Hypotension prediction using an adjustable hypotension threshold

Abstract

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

Description

[Technical Field]

[0001] The present disclosure relates generally to arterial pressure monitoring, and more particularly to predicting hypotension using an adjustable hypotension threshold. [Background technology]

[0002] Hypotension, or low blood pressure, can be a harbinger of serious medical complications and even death in patients undergoing surgery and in acutely or critically ill patients being treated in intensive care units (ICUs). The dangers associated with the occurrence of hypotension in patients arise from both the potential damage caused by the hypotension itself and the many serious underlying medical disorders that the occurrence of hypotension can signal.

[0003] By its very nature, hypotension in surgical or critically ill patients is a serious medical condition. For example, in the operating room (OR) setting, hypotension during surgery is associated with increased mortality and organ damage. Even short-term severe hypotension during surgery is associated with acute kidney injury and myocardial damage. Among critically ill patients, those who experience hypotension after emergency intubation can nearly double the in-hospital mortality rate. In surgical and critically ill patients alike, hypotension, if uncorrected, can compromise organ perfusion and lead to irreversible ischemic damage, neurological deficits, cardiomyopathy, and renal damage.

[0004] In addition to posing a significant risk in itself to surgical and critically ill patients, hypotension may be a symptom of one or more other serious underlying medical conditions. Examples of underlying conditions for which hypotension may be an acute symptom include sepsis, myocardial infarction, cardiac arrhythmia, pulmonary embolism, hemorrhage, dehydration, anaphylaxis, acute drug reactions, hypovolemia, cardiac output deficiency, and vasodilatory shock. Due to its association with such a variety of serious medical conditions, hypotension is relatively common and is often seen as one of the first signs of patient deterioration in the OR and ICU.

[0005] Conventional patient monitoring for hypotension in OR and ICU settings can include continuous or periodic blood pressure measurements. However, whether continuous or periodic, such monitoring generally provides only a real-time assessment. As a result, hypotension in surgical or critically ill patients is typically detected only after it begins to occur, and therapeutic measures and interventions are not initiated until the patient enters a hypotensive state. As noted above, extreme hypotension can have potentially catastrophic medical consequences very quickly, but even relatively mild levels of hypotension can herald or precipitate cardiac arrest in patients with limited cardiac reserve. Summary of the Invention [Problem to be solved by the invention]

[0006] Given the frequency with which hypotension is observed to occur in OR and ICU settings, and the serious and sometimes urgent medical consequences that can result when hypotension occurs, a solution that would allow prediction of future hypotensive events before they occur is highly desirable. [Means for solving the problem]

[0007] In one example, a method for monitoring a patient's arterial pressure and alerting medical personnel to a predicted future hypotensive event in the patient includes receiving, by a hemodynamic monitor, sensed hemodynamic data representing the patient's arterial pressure waveform. The method further includes offsetting, by the hemodynamic monitor, the received hemodynamic data based on a difference between a standard 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 representing a probability of a future hypotensive event in the patient based on the waveform analysis of the adjusted hemodynamic data, and invoking, by the hemodynamic monitor, a sensory alarm to produce a sensory signal in response to the risk score meeting a predetermined risk criterion.

[0008] In another example, a system for monitoring a patient's arterial pressure and alerting medical personnel of a predicted future hypotensive event includes a hemodynamic sensor, a system memory, a user interface, and a hardware processor. The hemodynamic sensor produces hemodynamic data representing the patient's arterial pressure waveform. The system memory stores hypotension prediction software code including a prediction weighting module. The user interface includes a sensory alarm that provides a sensory signal to alert medical personnel of a predicted future hypotensive event before the patient enters a hypotensive state. The hardware processor is configured to execute the hypotension prediction software code to offset hemodynamic data representing the patient's arterial pressure waveform 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 waveform analysis of the adjusted hemodynamic data and, using the prediction weighting module, determine a risk score representing the patient's probability of a future hypotensive event 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 a sensory alarm in the user interface in response to the risk score meeting a predetermined risk criterion. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 is a perspective view of an exemplary hemodynamic monitor that determines a risk score representing the probability of a future hypotensive event for a patient. [Figure 2] FIG. 1 is a perspective view of an exemplary minimally invasive pressure sensor for sensing hemodynamic data representative of a patient's arterial pressure. [Figure 3] FIG. 1 is a perspective view of an exemplary non-invasive sensor for sensing hemodynamic data representative of a patient's arterial blood pressure. [Figure 4]FIG. 1 is a block diagram illustrating an exemplary hemodynamic monitoring system that determines a risk score representing the probability of a future hypotensive event for a patient based on hemodynamic data adjusted based on the difference between a standard MAP threshold for hypotension and an adjusted MAP threshold. [Figure 5A] 1 is a graph showing an exemplary trace of an arterial pressure waveform including exemplary indicia corresponding to the probability of future hypotension in a patient. [Figure 5B] 10 is a graph showing an exemplary trace of an adjusted arterial pressure waveform offset based on the difference between a standard MAP threshold for hypotension and an adjusted MAP threshold for hypotension. [Figure 6] 1 is a flow chart illustrating an exemplary operation of a hemodynamic monitoring system for determining a risk score representing the probability of a future hypotensive event using adjusted hemodynamic data based on the difference between a standard MAP threshold for hypotension and an adjusted MAP threshold for hypotension. DETAILED DESCRIPTION OF THE INVENTION

[0010] As described herein, a hemodynamic monitoring system implements a predictive risk model that generates a risk score representing the probability of a future hypotensive event for a patient. The risk score is determined based on a weighted combination of multiple hypotensive profiling parameters that predict future hypotensive events. The risk coefficients that implement the weighting are selected based on a standard (or defined) mean arterial pressure (MAP) threshold for hypotension, such as 65 millimeters of mercury (mmHg) or other defined pressure threshold. The selection of the risk coefficients and / or hypotensive profiling parameters can be accomplished by training (e.g., offline training) the predictive risk model using machine learning or other techniques to minimize a cost function that represents the error of the predictive risk model output relative to the true value of a training subset that defines hypotension according to the standard MAP threshold for hypotension.

[0011] 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 (by retraining or otherwise) a predictive risk model to correspond to an adjustable (e.g., user-defined or otherwise adjustable) MAP threshold, the hypotension monitoring system adjusts hemodynamic data representing the patient's sensed arterial pressure waveform. That is, rather than requiring retraining or other modification of the predictive risk model to determine new risk coefficients and / or hemodynamic profiling parameters based on a modified definition of hypotension (i.e., the adjusted MAP threshold), the hemodynamic monitoring system adjusts an input signal (i.e., the sensed hemodynamic data representing the patient's arterial pressure waveform) based on the difference between the standard MAP threshold and the adjusted MAP threshold. Waveform analysis is performed on the adjusted hemodynamic data to determine a risk score representing the probability of a future hypotension event.

[0012] Thus, a hemodynamic monitoring system implementing the techniques of the present disclosure can utilize adjustable pressure thresholds for hypotension without requiring retraining or other modifications to predictive risk models, thereby enabling real-time updates to hypotension thresholds, for example, during surgery in an operating room (OR), intensive care unit (ICU), or other patient care environment. Thus, the system can provide a risk score representing a patient's probability of future hypotension to enable timely and effective intervention, while also leveraging the training and / or experience of medical personnel who may endorse the use of modified hypotension thresholds, thereby increasing the system's utility to medical personnel for patient care.

[0013] FIG. 1 is a perspective view of a hemodynamic monitor 10 that determines a risk score representing the probability of a future hypotensive event for a patient. As shown in FIG. 1, the hemodynamic monitor 10 includes a display 12 that presents a graphical user interface including control elements (e.g., graphical control elements) that enable user interaction with the hemodynamic monitor 10, in the example of FIG. 1. The hemodynamic monitor 10 may also include multiple 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 described further below. For example, as shown in FIG. 1, the hemodynamic monitor 10 may include an I / O connector 14. While the example of FIG. 1 shows five separate I / O connectors 14, it should be understood that in other examples, the hemodynamic monitor 10 may include fewer than five I / O connectors or more than five I / O connectors. In still other examples, the hemodynamic monitor 10 may not include an I / O connector 14, but rather may communicate wirelessly with various peripheral devices.

[0014] As described further below, hemodynamic monitor 10 includes one or more processors and computer-readable memory storing hypotension prediction software code executable to generate a risk score representing the probability of a future hypotension event for the patient. For example, hemodynamic monitor 10 can receive sensed hemodynamic data representing the patient's arterial pressure waveform via one or more hemodynamic sensors connected to hemodynamic monitor 10, e.g., via I / O connector 14. Hemodynamic monitor 10 executes the hypotension prediction software code to use the received hemodynamic data to obtain a plurality of hypotension profiling parameters, which may include one or more vital sign parameters characterizing the patient's vital sign data, as well as difference and combination parameters derived from the one or more vital sign parameters, as described further below. Hemodynamic monitor 10 further executes the hypotension prediction software code to apply a plurality of risk factors to the hypotension profiling parameters to generate a weighted combination that results in a risk score representing the patient's probability of a future hypotension event. As described in more detail below, multiple risk factors may be determined based on a standard mean arterial pressure (MAP) threshold, such as 65 mmHg or other defined pressure threshold.

[0015] As described herein, hemodynamic monitor 10 can further utilize an adjusted MAP threshold for hypotension, where the adjusted MAP threshold represents a deviation from a standard MAP threshold based on which the coefficients utilized by the hypotension prediction software code are determined. For example, hemodynamic monitor 10 can present a graphical control element (e.g., in a graphical user interface presented on display 12) that allows user input of an adjusted MAP threshold for hypotension, although input can be received via a physical control (e.g., a button, knob, or other physical input control).

[0016] For example, as shown in FIG. 1 , hemodynamic monitor 10 may present a graphical user interface on display 12. Display 12 may 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. In some examples, such as the example of FIG. 1 , display 12 may 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 gestural input. Hemodynamic monitor 10 presents control elements that allow user input of an adjusted MAP threshold, such as an absolute pressure (e.g., MAP threshold), a deviation value (e.g., deviation from a standard MAP threshold), or other indication of the adjusted MAP threshold, which in some examples may be user-defined, such as by a medical professional.

[0017] In response to receiving the adjusted MAP threshold, the hemodynamic monitor 10 offsets hemodynamic data representing the patient's arterial pressure waveform based on the difference between the standard MAP threshold for hypotension and the adjusted MAP threshold for hypotension to produce adjusted hemodynamic data, as described further below. The hemodynamic monitor 10 executes hypotension prediction software code to determine a risk score representing the probability of a future hypotensive event for the patient using a risk coefficient determined based on the standard MAP threshold. The hemodynamic monitor 10 can invoke a sensory alarm, such as an audible, tactile, or other sensory alarm, in response to determining that the risk score meets the predetermined risk criteria.

[0018] Thus, hemodynamic monitor 10 can alert medical personnel to a patient's predicted future hypotensive event before the patient enters a hypotensive state. Furthermore, rather than requiring retraining or other modifications to the hypotension prediction software code to determine a new risk factor based on an adjusted MAP threshold, hemodynamic monitor 10 can determine a risk score using a risk factor determined based on a standard MAP threshold. Thus, the techniques of the present disclosure enhance the utility of hemodynamic monitor 10 by enabling dynamic adaptation to an adjusted MAP threshold that can be based on medical personnel's training and expertise.

[0019] 2 is a perspective view of a hemodynamic sensor 16 that may be attached to a patient to sense hemodynamic data representative of the patient's arterial blood pressure. The hemodynamic sensor 16 shown in FIG. 2 is an example of a minimally invasive hemodynamic sensor that may be attached to the patient by, for example, a radial artery catheter inserted into the patient's arm. In another example, the hemodynamic sensor 16 may be attached to the patient by a femoral artery catheter inserted into the patient's leg.

[0020] As shown in FIG. 2 , hemodynamic sensor 16 includes housing 18, fluid input port 20, catheter fluid port 22, and I / O cable 24. 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. Catheter fluid port 22 is configured to be connected to a catheter (e.g., a radial artery catheter or a femoral artery catheter) via tubing or other hydraulic connection, the catheter being inserted into a patient's arm (i.e., a radial artery catheter) or the patient's leg (i.e., a femoral artery catheter). I / O cable 24 is configured to connect to hemodynamic monitor 10, for example, via one or more of I / O connectors 14 ( FIG. 1 ). Housing 18 of hemodynamic sensor 16 contains one or more pressure transducers, communication circuitry, processing circuitry, and corresponding electronic components for sensing fluid pressure corresponding to the patient's arterial pressure, which is transmitted to hemodynamic monitor 10 ( FIG. 1 ) via I / O cable 24.

[0021] In operation, a column of fluid (e.g., saline) is introduced from a fluid source (e.g., a saline bag) through fluid input port 20 through hemodynamic sensor 16 to catheter fluid port 22 toward a catheter inserted into a patient. Arterial pressure is transmitted through the fluid column to a pressure sensor located within housing 16, which senses the pressure of the fluid column. Hemodynamic sensor 16 converts the sensed pressure of the fluid column into an electrical signal via a pressure transducer and outputs a corresponding electrical signal to hemodynamic monitor 10 (FIG. 1) via I / O cable 24. Hemodynamic sensor 16 thus transmits analog sensor data (or a digital representation of the analog sensor data) to hemodynamic monitor 10 (FIG. 1) representing substantially continuous, beat-to-beat monitoring of the patient's arterial pressure.

[0022] FIG. 3 is a perspective view of a hemodynamic sensor 26 for sensing hemodynamic data representative of a patient's arterial blood pressure. The hemodynamic sensor 26 shown in FIG. 3 is an 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 blood pressure. As shown in FIG. 3, 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 as 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) transmitter and an optical receiver electrically connected to the cardiac reference sensor 30 to measure the changing volume of the finger's artery.

[0023] During operation, the pressure controller continuously adjusts the pressure in the finger cuff to maintain a constant arterial volume of the finger (i.e., the arterial unloaded volume), as measured by cardiac reference sensor 30 via the optical transmitter and receiver in inflatable finger cuff 28. The pressure applied by the pressure controller to continuously maintain the unloaded volume is representative of the finger's blood pressure and is communicated by the pressure controller to cardiac reference sensor 30. Cardiac reference sensor 30 converts the pressure signal representative of the finger's blood pressure into hemodynamic data representative of the patient's arterial pressure waveform, which is transmitted to hemodynamic monitor 10 (FIG. 1), for example, via I / O connector 14 (FIG. 1). Thus, hemodynamic sensor 26 transmits sensor data representative of substantially continuous, beat-to-beat monitoring of the patient's arterial pressure.

[0024] FIG. 4 is a block diagram of a hemodynamic monitoring system 32 that determines a risk score representing the probability of a future hypotensive event based on hemodynamic data adjusted based on the difference between a standard MAP threshold for hypotension and an adjusted MAP threshold. As shown in FIG. 4, the hemodynamic monitoring system 32 includes a hemodynamic monitor 10 and a hemodynamic sensor 34. The hemodynamic monitoring system 32 may be implemented in a patient care environment, such as an ICU, OR, or other patient care environment. As shown in FIG. 4, the patient care environment may include a patient 36 and a medical professional 38 trained to utilize the hemodynamic monitoring system 32.

[0025] As described above with respect to FIG. 1 , hemodynamic monitor 10 can be an integrated hardware unit including, for example, 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 of the components and / or described functionality of hemodynamic monitor 10 may be distributed among multiple hardware units. For example, in some examples, display 12 may be a separate display device that is separate from and operably coupled to hemodynamic monitor 10. Generally, while shown and described in the example of FIG. 4 as an integrated hardware unit, it should be understood that hemodynamic monitor 10 can include any combination of devices and components electrically, communicatively, or in some cases operably connected to perform the functions attributed to hemodynamic monitor 10 herein.

[0026] As shown in FIGURE 4, system memory 42 stores hypotension prediction software code 48. Hypotension prediction software code 48 includes a prediction weighting module 50 and hypotension profiling parameters 52. Display 12 provides a user interface 54, which includes control elements 56 that enable user interaction with hemodynamic monitor 10 and / or other components of hemodynamic monitoring system 32. As shown in FIGURE 4, user interface 54 also provides a sensory alarm 58 to alert medical personnel of a predicted future hypotension event in patient 36, as described further below.

[0027] The hemodynamic sensor 34 can be attached to the patient 36 to sense hemodynamic data representative of the patient's 36 arterial pressure waveform. The hemodynamic sensor 34 can be operatively connected (e.g., electrically and / or communicatively connected by a wired or wireless connection or both) to the hemodynamic monitor 10 to provide the sensed hemodynamic data to the hemodynamic monitor 10. In some examples, the hemodynamic sensor 34 provides the hemodynamic data representative of the patient's 36 arterial pressure waveform to the hemodynamic monitor 10 as an analog signal, which is converted by the ADC 44 into digital hemodynamic data representative of the arterial pressure waveform. In other examples, the hemodynamic sensor 34 can provide the sensed hemodynamic data to the hemodynamic monitor 10 in digital form, in which case the hemodynamic monitor 10 may not include or utilize an ADC 44. In yet another example, hemodynamic sensor 34 may provide hemodynamic data representing the arterial pressure waveform of patient 36 to hemodynamic monitor 10 as an analog signal, which is analyzed by hemodynamic monitor 10 in its analog form.

[0028] Hemodynamic sensor 34 may be a non-invasive or minimally invasive sensor attached to patient 36. For example, hemodynamic sensor 34 may take the form of minimally invasive hemodynamic sensor 16 (FIG. 2), non-invasive hemodynamic sensor 26 (FIG. 3), or other minimally invasive or non-invasive hemodynamic sensor. In some examples, hemodynamic sensor 34 may be non-invasively attached to an extremity of patient 36, such as the wrist, arm, finger, ankle, toe, or other extremity of patient 36. Thus, hemodynamic sensor 34 may take the form of a small, lightweight, and painless hemodynamic sensor suitable for extended wear by patient 36 to provide substantially continuous, beat-by-beat monitoring of the arterial blood pressure of patient 36 over an extended period of time, such as several minutes or hours.

[0029] In some examples, the hemodynamic sensor 34 may be configured to sense the arterial pressure of the patient 36 in a minimally invasive manner. For example, the hemodynamic sensor 34 may be attached to the patient 36 by a radial artery catheter inserted in the arm of the patient 36. In other examples, the hemodynamic sensor 34 may be attached to the patient 36 by a femoral artery catheter inserted in the leg of the patient 36. Such minimally invasive techniques may also enable the hemodynamic sensor 34 to provide substantially continuous, beat-by-beat monitoring of the arterial pressure of the patient 36 over extended periods of time, such as minutes or hours.

[0030] The system processor 40 is configured to execute hypotension prediction software code 48, which implements a predictive weighting module 50 that utilizes hypotension profiling parameters 52 to generate a risk score representing the probability of a future hypotension event for the patient 36. Examples of the system processor 40 may include 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.

[0031] The system memory 42 may be configured to store information within the hemodynamic monitor 10 during operation. The system memory 42, in some examples, is described as a computer-readable storage medium. In some examples, the computer-readable storage medium may include non-transitory media. The term "non-transitory" may indicate that the storage medium is not embodied in a carrier wave or propagated signal. In some examples, the non-transitory storage medium may store data that may change over time (e.g., in RAM or cache). The system memory 42 may include volatile and non-volatile computer-readable memory. Examples of volatile memory may 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 memory may include, for example, a magnetic hard disk, an optical disk, flash memory, or forms of electrically programmable memory (EPROM) or electrically erasable programmable memory (EEPROM).

[0032] Display 12 may 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 may 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 may take the form of a graphical user interface (GUI) that presents graphical control elements presented on a touch-sensitive and / or presence-sensitive display screen of display 12, for example. In such examples, user input may be received in the form of gesture input, such as a touch gesture, a scroll gesture, a zoom gesture, or other gesture input. In some examples, user interface 54 may 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.

[0033] In operation, hemodynamic sensor 34 senses hemodynamic data representing the arterial pressure waveform of patient 36. Hemodynamic sensor 34 provides the hemodynamic data (e.g., as analog sensor data) to hemodynamic monitor 10. ADC 44 converts the analog hemodynamic data into digital hemodynamic data representing the patient's arterial pressure waveform.

[0034] System processor 40 executes hypotension prediction software code 48 to use the received hemodynamic data to determine a risk score representing the probability of a future hypotension event for patient 36. For example, system processor 40 may execute hypotension prediction software code 48 to use the received hemodynamic data to obtain a plurality of hypotension profiling parameters 52. Hypotension profiling parameters 52 may include one or more vital sign parameters characterizing vital sign data of patient 36, as well as difference and combination parameters derived from the one or more vital sign parameters, as further described below.

[0035] The prediction weighting module 50 of the hypotension prediction software code 48 determines a risk score corresponding to the probability of a future hypotension event for the patient 36 based on a weighted combination of the hypotension profiling parameters 52. That is, the prediction weighting module 50 applies multiple risk factors stored in the system memory 42 to the hypotension profiling parameters 52 to generate the weighted combination that results in the risk score. The risk factors may be determined by a training operation (e.g., offline training) using machine learning or other techniques to minimize a cost function that represents the error of the risk score relative to a true value for a training subset (e.g., a collection of data from multiple patients) that defines hypotension according to a standard MAP threshold for hypotension. That is, the risk factors utilized by the prediction weighting module 50 may be selected by the training operation to minimize the 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 predictive risk score for predicting future hypotensive events can be evaluated for positive and negative training data subsets that define the occurrence of hypotension relative to a standard (e.g., predefined) MAP threshold, such as 65 mmHg or other pressure threshold.

[0036] As described herein, hemodynamic monitor 10 may receive an adjusted MAP threshold for hypotension, such as a user-defined MAP threshold, via control element 56 of user interface 54. The adjusted MAP threshold may represent a deviation from a standard MAP threshold, which determines the risk factor utilized by predictive weighting module 50. For example, the adjusted MAP threshold provided by healthcare professional 38 may take the form of an absolute pressure (e.g., MAP threshold), a deviation value (e.g., deviation from a standard MAP threshold), or other indication of the adjusted MAP threshold.

[0037] In response to receiving the adjusted MAP threshold, the hypotension prediction software code 48 offsets hemodynamic data representing the arterial pressure waveform of the patient 36 based on the difference between a standard MAP threshold for hypotension and the adjusted MAP threshold, which may be received, for example, via the user interface 54, to produce adjusted digital hemodynamic data. For example, the hypotension prediction software code 48 may 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 hypotension profiling parameters 52 based on the adjusted hemodynamic data and to determine a predicted risk score as a weighted combination of the hypotension profiling parameters 52 using risk factors determined based on the standard MAP threshold.

[0038] The system processor 40 executes the hypotension prediction software code 48 to invoke a sensory alarm 58 via the user interface 54 in response to determining that the risk score meets a predetermined risk criterion, as described further below. For example, the hypotension prediction software code 48 may invoke the sensory alarm 58 to warn of a hypotension event predicted to occur, for example, in one to five minutes, or up to about 30 minutes. The sensory alarm 58 may be implemented as one or more of a visual alarm, an audible alarm, a tactile alarm, or other type of sensory alarm. For example, the sensory alarm 58 may be invoked as any combination of flashing and / or colored graphics presented by the user interface 54 on the display 12, a display of a risk score by the user interface 54 on the display 12, an audible warning sound such as a siren or repeating tone, and a tactile alarm configured to vibrate the hemodynamic monitor 10 or, in some cases, deliver a perceptible physical impact to the healthcare professional 38 or other user.

[0039] Thus, the hemodynamic monitor 10 alerts medical personnel to predicted future hypotensive events in the patient 36, thereby enabling timely and effective intervention to prevent the predicted future hypotensive events. Furthermore, rather than requiring retraining of the predictive risk model to determine a new risk factor 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 a risk score using the unaltered risk factor, thereby enabling medical personnel to make real-time updates to the MAP threshold that defines hypotension. The techniques described herein therefore enhance the usefulness of the hemodynamic monitor 10 by enabling the hemodynamic monitor 10 to adapt to user-defined modifications, which may be based on the training and expertise of the attending medical personnel, for example, to predict future hypotensive events for the patient 36.

[0040] 5A and 5B are graphs illustrating exemplary traces of an arterial pressure waveform before (FIG. 5A) and after (FIG. 5B) application of an offset, where the offset is determined based on the difference between a standard MAP threshold for hypotension and an adjusted MAP threshold for hypotension. For clarity and ease of explanation, FIGS. 5A and 5B are described below in conjunction with and with reference to the hemodynamic sensing system 32 of FIG. 4.

[0041] Figure 5A is a graph showing an example tracing of an arterial pressure waveform 60A corresponding to hemodynamic data sensed by hemodynamic sensor 34 and received by hemodynamic monitor 10. Figure 5B is a graph showing an example tracing of an arterial pressure waveform 60B representing arterial pressure waveform 60A after application of an offset by hypotension prediction software code 48 based on the difference between a standard MAP threshold for hypotension and an adjusted MAP threshold for hypotension.

[0042] As shown in Figures 5A and 5B, in this example, the hypotension prediction software code 48 applies a 5 mmHg offset to the arterial pressure waveform 60A to produce an adjusted arterial pressure waveform 60B. In the example of Figures 5A and 5B, the applied 5 mmHg offset corresponds to a 5 mmHg difference between the standard MAP threshold for hypotension and the adjusted MAP threshold for hypotension. That is, in the example of Figures 5A and 5B, the adjusted MAP threshold for hypotension is provided, for example, via control element 56 of user interface 54. System processor 40 executes the blood pressure prediction software code 48 to determine the difference between the standard MAP threshold (e.g., 65 mmHg) and the adjusted MAP threshold (e.g., 60 mmHg), which corresponds to a 5 mmHg difference in this example, although other differences are possible (e.g., greater than 5 mmHg or less than 5 mmHg). Hypotension prediction software code 48 executed by system processor 40 applies an offset to hemodynamic waveform 60A to produce adjusted hemodynamic waveform 60B that represents waveform 60A with a 5 mmHg offset added consistently throughout hemodynamic waveform 60A.

[0043] 5A and 5B are described with respect to a positive offset (i.e., a 5 mmHg offset) applied to hemodynamic waveform 60A to produce adjusted hemodynamic waveform 60B, it should be understood that negative offsets are also contemplated. For example, if an adjusted MAP threshold for hypotension is provided (e.g., by a user) that is greater than a standard MAP threshold for hypotension, the offset applied is negative. Conversely, as described with respect to the example of FIGS. 5A and 5B, if an adjusted MAP threshold for hypotension is provided (e.g., by a user) that is less than a standard MAP threshold for hypotension, the offset applied is positive.

[0044] The system processor 40 executes the hypotension prediction software code 48 to determine hypotension profiling parameters 52 based on the adjusted arterial pressure waveform 60B. The prediction weighting module 50 applies risk factors determined based on a standard MAP threshold (e.g., 65 mmHg) to determine a risk score representing the probability of a future hypotension event for the patient 36.

[0045] As further shown in FIGURE 5B, the adjusted hemodynamic waveform 60B (e.g., represented by digital hemodynamic data) can include various indicia predictive of a future hypotensive event in patient 36. FIGURE 5B shows exemplary indicia 62, 64, 66, and 68, which correspond to the onset of patient 36's heartbeat (indicia 62), the peak systolic pressure indicating the end of systole (indicia 64), the presence of a dicrotic notch indicating the end of systole (indicia 66), and the diastolic phase of a heartbeat (indicia 68), respectively. FIGURE 5B also shows an exemplary slope "m" of adjusted arterial pressure waveform 60B, although it should be understood that slope "m" is merely representative of multiple slopes that may be determined at multiple locations along adjusted arterial pressure waveform 60B.

[0046] Additional indicia predictive of future hypotension for a patient can be extracted from the adjusted hemodynamic waveform 60B by the hypotension prediction software code 48 based on the behavior of the adjusted hemodynamic waveform 60B during various intervals, such as the interval from peak systolic pressure at indicia 64 to diastole at indicia 66, and the interval from the start of the heartbeat at indicia 62 to diastole at indicia 66. The behavior of the adjusted arterial pressure waveform 60B during the following intervals 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 during each of intervals 1 through 6. The respective areas and standard deviations determined for intervals 1 through 6 may serve as additional indices for predicting future hypotension for patient 36.

[0047] Thus, a hemodynamic monitor 10 implementing the techniques of the present disclosure can offset received hemodynamic data sensed by 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 possibly modifying the predictive model implemented by hypotension prediction software code 48 to determine a modified risk factor based on the adjusted MAP threshold, hemodynamic monitor 10 can offset the input signal (i.e., hemodynamic data received from hemodynamic sensor 34) for use with the unmodified risk factor determined based on the standard MAP threshold for hypotension. Thus, hemodynamic monitor 10 can utilize the unmodified risk factor to determine a risk score representing the probability of a future hypotensive event for patient 36 while accommodating a user-defined MAP threshold for hypotension.

[0048] 6 is a flow chart illustrating exemplary operations for determining a risk score representing the probability of a future hypotensive event using adjusted hemodynamic data based on the difference between a standard MAP threshold for hypotension and an adjusted MAP threshold for hypotension. For clarity and ease of explanation, the exemplary operations are described below within the context of the hemodynamic monitoring system 32 of FIG.

[0049] The adjusted MAP threshold for hypotension is received by hemodynamic monitor 10 (step 70). For example, hemodynamic monitor 10 may receive the adjusted MAP threshold for hypotension provided, for example, by healthcare professional 38 via control element 56 of user interface 54. Hemodynamic monitor 10 receives sensed hemodynamic data representing the arterial pressure waveform of patient 36 (step 72). For example, hemodynamic monitor 10 may receive an analog hemodynamic sensor signal from hemodynamic sensor 34 representing the arterial pressure waveform of patient 36.

[0050] 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 formula: f'(t)=f(t)+(θ-θ') (Equation 1) where f'(t) is the adjusted hemodynamic data, f(t) is the received hemodynamic data, θ is the standard MAP threshold for hypotension, and θ' is the adjusted MAP threshold for hypotension.

[0051] The system processor 40 of the hemodynamic monitor 10 executes the hypotension prediction software code 48 to perform waveform analysis of the adjusted hemodynamic data (step 76). For example, the system processor 40 may execute the hypotension prediction software code 48 to perform waveform analysis of the adjusted hemodynamic data to obtain hypotension profiling parameters 52 that predict future hypotension in the patient 36. The hypotension profiling parameters 52 may include one or more of vital sign parameters that characterize the vital sign data of the patient 36, difference parameters derived from the vital sign parameters, and combination parameters that represent one or more combinations of the vital sign parameters and the difference parameters.

[0052] The vital sign parameters characterizing the vital sign data may include, for example, stroke volume, heart rate, respiration, cardiac contractility, mean arterial pressure, baroreflex sensitivity measurements, hemodynamic complexity measurements, frequency-domain hemodynamic features, or other vital sign parameters. Baroreflex sensitivity measurements quantify the relationship between complementary physiological processes. For example, a decrease in blood pressure in a healthy patient is generally compensated for by an increase in heart rate and / or an increase in peripheral resistance. Baroreflex sensitivity measurements, which may be included in the one or more vital sign parameters characterizing the vital sign data, correspond to the degree to which the patient 36 is appropriately responding to normal physiological fluctuations.

[0053] Hemodynamic complexity measures quantify the amount of regularity in cardiac measurements over time, as well as entropy, e.g., the unpredictability of variability in cardiac measurements over time. For example, unpredictable cardiac variability is a normal phenomenon associated with health. Very low entropy, i.e., a high degree of regularity and the virtual absence of unpredictable variability in cardiac measurements over time, can be an important warning sign of an impending hypotensive event. Frequency-domain hemodynamic features quantify various measures of cardiac function as a function of frequency rather than time.

[0054] The hypotension prediction software code 48 can further determine difference parameters based on one or more vital sign parameters characterizing the vital sign data of the patient 36. The hypotension prediction software code 48 can derive difference parameters from the one or more vital sign parameters by determining the variability of 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. As a result, each of the one or more vital sign parameters can give rise to one, two, or several difference parameters that are included in the hypotension profiling parameters 52.

[0055] For example, a differential parameter stroke volume variation (SVV) can be derived based on the change in the parameter stroke volume (SV) over time and / or as a function of sampling frequency. Similarly, a change in mean arterial pressure (ΔMAP) can be derived as a differential parameter with respect to time and / or sampling frequency. As a further example, a change in MAP with respect to time can be derived by subtracting the average of MAP over the past 5 minutes, 10 minutes, or other duration from the current value of MAP.

[0056] The hypotension prediction software code 48 can use one or more vital sign parameters and the derived difference parameters to generate combination parameters included in the hypotension profiling parameters 52. For example, the combination parameters can be generated by using one or more vital sign parameters and difference parameters to generate power combinations of a subset of one or more vital sign parameters and difference parameters. For example, each of the combination parameters can be generated as a power combination of three parameters, where the three parameters can be randomly or purposefully selected from among one or more vital sign parameters and / or difference parameters characterizing the vital sign data. Each of the three parameters selected from among one or more vital sign parameters and / or difference parameters can be raised to an exponential power and multiplied with or added to two other parameters also raised to an exponential power. The exponential power to which each of the three parameters selected from one or more vital sign parameters and / or difference parameters is raised can be, but need not be, the same exponential power.

[0057] In some examples, the generation of the combination parameters may be performed using a predetermined, limited integer range of exponent powers. For example, the exponent powers used to generate the combination parameters may be integer powers selected from among negative 2, negative 1, zero, 1, and 2 (-2, -1, 0, 1, 2). Thus, each combination parameter, in some examples, may be expressed according to the following formula:

[0058]

number

[0059] where Y is one of one or more vital sign parameters or difference parameters characterizing the vital sign data, n is any integer greater than 2, and a, b, and c can each be one of −2, −1, 0, 1, and 2. In some examples, Equation 2 above can be applied to substantially all possible power combinations of one or more vital sign parameters, difference parameters, and one or more vital sign parameters with different difference parameters, subject to the predetermined constraints discussed above (i.e., the value of n is any integer greater than 2, and a, b, and c are each selected from the group consisting of −2, −1, 0, 1, and 2).

[0060] The hypotension profiling parameters 52 include one or more vital sign parameters characterizing the vital sign data, a difference parameter, and a combination parameter. Thus, the hypotension prediction software code 48 determines the hypotension profiling parameters 52 by identifying one or more vital sign parameters characterizing the vital sign data based on the adjusted hemodynamic data, obtaining a difference parameter based on the one or more vital sign parameters, and generating a combination parameter using one or more of the vital sign parameters and the difference parameter.

[0061] A risk score representing the probability of a future hypotensive event for the patient 36 is determined based on 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 a weighted combination risk score of the hypotension profiling parameters 52. The prediction weighting module 50 can determine the weighted combination of the hypotension profiling parameters 52 by applying multiple risk factors to the hypotension profiling parameters 52, including vital sign parameters characterizing the vital sign data of the patient 36, difference parameters derived from the vital sign parameters, and combination parameters. The multiple risk factors applied by the prediction weighting module 50 can be determined (e.g., by offline training) with respect to a standard MAP threshold for hypotension. Therefore, it should be noted that because the hypotension prediction software code 48 determines the risk score based on hypotension profiling parameters 52 derived from hemodynamic data sensed by hemodynamic sensors attached to the patient 36, the hypotension prediction software code 48 determines the risk score for the patient 36 without directly comparing it to hypotension in other patients and without directly referencing a hypotension database that may store information regarding hypotension in patients other than the patient 36.

[0062] In some examples, predictive weighting module 50 determines a risk score representing the probability of a future hypotensive event for patient 36 according to the following formula: R=1 / (1+e -A ) (Formula 3) where R is the risk score and A is

[0063]

number

[0064] It is expressed as: however, v1 = CWI, i.e., cardiac work indexed by the body surface area of ​​the patient 36; v2 = MAPavg, i.e., average mean arterial pressure; v3 = ΔMAPavg, i.e., the change in the average mean arterial pressure MAPavg compared to the initial state; v4=avgSysDec, i.e., the average pressure during the decay portion of systole, v5 = ΔSys, i.e., the change in systolic pressure compared to the initial value, v6=ppAreaNor, i.e., the normalized area under the adjusted arterial pressure waveform; v7=biasDia, i.e., bias of diastolic slope, v8=CW, i.e., cardiac work, v9 = mapDnlocArea, i.e., the area under the adjusted arterial pressure waveform between the first instance of MAP and the dicrotic notch; v 10 =SWcomb, i.e., work done per cycle, v 11 = ppArea, i.e., the area under the adjusted arterial pressure waveform, v 12 =decAreaNor, i.e., normalized area of ​​the decay phase, v 13 =slopeSys, i.e., systolic slope, v 14 = Cwk, i.e. Windkessel compliance, v 15 =sys_rise_area_nor, i.e., normalized area under the systolic rise phase, v 16 =pulsepres, i.e. pulse pressure, v 17 =avg_sys, i.e., average systolic pressure, v 18 = dpdt2, i.e., the maximum value of the second derivative of the adjusted arterial pressure waveform, v 19 = dpdt, i.e., the maximum value of the first derivative of the adjusted arterial pressure waveform, c0, c1, ......, c 11is the risk coefficient determined with respect to the standard MAP threshold for hypotension.

[0065] In some examples, the risk score R can be expressed as a fraction, as represented above in Equation 3. In other examples, the risk score can be converted to a percentage risk score between 0 percent and 100 percent.

[0066] Hemodynamic monitor 10 invokes a sensory alarm 80 in response to the risk score meeting a predetermined risk criterion. For example, hypotension prediction software code 48 may invoke sensory alarm 58 in user interface 54 in response to determining that risk score R, determined according to Equation 3 above, meets a predetermined risk criterion. In some examples, the output of hypotension prediction software code 48 may be processed using DAC 46 to convert a digital signal to an analog signal for presentation via user interface 54 on display 12.

[0067] The predetermined risk criteria can be based on the value of the risk score, the trend of the risk score over a time period, or both. For example, if the risk score is expressed as a percentage between 0 and 100, the hypotension prediction software code 48 can invoke the sensory alarm 58 (e.g., immediately) in response to determining that the risk score exceeds a first predetermined threshold, such as 85 percent. In some examples, the hypotension prediction software code 48 can invoke the sensory alarm 58 in response to determining that the risk score meets a second predetermined threshold throughout the first predetermined time period. In such examples, the second predetermined threshold can be lower than the first predetermined threshold.

[0068] Thus, the hypotension prediction software code 48 can invoke the sensory alarm 58, for example, immediately in response to determining that the risk score exceeds a first predetermined threshold (e.g., 85 percent). The hypotension prediction software code 48 can also invoke the sensory alarm 58 in response to determining that the risk score exceeds a second predetermined threshold (e.g., 80 percent) that is less than the first predetermined threshold for a first predetermined time period (e.g., 10-30 seconds), during which the risk score is continuously greater than the second predetermined threshold (80 percent) and less than the first predetermined threshold (e.g., 85 percent). In some examples, the hypotension prediction software code 48 can invoke the sensory alarm 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 time period (e.g., one minute or several minutes). In yet another example, the hypotension prediction software code 48 may invoke a sensory alarm 58 in response to determining that the risk score exceeds a fourth predetermined threshold (e.g., 75 percent) a threshold number of times (e.g., two, three, or other times) over a third predetermined time period (e.g., one minute, two minutes, or other time period).

[0069] 6 , in some examples, hemodynamic monitor 10 may use hypotension prediction software code 48 to identify the most likely cause of a predicted future hypotensive event in patient 36. For example, based on the identified indicia, hypotension prediction software code 48 may identify insufficient vascular tone, decreased blood volume, decreased cardiac contractility, or other most likely cause of a predicted future hypotensive event in patient 36.

[0070] In some examples, the hemodynamic monitor 10 can recommend a medical intervention to prevent a predicted future hypotensive event in the patient 36, such as by identifying a recommended medical intervention that corresponds to an identified most likely cause of the predicted future hypotensive event in the patient 36. For example, with respect to the most likely cause of insufficient vascular tone, the hemodynamic monitor 10 can recommend the medical intervention of administration of a vasoconstrictor. For example, with respect to the most likely cause of hypovolemia, the hemodynamic monitor 10 can recommend the medical intervention of administration of saline or whole blood.

[0071] Thus, a hemodynamic monitor 10 implementing the techniques of the present disclosure provides a risk score that predicts future hypotensive events for a patient 36, thereby enabling timely and effective intervention to prevent hypotensive events before the patient 36 enters a hypotensive state. Furthermore, by enabling adjustment of defined hypotensive thresholds without requiring retraining of the predictive risk model, the techniques described herein enhance the utility of the hemodynamic monitoring system 32 to accommodate, for example, the training and experience of medical personnel.

[0072] While the present invention has been described in terms of exemplary embodiments, those skilled in the art will recognize that various changes can be made in the elements thereof and equivalents can be substituted without departing from the scope of the invention. In addition, many modifications can be made to adapt a particular situation or material to the teachings of the invention without departing from essential scope thereof. Therefore, it is intended that the present invention not be limited to the particular embodiments disclosed, but will include all embodiments falling within the scope of the appended claims. [Explanation of symbols]

[0073] 10 Hemodynamic monitor 12 Display 14 Input and / or Output (I / O) Connectors 16 Hemodynamic Sensor 18 Housing 20 Fluid Inlet Port 22 Catheter fluid port 24 I / O cables 26 Hemodynamic Sensor 28 Inflatable Finger Cuff 30 Cardiac Reference Sensor 32 Hemodynamic Monitoring System 34 Hemodynamic Sensor 36 patients 38 Healthcare workers 40 System Processors 42 system memory 44 Analog-to-Digital (ADC) Converter 46 Digital-to-Analog (DAC) Converter 48 Hypotension Prediction Software Code 50 Prediction Weighting Module 52 Hypotension Profiling Parameters 54 User Interface 56 Control Elements 58 Sensory Alarm

Claims

1. 1. A method of operating a medical device performed by a hemodynamic monitoring device, comprising: receiving, by a processor, sensed hemodynamic data representative of the patient's arterial pressure waveform via a hemodynamic sensor; offsetting, by the processor, 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 that differs from the standard MAP threshold for hypotension to generate adjusted hemodynamic data; determining, by the processor, a plurality of hypotensive profiling parameters predictive of future hypotensive events for the patient by performing waveform analysis of the conditioned hemodynamic data; applying, by the processor, a plurality of risk factors to the plurality of hypotensive profiling parameters to determine a risk score representing a probability of a future hypotensive event for the patient based on the waveform analysis of the adjusted hemodynamic data, the plurality of risk factors being determined based on the standard MAP threshold; invoking, by the processor, a sensory alarm to generate a sensory signal in response to the risk score meeting a predetermined risk criterion; A method comprising:

2. offsetting 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. The method of claim 1.

3. adding the difference between the standard MAP threshold for hypotension and the adjusted MAP threshold to the received hemodynamic data comprises adding the difference between the standard MAP threshold for hypotension and the adjusted MAP threshold to the received hemodynamic data according to the following formula: f'(t)=f(t)+(θ-θ') where f'(t) is the adjusted hemodynamic data; f(t) is the received hemodynamic data; θ is the standard MAP threshold for hypotension; θ' is the adjusted MAP threshold for hypotension; The method of claim 2.

4. performing the waveform analysis of the conditioned hemodynamic data to determine the plurality of hypotensive profiling parameters predictive of the future hypotensive event for the patient, performing the waveform analysis of the adjusted hemodynamic data to obtain vital sign parameters from the adjusted hemodynamic data; deriving a difference parameter based on one or more of the vital sign parameters; generating a combination parameter using one or more of the vital sign parameters and / or one or more of the difference parameters; Including, the plurality of hypotension profiling parameters include one or more of the vital sign parameter, the difference parameter, and the combination parameter; The method of claim 1.

5. the vital sign parameters include one or more of stroke volume, heart rate, respiration, and cardiac contractility; The method of claim 4.

6. deriving the difference parameter based on one or more of the vital sign parameters comprises deriving the difference parameter to represent variation in the one or more of the vital sign parameters with respect to time, with respect to frequency, or with respect to other vital sign parameters; The method of claim 4.

7. generating the combined parameter includes generating the combined parameter as a combination of vital sign parameters, a combination of difference parameters, or a combination of at least one vital sign parameter and at least one difference parameter; The method of claim 4.

8. receiving, by the processor, the adjusted MAP threshold for hypotension via a user interface of the hemodynamic monitoring device. The method of claim 1 further comprising:

9. 1. A system for monitoring a patient's arterial blood pressure and alerting medical personnel of predicted future hypotensive events, comprising: a hemodynamic sensor that produces hemodynamic data representative of the patient's arterial pressure waveform; a system memory storing hypotension prediction software code including a prediction weighting module; a user interface including a sensory alarm that provides a sensory signal to alert the medical personnel of the predicted future hypotensive event before the patient enters a hypotensive state; A hardware processor, offsetting the hemodynamic data representing the arterial pressure waveform of the patient based on a difference between a hypotensive standard MAP threshold and an adjusted MAP threshold to produce adjusted hemodynamic data; performing a waveform analysis of the conditioned hemodynamic data by determining a plurality of hypotensive profiling parameters that are predictive of the future hypotensive event for the patient; determining a risk score representing the probability of a future hypotensive event for the patient based on the waveform analysis of the adjusted hemodynamic data using the prediction weighting module by applying a plurality of risk factors to the plurality of hypotensive profiling parameters, wherein the plurality of risk factors are determined based on the standard MAP threshold; Invoking the sensory alarm of the user interface in response to the risk score meeting a predetermined risk criterion; a hardware processor configured to execute the hypotension prediction software code; A system comprising:

10. 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 and the adjusted MAP threshold for hypotension to the hemodynamic data. The system of claim 9.

11. 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 formula: f'(t)=f(t)+(θ-θ') where f'(t) is the adjusted hemodynamic data; f(t) is the hemodynamic data; θ is the standard MAP threshold for hypotension; θ' is the adjusted MAP threshold for hypotension; The system of claim 10.

12. the hardware processor executing the hypotension prediction software code, performing the waveform analysis of the adjusted hemodynamic data to obtain vital sign parameters from the adjusted hemodynamic data; deriving a difference parameter based on one or more of the vital sign parameters; generating a combination parameter using one or more of said vital sign parameters and / or one or more of said difference parameters; and determining the plurality of hypotensive profiling parameters that predict the future hypotensive event for the patient by executing the hypotension prediction software code that performs: the plurality of hypotension profiling parameters include one or more of the vital sign parameter, the difference parameter, and the combination parameter; The system of claim 9.

13. the vital sign parameters include one or more of stroke volume, heart rate, respiration, and cardiac contractility; 13. The system of claim 12.

14. the hardware processor is configured to execute the hypotension prediction software code to derive the difference parameter based on one or more of the vital sign parameters by deriving the difference parameter to represent variation in one or more of the vital sign parameters with respect to time, with respect to frequency, or with respect to other vital sign parameters.

13. The system of claim 12.

15. the hardware processor is configured to execute the hypotension prediction software code to generate the combined parameter by generating the combined parameter as a combination of vital sign parameters, a combination of difference parameters, or a combination of at least one vital sign parameter and at least one difference parameter.

13. The system of claim 12.

16. the hemodynamic sensor is a non-invasive hemodynamic sensor attachable to an extremity of the patient; The system of claim 9.

17. the hemodynamic sensor is a minimally invasive arterial catheter-based hemodynamic sensor; The system of claim 9.

18. the hemodynamic sensor producing the hemodynamic data as an analog hemodynamic sensor signal representative of the arterial pressure waveform of the patient; The system of claim 9.

19. an analog-to-digital converter that converts the analog hemodynamic sensor signal into digital hemodynamic data representative of the arterial pressure waveform of the patient; 20. The system of claim 18, further comprising:

20. the user interface further includes a control element that allows user input of the adjusted MAP threshold for hypotension. The system of claim 9.

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