or more of the vital sign parameters includes deriving the differential parameter to represent the variation of the one or more of the vital sign parameters relative to time, relative to frequency, or relative to other vital sign parameters.

10. The method according to claim 7, Generating the combined parameters includes generating the combined parameters as a combination of vital sign parameters, a combination of differential parameters, or a combination of at least one vital sign parameter and at least one differential parameter.

11. The method according to claim 1, further comprising: The adjusted MAP threshold for low blood pressure is received by the hemodynamic monitor via the user interface of the hemodynamic monitor.

12. A system for monitoring a patient's arterial pressure and providing warnings to healthcare personnel of predicted future hypotensive events, the system comprising: A hemodynamic sensor that generates hemodynamic data representing the patient's arterial pressure waveform; System memory, the system memory storing software code for predicting low blood pressure, including a prediction weighting module; The user interface includes a sensory alarm that provides sensory signals to warn the medical staff of a predicted future hypotensive event before the patient enters a hypotensive state. as well as A hardware processor, configured to execute the low blood pressure prediction software code to: The hemodynamic data representing the patient's arterial pressure waveform are offset based on the difference between a standard MAP threshold for low blood pressure and an adjusted MAP threshold to generate adjusted hemodynamic data. Perform waveform analysis on the adjusted hemodynamic data; The prediction weighting module is used, and the waveform analysis based on the adjusted hemodynamic data is used to determine a risk score representing the probability of future hypotensive events in the patient; as well as The sensory alarm is invoked in response to the risk score meeting a predetermined risk criterion.

13. The system according to claim 12, The hardware processor is configured to execute the hypotension prediction software code to offset the hemodynamic data by adding the difference between the standard MAP threshold for hypotension and the adjusted MAP threshold to the hemodynamic data.

14. The system according to claim 13, The hardware processor is configured to execute the hypotension prediction software code to add the difference between the standard MAP threshold and the adjusted MAP threshold for hypotension to the hemodynamic data according to the following equation: in These are the adjusted hemodynamic data; in These are the hemodynamic data; in θ It is the standard MAP threshold for the aforementioned hypotension; and in θ' It is the adjusted MAP threshold for the aforementioned low blood pressure.

15. The system according to claim 12, The hardware processor is configured to execute the hypotension prediction software code to perform waveform analysis of the adjusted hemodynamic data by determining multiple hypotension analysis parameters that predict the patient's future hypotension events.

16. The system according to claim 15, The hardware processor is configured to execute the hypotension prediction software code to apply multiple risk coefficients to the multiple hypotension analysis parameters using the prediction weighting module to determine the risk score representing the probability of the patient's future hypotension event.

17. The system according to claim 16, The multiple risk coefficients are determined based on the standard MAP threshold.

18. The system according to claim 15, The hardware processor is configured to execute the hypotension prediction software code to determine the plurality of hypotension analysis parameters that predict the patient's future hypotension events by executing the hypotension prediction software code. Perform waveform analysis on the adjusted hemodynamic data to obtain vital sign parameters from the adjusted hemodynamic data; Based on one or more derived differential parameters from the vital sign parameters; as well as Generate combined parameters using one or more of the vital sign parameters and / or one or more of the differential parameters; The plurality of hypotension analysis parameters include one or more of the vital sign parameters, the differential parameters, and the combined parameters.

19. The system according to claim 18, The vital signs parameters mentioned therein include one or more of stroke volume, heart rate, respiration, and cardiac contractility.

20. The system according to claim 18, The hardware processor is configured to execute the hypotension prediction software code to derive the differential parameters based on one or more of the vital signs parameters by deriving the differential parameters to represent the changes of one or more of the vital signs parameters relative to time, relative to frequency, or relative to other vital signs parameters.

21. The system according to claim 18, The hardware processor is configured to execute the hypotension prediction software code to generate the combined parameters by generating the combined parameters as a combination of vital sign parameters, a combination of differential parameters, or a combination of at least one vital sign parameter and at least one differential parameter.

22. The system according to claim 12, The hemodynamic sensor described therein is a non-invasive hemodynamic sensor that can be attached to the patient's limbs.

23. The system according to claim 12, The hemodynamic sensor mentioned above is a hemodynamic sensor based on a minimally invasive arterial catheter.

24. The system according to claim 12, The hemodynamic sensor generates the hemodynamic data as a simulated hemodynamic sensor signal representing the patient's arterial pressure waveform.

25. The system of claim 24, further comprising: An analog-to-digital converter that converts the analog hemodynamic sensor signal into digital hemodynamic data representing the patient's arterial pressure waveform.

26. The system according to claim 12, The user interface also includes a control element that allows the user to input an adjusted MAP threshold for low blood pressure.

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