Abstract: A method and apparatus for determining a subject's autoregulation function state is provided. The method includes: continuously sensing a tissue region of a subject with a tissue oximeter to produce first signals representative of at least one tissue oxygenation parameter during a period of time; continuously measuring a blood pressure level of the subject during the period of time to produce second signals representative of the subject's blood pressure during the period of time; determining a presence of a confounding factor that affects the sensed tissue oxygenation parameter in a manner independent of an autoregulation function of the subject, the determination using the first signals; using the first and second signals to determine an autoregulation function state of the subject when the absence of the confounding factor is determined. The method may include determining an at least one of an LLA or a ULA of a subject's autoregulation function state.

Abstract: A method for determining a post-induction score that represents a prediction that a patient will experience a hypotensive event after beginning an administration of anesthesia is disclosed herein that includes receiving, by a hemodynamic monitor prior to the administration of anesthesia on the patient, sensed hemodynamic data representative of an arterial pressure waveform of the patient. The method further includes extracting, by the hemodynamic monitor, at least one waveform feature from the sensed hemodynamic data. Additionally, the method includes determining, by the hemodynamic monitor based on the at least one waveform feature, the post-induction score that represents the likelihood that the patient will experience a hypotensive event after beginning the administration of anesthesia. Finally, the post-induction score is displayed.

Abstract: A hemodynamic monitoring system monitors arterial blood pressure of a patient and provides a warning to medical personnel of a predicted future hypotension event of the patient. Waveform analysis is performed on sensed hemodynamic data representative of an arterial pressure waveform of the patient to determine a plurality of hypotension profiling parameters predictive of a future hypotension event for the patient. A set of transformed hypotension profiling parameters is generated based on the hypotension profiling parameters and mean and standard deviation values of the hypotension profiling parameters at a standard mean arterial pressure (MAP) threshold for hypotension and an adjusted MAP threshold for hypotension. A risk score representing a probability of a future hypotension event for the patient is determined based on the set of transformed hypotension profiling parameters. A sensory alarm is invoked to produce a sensory signal in response to the risk score satisfying a predetermined risk criterion.

Abstract: A hemodynamic monitoring system monitors arterial blood pressure of a patient and provides a warning to medical personnel of a predicted future hypotension event of the patient. Sensed hemodynamic data representative of an arterial pressure waveform of the patient are received by a hemodynamic monitor. The received hemodynamic data is offset, 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. Waveform analysis of the adjusted hemodynamic data is performed, and a risk score representing a probability of a future hypotension event for the patient is determined based on the waveform analysis. A sensory alarm is invoked to produce a sensory signal in response to the risk score satisfying a predetermined risk criterion.

Abstract: There are provided systems and methods for performing mean arterial pressure (MAP) derived prediction of future hypotension. Such a system includes a hardware unit including a hardware processor and a system memory, a hypotension prediction software code stored in the system memory, and a sensory alarm. The hardware processor is configured to execute the hypotension prediction software code to receive MAP data of the living subject, and to transform the MAP data to one or more parameters predictive of a future hypotension event of the living subject. The hardware processor is further configured to execute the hypotension prediction software code to determine a risk score of the living subject corresponding to the probability of the future hypotension event based on at least some of the one or more parameters, and to invoke the sensory alarm if the risk score of the living subject satisfies a predetermined risk criteria.

Abstract: A system for monitoring arterial pressure of a patient determines a score that is predictive of responsiveness of the patient to a therapy. Sensed hemodynamic data representative of an arterial pressure waveform of the patient are received by a hemodynamic monitor. Magnitude data and trend data are derived from the hemodynamic data. The score that is predictive of the responsiveness of the patient to the therapy is determined based on the magnitude data and the trend data of the hemodynamic parameter. A representation of the score is output.

Abstract: There are provided systems and methods for performing mean arterial pressure (MAP) derived prediction of future hypotension. Such a system includes a hardware unit including a hardware processor and a system memory, a hypotension prediction software code stored in the system memory, and a sensory alarm. The hardware processor is configured to execute the hypotension prediction software code to receive MAP data of the living subject, and to transform the MAP data to one or more parameters predictive of a future hypotension event of the living subject. The hardware processor is further configured to execute the hypotension prediction software code to determine a risk score of the living subject corresponding to the probability of the future hypotension event based on at least some of the one or more parameters, and to invoke the sensory alarm if the risk score of the living subject satisfies a predetermined risk criteria.

Abstract: A system disclosed herein includes a hardware processor and a predictive risk model training software code stored in a system memory. The hardware processor executes the software code to receive vital sign data of a population of subjects including positive and negative subjects with respect to a health state, to define data sets for use in training a predictive risk model, to transform the vital sign data to parameters characterizing the vital sign data, and to obtain differential parameters based on those parameters. The hardware processor executes the software code to further generate combinatorial parameters using the parameters and the differential parameters, to analyze the parameters, the differential parameters, and the combinatorial parameters to identify a reduced set of parameters correlated with the health state, to identify a predictive set of parameters enabling prediction of the health state for a living subject, and to compute predictive risk model coefficients.

Abstract: A system having a processor obtain a digital hemodynamic data from a hemodynamic sensor, obtain one or more vital sign parameters characterizing vital sign data from the digital hemodynamic data, derive differential parameters based on the one or more vital sign parameters, generate combinatorial parameters using the one or more vital sign parameters and the differential parameters, determine a risk score corresponding to a probability of a future hypotension event for the living subject based on a weighted combination of a plurality of hypotension profiling parameters including the one or more vital sign parameters characterizing vital sign data, the differential parameters and the combinatorial parameters, and invoke a sensory alarm if the risk score satisfies a predetermined risk criterion.

Abstract: A system having a processor obtain a digital hemodynamic data from a hemodynamic sensor, obtain one or more vital sign parameters characterizing vital sign data from the digital hemodynamic data, derive differential parameters based on the one or more vital sign parameters, generate combinatorial parameters using the one or more vital sign parameters and the differential parameters, determine a risk score corresponding to a probability of a future hypotension event for the living subject based on a weighted combination of a plurality of hypotension profiling parameters including the one or more vital sign parameters characterizing vital sign data, the differential parameters and the combinatorial parameters, and invoke a sensory alarm if the risk score satisfies a predetermined risk criterion.

Abstract: Embodiments of the disclosure are directed to methods, apparatuses, and computer program products for determining a hemodynamic parameter. An exemplary method comprises: receiving data associated with at least one heart beat; calculating a first standard deviation for at least a portion of the data; interpolating a second standard deviation for at least a second portion of the data; and determining the hemodynamic parameter based on the first standard deviation and the second standard deviation.

Abstract: A system for managing healthcare of a living subject includes a computing platform having a hardware processor, a system memory storing a software code, and a display. The hardware processor executes the software code to receive medical history data of the living subject including data entries corresponding to one or more physiological parameter(s), determine respective target range(s) for the physiological parameter(s) based on the medical history data, and store the custom target range(s) in a medical profile of the living subject. The hardware processor further executes the software code to receive sensing signals for the living subject from a device configured to monitor the physiological parameter(s), obtain, from the sensing signals, a present measurement of the physiological parameter(s), retrieve the custom target range(s) from the medical profile of the living subject, compare the present measurement(s) with the custom target range(s), and render the comparison on the display.

Abstract: A cardiac monitoring system includes a display, a blood pressure sensor configured to sense a blood pressure of an artery of a patient, an analog-to-digital converter (ADC) configured to convert a blood pressure signal from the blood pressure sensor to digital blood pressure data, a hardware processor, and a software code. The hardware processor executes the software code to identify cardiovascular metrics of the patient, including one or more of an aortic impedance and an aortic compliance of the patient, based on the blood pressure data, and to determine a stroke volume (SV) of the patient using a subset of the cardiovascular metrics including the aortic impedance and/or aortic compliance, as well as an additive factor. The additive factor is based on a meta-parameter including a weighted sum of combinatorial parameters, each combinatorial parameter including another subset of the cardiovascular metrics.

Abstract: There are provided systems and methods for performing mean arterial pressure (MAP) derived prediction of future hypotension. Such a system includes a hardware unit including a hardware processor and a system memory, a hypotension prediction software code stored in the system memory, and a sensory alarm. The hardware processor is configured to execute the hypotension prediction software code to receive MAP data of the living subject, and to transform the MAP data to one or more parameters predictive of a future hypotension event of the living subject. The hardware processor is further configured to execute the hypotension prediction software code to determine a risk score of the living subject corresponding to the probability of the future hypotension event based on at least some of the one or more parameters, and to invoke the sensory alarm if the risk score of the living subject satisfies a predetermined risk criteria.

Abstract: A system and method are disclosed for detecting a vasoactive agent in patient's bloodstream. In one embodiment, an input signal is received that is associated with arterial blood pressure. A change of an arterial blood pressure parameter over time is determined. A vasoactive agent is then automatically detected using the determined change. In another embodiment, a waveform associated with an arterial blood pressure signal can be received. A parameter associated with the received waveform is calculate. Then the calculated parameter can be used to determine the presence of a vasoactive agent. In yet another embodiment, detection of a vasoactive agent in any of the other embodiments can be used in a calculation of a hemodynamic parameter, such as cardiac output, stroke volume, systemic vascular resistance, stroke volume variation, cardiac index, stroke volume index, systemic vascular resistance index, vascular compliance, and vascular tone.

Abstract: A system disclosed herein includes a hardware processor and a predictive risk model training software code stored in a system memory. The hardware processor executes the software code to receive vital sign data of a population of subjects including positive and negative subjects with respect to a health state, to define data sets for use in training a predictive risk model, to transform the vital sign data to parameters characterizing the vital sign data, and to obtain differential parameters based on those parameters. The hardware processor executes the software code to further generate combinatorial parameters using the parameters and the differential parameters, to analyze the parameters, the differential parameters, and the combinatorial parameters to identify a reduced set of parameters correlated with the health state, to identify a predictive set of parameters enabling prediction of the health state for a living subject, and to compute predictive risk model coefficients.

Abstract: There are provided systems and methods for performing mean arterial pressure (MAP) derived prediction of future hypotension. Such a system includes a hardware unit including a hardware processor and a system memory, a hypotension prediction software code stored in the system memory, and a sensory alarm. The hardware processor is configured to execute the hypotension prediction software code to receive MAP data of the living subject, and to transform the MAP data to one or more parameters predictive of a future hypotension event of the living subject. The hardware processor is further configured to execute the hypotension prediction software code to determine a risk score of the living subject corresponding to the probability of the future hypotension event based on at least some of the one or more parameters, and to invoke the sensory alarm if the risk score of the living subject satisfies a predetermined risk criteria.

Abstract: The present application concerns detecting catheter proximity to a blood-vessel wall and blood-vessel wall artifacts associated therewith. In one embodiment, a light source, in a catheter, can be used to project light into the blood vessel. An intensity associated with at least one light wavelength that interacted with blood can be measured. Based on the measured intensity, a determination can be made regarding blood-vessel wall artifacts due to the catheter tip proximity to a blood-vessel wall. Feedback can be provided to the clinician in order to assist the clinician in adjusting the catheter to optimize signal quality and minimize artifacts due to the blood-vessel wall.

Abstract: Embodiments of the disclosure are directed to apparatuses, methods and computer program products for determining cardiac output. An exemplary method comprises: receiving blood pressure data; determining a standard deviation associated with the blood pressure data; determining a pulse rate associated with the blood pressure data; determining a compliance factor associated with the blood pressure data; determining a function associated with the blood pressure data; and determining the cardiac output based on the standard deviation, the pulse rate, the compliance, and the function.

Abstract: Embodiments of the disclosure are directed to methods, apparatuses, and computer program products for determining a hemodynamic parameter. An exemplary method comprises: receiving data associated with at least one heart beat; calculating a first standard deviation for at least a portion of the data; interpolating a second standard deviation for at least a second portion of the data; and determining the hemodynamic parameter based on the first standard deviation and the second standard deviation.