WO2009025667A1 - Détermination du débit cardiaque et de la pression ventriculaire gauche - Google Patents

Détermination du débit cardiaque et de la pression ventriculaire gauche Download PDF

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WO2009025667A1
WO2009025667A1 PCT/US2007/076351 US2007076351W WO2009025667A1 WO 2009025667 A1 WO2009025667 A1 WO 2009025667A1 US 2007076351 W US2007076351 W US 2007076351W WO 2009025667 A1 WO2009025667 A1 WO 2009025667A1
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waveform
proportional
sap
pap
value
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PCT/US2007/076351
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English (en)
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Richard Cohen
Ramakrishna Mukkamala
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Massachusetts Institute Of Technology
Michigan State University
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Priority to PCT/US2007/076351 priority Critical patent/WO2009025667A1/fr
Publication of WO2009025667A1 publication Critical patent/WO2009025667A1/fr

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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/026—Measuring blood flow
    • A61B5/029—Measuring or recording blood output from the heart, e.g. minute volume
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/02028—Determining haemodynamic parameters not otherwise provided for, e.g. cardiac contractility or left ventricular ejection fraction
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/026—Measuring blood flow
    • A61B5/0265—Measuring blood flow using electromagnetic means, e.g. electromagnetic flowmeter
    • A61B5/027—Measuring blood flow using electromagnetic means, e.g. electromagnetic flowmeter using catheters
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
    • A61B5/346—Analysis of electrocardiograms
    • A61B5/349—Detecting specific parameters of the electrocardiograph cycle
    • A61B5/352—Detecting R peaks, e.g. for synchronising diagnostic apparatus; Estimating R-R interval
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235—Details of waveform analysis
    • A61B5/7239—Details of waveform analysis using differentiation including higher order derivatives

Definitions

  • Cardiac output is the volume of blood ejected by the heart per unit time
  • left atrial pressure generally indicates the blood pressure attained in the left ventricle during the filling phase of the cardiac cycle.
  • CO and LAP are perhaps the two most important quantities to be able to monitor in critically ill patients, as they facilitate the diagnosis, monitoring, and treatment of various disease processes such as left ventricular failure, mitral valve disease, and shock of any cause [36]. For example, a decrease in CO while LAP is rising would indicate that the patient is in left ventricular failure, whereas a decrease in CO while LAP is falling would indicate that the patient might be going into hypovolemic shock.
  • Several methods are currently available for monitoring CO or LAP. While each of these methods can offer some advantages, as described below, all of the methods are limited in at least one clinically significant way.
  • PCWP Since PCWP is measured when flow has ceased through the branch, in theory, the PCWP should provide an estimate of LAP. However, the PCWP is not equal to LAP and is only an approximation [31 ,44]. In fact, as a result of a number of technical problems, in practice, the PCWP method frequently provides only a poor estimate of LAP. These problems include partial wedging and balloon over-inflation [38,53], dependence of the measurement on the wedge catheter position [27,33], and inter-clinician variability in interpreting the phasic PCWP measurement [37].
  • thermodilution and PCWP methods are only made every few hours.
  • Alternative methods for monitoring CO include the aortic flow probe, oxygen Fick, dye dilution, continuous thermodilution, Doppler ultrasound, and thoracic bioimpedance.
  • the aortic flow probe uses ultrasound transit-time (or electromagnetic) principles to measure instantaneous flow [17]. While this method is continuous and very accurate, it requires the placement of the flow probe directly around the aorta and is therefore much too invasive for most clinical applications.
  • the oxygen Fick method involves simultaneous measurement of central venous and arterial oxygen content of blood and measurement of ventilatory oxygen uptake [17]. Although this method is also highly regarded in terms of its accuracy, it is too cumbersome for frequent clinical application.
  • the dye dilution method involves the injection of a dye into the right atrium and serial measurement of the dye concentration in blood samples drawn from an arterial catheter [17].
  • the related thermodilution method is generally preferred over this method, because thermodilution requires only one catheter and is less affected by indicator recirculation.
  • the continuous thermodilution method involves automatic heating of blood in the right atrium via a thermal filament, measurement of the temperature changes downstream in the pulmonary artery, and computation of average flow via cross correlation and bolus thermodilution principles [17,76]. While this method does not require an operator, the temperature changes generated by the thermal filament must be small to avoid damaging tissue and blood [17].
  • thermodilution the signal to noise ratio of continuous thermodilution is small compared to standard thermodilution, which may render the continuous approach to be less accurate [78].
  • Doppler ultrasound methods generally measure the Doppler shift in the frequency of an ultrasound beam reflected from the flowing aortic blood [17]. These non-invasive methods are not commonly employed in critical care medicine, because they require expensive capital equipment and an expert operator to stabilize an external ultrasound transducer [40]. Thoracic bioimpedance involves measuring changes in the electrical impedance of the thorax during the cardiac cycle [17,40]. Although this method is non-invasive and continuous, it is too inaccurate for use in critically ill patients due to excessive lung fluids [H].
  • LAP left heart catheterization
  • physical examination the gold standard method permitting continuous and accurate monitoring of LAP [65].
  • this method is too invasive and risky for routine clinical application.
  • clinical and radiographic signs of congestion such as rales, third heart sound, prominent jugular vein, and interstitial and alveolar edema are utilized to obtain a qualitative indication of elevated LAP in patients typically with heart failure [9]. While this approach is simple and non-invasive, it is neither continuous nor has it been shown to be sensitive to at least changes in PCWP [9,16,69].
  • Doppler imaging methods e.g., color M-mode Doppler, tissue Doppler, pulsed Doppler
  • parameters such as transmitral and pulmonary venous velocity profiles are obtained to qualitatively monitor LAP changes or quantitatively monitor PCWP through empirical formulas [21,22,57].
  • these techniques may also be non-invasive, they are expensive, can only be used intermittently, and are not specific and may therefore be inaccurate [2,57 ,62].
  • RVP right ventricular pressure
  • this approach would permit continuous and automatic measurement of these two critically important hemodynamic variables with a level of invasiveness suitable for routine clinical use.
  • a continuous and automatic monitoring approach would be desirable for several reasons. Continuous monitoring of both CO and LAP would be a great advantage during fluid and pharmaceutical interventions, as the clinician would be able to assess the effects of the interventions and be quickly alerted to possible complications. Continuous monitoring would also provide an early indication of deleterious hemodynamic events induced by disease (e.g., hypovolemia via simultaneously decreasing CO and LAP).
  • automatic monitoring would save precious time in the busy intensive care unit (ICU) and operating room (OR) environments [17] and circumvent the clinically significant problems associated with implementing the standard measurement methods (see above).
  • Bourgeois et al acknowledged that exponential diastolic decays are obscured in peripheral SAP waveforms [5]. Moreover, after Engelberg et al suggested that the pulmonary arterial tree be represented by a Windkessel model in which the small pulmonary vascular resistance (PVR) is referenced to LAP (electrical analog in Figure 3) [18], Milnor et al attempted to fit an exponential function to each diastolic decay interval of PAP waveforms minus average LAP in man and reported that all of the waveforms were not adequate for doing so [51]. Subsequently, Tajimi et al reported that they were not able to identify a location in the canine or human pulmonary artery in which exponential diastolic pressure decays were consistently visible [71].
  • PVR small pulmonary vascular resistance
  • Mukkamala et al introduced a technique to monitor CO by analyzing a single arterial pressure waveform (measured at any site in the systemic or pulmonary arterial trees) over time scales greater than a cardiac cycle [54]. They evaluated their technique with respect to peripheral SAP waveforms in swine and their results showed excellent agreement with aortic flow probe measurements over a wide physiologic range [54]. While this technique may permit continuous and accurate monitoring of CO with a level of invasiveness suitable for routine clinical application, it does not provide a convenient means to monitor LAP. [0014] Some investigators have attempted to monitor LAP or PCWP by analysis of blood pressure waveforms.
  • a technique that accurately monitors both CO and LAP by analysis of a PAP waveform, a RVP waveform, or other circulatory signals.
  • Such a technique could be utilized, for example, to continuously monitor critically ill patients instrumented with pulmonary artery catheters and chronically monitor heart failure patients instrumented with implanted devices.
  • the present invention involves the mathematical analysis of the contour of a PAP waveform, a RVP waveform, or another circulatory signal in order to determine average LAP, average SVP, proportional CO, proportional PVR, proportional SVR, and/or other clinically important hemodynamic variables.
  • the methods of the invention may be employed to make individual measurements of average LAP, average SVP, proportional CO, proportional PVR, proportional SVR, and/or other clinically important hemodynamic variables at one or more time instances or may be employed for continuous monitoring of one or more of these variables.
  • the mathematical analysis of a circulatory contour is defined here to comprise an examination of the temporal variations in the signal.
  • the temporal variations in the signal can be examined within a single cardiac cycle, between different cardiac cycles, or both. Simply monitoring the signal at the same time instance relative to a physiologically significant event, such as the end of diastole or the end of systole, in multiple cycles does not constitute performing a mathematical analysis of a circulatory contour.
  • the above definition is intended to exclude trivial examinations of the temporal variations in the signal that solely provide an estimate of the time instance of such a physiologically significant event (e.g., zero temporal derivative of the signal).
  • monitoring LAP via the end-diastolic PAP does not constitute a mathematical analysis of a circulatory contour even if the time instance of the end of diastole is determined via the zero temporal derivative of the PAP waveform (i.e., the time point at which the derivative of the PAP waveform is zero), since in effect this examination indicates PAP at particular instances of time.
  • an examination of the temporal variations in the signal involves the analysis of at least two time instances of the signal within a single cardiac cycle or at least two time instances of the signal within at least two cardiac cycles.
  • an examination of the temporal variations in the signal involves the analysis of an interval of the signal within a cardiac cycle (e.g., fraction of the diastolic interval greater than 25%) or encompassing multiple cardiac cycles (e.g., at least 30 cardiac cycles).
  • an examination of the temporal variations in the signal involves the analysis of an interval of the signal within individual cardiac cycles (e.g., systolic ejection interval) over a period encompassing multiple cardiac cycles (e.g., at least 30 cardiac cycles).
  • the average values for hemodynamic variables computed as described herein may be averages over a single beat or over multiple beats.
  • the mathematical analysis of a circulatory contour involves the use of the Windkessel model of Figure 3 to represent the slow dynamical properties of the pulmonary arterial tree.
  • proportional CO, average LAP, and other hemodynamic variables are determined by mathematical analysis of one or more individual diastolic decay interval(s) of a PAP waveform.
  • a set of basis functions one or more of which may include a constant term or may be a constant term, are fitted to each diastolic decay interval of PAP to respectively determine the dynamical properties of the pulmonary arterial tree and the average LAP.
  • Any basis functions known in the art may be employed. For example, real exponentials, complex exponentials, and/or polynomials (e.g., over a specific time interval) can be used.
  • complex exponential functions and a constant term are fitted to each diastolic decay interval of PAP to respectively determine the dynamical properties of the pulmonary arterial tree and the average LAP ( Figure 4).
  • Any number of complex exponential functions may be utilized in the fitting procedure to account for wave, inertial, and Windkessel effects in the pulmonary arterial tree.
  • the fitting procedure may be performed using any method known in the art and applied to, for example, the entire PAP downstroke (i.e., from maximum to minimum pressure; Figure 4).
  • the Windkessel time constant ⁇ is determined by, for example, extrapolating the computed exponential functions to low-pressure values and fitting a mono-exponential function to the extrapolated pressure values for which the faster wave and inertial effects have dissipated or vanished (Figure 4).
  • the average LAP is determined by, for example, computing the mean value of the resulting constant term (i.e., the constant term that the mono-exponential function approaches asymptotically) over any number of beats, while proportional CO is determined, for example, by computing the mean value of the resulting PAP-LAP (i.e., the mean value resulting from subtracting the LAP from PAP) over any number of beats and dividing this quantity by the mean value of the corresponding ⁇ .
  • the set of basis functions is a set of decaying polynomial functions, at least one of which is or includes a constant term.
  • the polynomials may be extrapolated to low pressure values, and a single exponential can then be fitted to the low pressure values to determine the time constant.
  • the basis functions can be extrapolated to low pressure values, and the time constant may be measured from the extrapolated pressure values by any other method known in the art (e.g., the time duration required for the extrapolated pressure to drop by a predetermined amount, such as by a factor of e "1 (36.79%). It will be appreciated that other methods for determining average LAP from the unknown constant, e.g., without performing extrapolation, may also be used.
  • proportional CO, average LAP, and/or other hemodynamic variables are determined by mathematical analysis of all temporal variations in a PAP waveform including those occurring over time scales greater than a cardiac cycle in which the confounding effects of wave and inertial phenomena are attenuated [55].
  • a segment of a PAP waveform of duration greater than a cardiac cycle e.g., ranging from 30 seconds to ten-minutes
  • the cardiac contractions signal may be established from the PAP waveform and possibly other physiologic signals by, for example, forming an impulse train in which each impulse is located at the onset of each cardiac contraction and has area equal to an arbitrary constant, the ensuing pulse pressure (x(t) in Figure 5), or any other value based on the PAP pulse ⁇ e.g., the ensuing pulse pressure determined after lowpass filtering the PAP waveform to attenuate the wave and inertial effects or the value of PAP at any defined time instance in the cardiac cycle relative to the onset of a cardiac contraction with or without respect to the value of PAP at the cardiac contraction onset).
  • the unknown constant term and impulse response are determined so as to permit the best fit of the PAP waveform segment according to any of the methods known in the art.
  • the process of determining the unknown constant term and impulse response that provide the best fit, or an acceptable fit, to a waveform or portion thereof is referred to as "fitting" herein.
  • the resulting pulmonary arterial tree impulse response is defined to represent the PAP-LAP response to a single, solitary cardiac contraction (h(t) in Figure 5).
  • the Windkessel time constant ⁇ of the pulmonary arterial tree is then determined from this impulse response by fitting an exponential to its tail end once the faster wave and inertial effects have vanished (h(t) in Figure 5).
  • proportional CO is determined as the difference between the mean value of the analyzed PAP waveform segment and average LAP (i.e., the resulting constant term) divided by the resulting ⁇ .
  • proportional CO may be determined as the product of the peak value of the pulmonary arterial tree impulse response and the average heart rate.
  • the above aspects of the present invention may be utilized, for example, in patients instrumented with pulmonary artery catheters in ICUs, ORs, and recovery rooms.
  • the continuous, proportional CO, PVR, and/or ⁇ values may be conveniently calibrated to continuous, absolute CO and PVR values with a single thermodilution measurement. It will be appreciated that certain embodiments of the invention provide absolute average LAP without requiring calibration based on a thermodilution measurement.
  • Preferred methods of the invention for determining proportional CO, average LAP, proportional PVR, and/or other clinically important hemodynamic variables by performing a mathematical analysis of a PAP waveform, e.g., as described above, do not entail the use of a neural network.
  • Certain preferred methods of the invention also do not make use of a set of training data.
  • the methods of the invention for determining proportional CO, average LAP, proportional PVR, and/or other clinically important hemodynamic variables do not require making conventional measurements of a subject's PCWP (e.g., by advancing a pulmonary artery catheter into a branch of the pulmonary artery, inflating the balloon, and averaging the ensuing steady-state pressure) as a prerequisite to the monitoring of proportional CO, average LAP, and/or other clinically important hemodynamic variables in the subject.
  • the methods of the invention for determining proportional CO, average LAP, proportional PVR, and/or other clinically important hemodynamic variables also do not require a training data set comprising conventional measurements of PCWP in one or more subjects in order to monitor, according to the methods of the invention, proportional CO, average LAP, and/or other clinically important hemodynamic variable(s) in the same subjects or different subjects.
  • proportional CO, average LAP, and/or other clinically important hemodynamic variable(s) in the same subjects or different subjects are also do not require a training data set comprising conventional measurements of PCWP in one or more subjects in order to monitor, according to the methods of the invention, proportional CO, average LAP, and/or other clinically important hemodynamic variable(s) in the same subjects or different subjects.
  • the methods and apparatus of the invention are therefore not adapted specifically for determining PCWP from a PAP waveform based on a correlation between measured values of the PAP and PCWP but instead determine LAP without relying on a correlation between measured PAP and PCWP.
  • PCWP is usually measured primarily in order to provide an estimate of LAP even though such an estimate suffers from a number of limitations noted above.
  • the methods of the invention offer an advantage over prior art methods that employ either a measured or estimated PCWP value as an estimate for LAP.
  • the LAP determined according to the methods of the invention could be used to approximately determine PCWP.
  • LAP determined according to the methods of the invention could either be used directly as an approximate of PCWP, or the determined LAP could be adjusted in order to provide an improved estimate of PCWP.
  • such an adjustment is accomplished through a training data set comprising PAP waveforms and conventional PCWP measurements.
  • LAP is determined as described above with respect to the PAP waveforms in the training data set, and a model (e.g., linear or nonlinear regression) is developed according to any of the methods known in the art to predict the corresponding PCWP measurements in the training data set.
  • PCWP is subsequently estimated from a PAP waveform by first determining LAP according to the methods of the invention and then applying the trained model to the determined LAP to predict PCWP.
  • proportional CO, average LAP, and/or other hemodynamic variables are determined by mathematical analysis of the contour of a RVP waveform.
  • the RVP waveform is preferably obtained from patients without stenosis of the pulmonic valve so that the RVP waveform may be regarded as equivalent to the unobserved PAP waveform during each systolic ejection interval.
  • the systolic ejection intervals of the RVP waveform are identified by any method known in the art, e.g., using a phonocardiogram or other physiologic signals.
  • the beginning of systole for each beat may be determined as the time of the maximum temporal derivative of each RVP pulse [61], while the end of systole for each beat may be identified as the time of the peak value of each RVP pulse (y(t) in Figure 6a).
  • the end of systole for each beat may be identified as the time of the peak value of each RVP pulse (y(t) in Figure 6a).
  • the systolic ejections intervals of a segment of a RVP waveform of duration greater than a cardiac cycle are fitted according to the sum of an unknown constant term representing the average LAP and the convolution of an unknown impulse response representing the dynamical properties of the pulmonary arterial tree with a known and complete cardiac contractions signal as defined above.
  • the impulse response and constant term that provide the best fit of the systolic ejection intervals of the RVP waveform segment are then utilized to determine average LAP and the Windkessel time constant ⁇ of the pulmonary arterial tree as described above ( Figure 6a).
  • the complete PAP waveform segment (including diastolic intervals) is constructed by the convolution between the resulting impulse response and the complete cardiac contractions signal (z(t) in Figure 6b) plus the resulting average LAP.
  • proportional CO is determined either as the difference between the mean value of the constructed PAP waveform segment and the resulting average LAP divided by the resulting ⁇ or the product of the peak value of the pulmonary arterial tree impulse response and the average heart rate.
  • This particular aspect of the invention may be utilized, for example, in patients instrumented with implanted devices capable of monitoring a RVP waveform [I].
  • the method (and apparatus) for constructing a PAP waveform containing both systolic and diastolic intervals based on the systolic ejection intervals of the RVP waveform is an aspect of this invention.
  • the PAP waveform constructed according to the method of the invention can be further analyzed for any of a variety of purposes including, but not limited to, determining average LAP, proportional CO, or proportional PVR as described herein.
  • the mathematical analysis of a circulatory contour involves the use of a Windkessel model analogous to Figure 3 to represent the slow dynamical properties of the systemic arterial tree.
  • the above mathematical procedures described in the context of PAP waveform analysis are applied to a SAP waveform (or a related waveform such as a photoplethysmography signal) measured at any site in the systemic arterial tree.
  • the above mathematical procedures described in the context of RVP waveform analysis may be applied to a left ventricular pressure (LVP) waveform in which aortic stenosis is absent.
  • LVP left ventricular pressure
  • the dynamical properties of the systemic arterial tree and the average SVP (through the constant term) are determined.
  • SVP may be regarded as negligible with respect to SAP (i.e., left panel of Figure 1) and only the dynamical properties of the systemic arterial tree are determined.
  • the determined dynamical properties may then be analogously utilized to determine proportional CO and proportional SVR.
  • proportional CO and proportional SVR may be utilized, for example, in ICUs, ORs, and recovery rooms in which radial artery catheters are routinely employed or at home, in emergency rooms, and in the ward in which non-invasive SAP waveforms (e.g., finger- cuff photoplethysmography [32], arterial tonometry [35]) could easily be obtained.
  • the continuous, proportional CO and ⁇ values may be conveniently calibrated to continuous, absolute CO and SVR values with a single, absolute measurement of CO.
  • the method for constructing a SAP waveform containing both systolic and diastolic intervals based on the systolic ejection intervals of the LVP waveform is an aspect of this invention.
  • the SAP waveform constructed according to the method of the invention can be further analyzed for any of a variety of purposes including, but not limited to, determining SVP, proportional CO, or proportional SVR as described herein.
  • the constant term represents the asymptotic value of the waveform were cardiac contractions to cease.
  • the invention provides a method for determining the value of a hemodynamic variable based on a PAP, RVP, SAP, or LVP waveform, comprising steps of (i) performing a mathematical analysis to determine the asymptotic value of the waveform were cardiac contractions to cease and (ii) selecting the asymptotic value as the value for the hemodynamic variable.
  • the waveform is a PAP waveform and the hemodynamic variable is average LAP.
  • the waveform is a RVP waveform and the hemodynamic variable is averageLAP.
  • the waveform is a SAP waveform and the hemodynamic variable is average SVP. In certain embodiments of the invention the waveform is a LVP waveform and the hemodynamic variable is average SVP. Any of the methods may further comprise determining the value of proportional CO, proportional PVR, or proportional SVR.
  • the invention further comprises apparatus for use in performing any one or more of the methods of the invention.
  • the invention further provides computer-executable process steps stored on a computer-readable medium for performing one or more methods of the invention.
  • the invention further provides methods of monitoring a subject comprising performing one or more of the inventive methods on a PAP waveform, RVP waveform, SAP waveform or related signal, or LVP waveform obtained from the subject.
  • the methods may further comprise the step of obtaining such a waveform from the subject.
  • the methods may further comprise the step of administering a therapy to the subject, or modifying the subject's therapy, based on one or more hyemodynamic variables obtained according to the methods.
  • FIG. 1 Previous analysis technique for monitoring cardiac output (CO) from a systemic arterial pressure (SAP) waveform [6].
  • SAP cardiac output
  • SAP systemic arterial pressure
  • this technique involves first fitting an exponential function to each diastolic interval of the SAP waveform to determine ⁇ (right) and then dividing the time-averaged SAP (MAP) with ⁇ to estimate proportional CO.
  • FIG. 2 Swine arterial pressure waveforms measured a) centrally in the aorta, (b) peripherally in the radial artery, and (c) in the main pulmonary artery.
  • the diastolic intervals of the central systemic arterial pressure (SAP) waveform resemble exponential decays; however, the measurement of central SAP is too invasive for routine clinical application.
  • exponential diastolic decays are not visible in the peripheral SAP and pulmonary artery pressure (PAP) waveforms, which are heavily corrupted by fast wave reflections and inertial effects.
  • PAP pulmonary artery pressure
  • FIG 3 Electrical analog of the Windkessel model of the pulmonary arterial tree.
  • One embodiment of the mathematical analysis utilizes this model to represent the slow dynamical behavior of the pulmonary arterial tree. For example, if pulsatile activity suddenly ceased, this model predicts that pulmonary artery pressure (PAP) would eventually decay like a pure exponential with a Windkessel time constant ⁇ equal to the product of the pulmonary vascular resistance (PVR) and the nearly constant pulmonary arterial compliance (PAC) as soon as the faster wave and inertial effects vanished (see Figure 2). The model also indicates that the exponential pressure decay would equilibrate towards the left atrial pressure (LAP), which significantly contributes to PAP due to the relatively small PVR.
  • PAP pulmonary artery pressure
  • LAP left atrial pressure
  • Figure 4 One embodiment in which the mathematical analysis is applied to the individual diastolic decay intervals of a pulmonary artery pressure (PAP) waveform (y(t)). Multiple, complex exponential functions and a constant term are fitted to each diastolic decay interval of y(t) to respectively determine the dynamical properties of the pulmonary arterial tree and the average left atrial pressure (LAP). Then, the Windkessel time constant ⁇ of the pulmonary arterial tree (see Figure 3) is determined by extrapolating the computed exponential functions to low-pressure values and fitting a mono-exponential function to the extrapolated pressure values for which the faster wave and inertial effects have vanished. Finally, proportional cardiac output (CO) is determined via Ohm's law (overbar indicates time averaging). This intra-beat embodiment of the mathematical analysis may be capable of monitoring beat-to-beat changes in CO and LAP.
  • PAP pulmonary artery pressure
  • Figure 5 One embodiment in which the mathematical analysis is applied to all temporal variations in a pulmonary artery pressure (PAP) waveform (y(tj) including those occurring over time scales greater than a cardiac cycle.
  • PAP pulmonary artery pressure
  • Average left atrial pressure (LAP) and the response of PAP minus average LAP to a single, solitary cardiac contraction (h(t)) are simultaneously estimated by fitting a segment of y(t).
  • the Windkessel time constant ⁇ of the pulmonary arterial tree (see Figure 3) is determined by fitting a mono-exponential function to the tail end o ⁇ h(t) once the faster wave and inertial effects have vanished.
  • proportional cardiac output (CO) is computed via Ohm's law (overbar indicates time averaging).
  • FIG. 6 One embodiment in which the mathematical analysis is applied to a right ventricular pressure (RVP) waveform (y(tj) obtained from patients without pulmonic valve stenosis, (a) The systolic ejection intervals of a RVP waveform segment are identified and regarded as equivalent to the unobserved pulmonary artery pressure (PAP).
  • RVP right ventricular pressure
  • the present invention is based at least in part on the recognition that proportional CO, average LAP, and/or other hemodynamic variables are reflected in the contour of a PAP waveform, a RVP waveform, or other circulatory signals.
  • the invention therefore involves the mathematical analysis of the contour of a circulatory signal so as to decipher, and thereby determine, e.g., continuously, these clinically significant hemodynamic variables.
  • the mathematical analysis of a circulatory contour is specifically defined here to comprise an examination of the temporal variations in the signal.
  • monitoring LAP via the end-diastolic PAP does not constitute a mathematical analysis of a circulatory contour, since this examination simply indicates PAP at particular instances of time (end-diastole).
  • the mathematical analysis of a circulatory contour is based on the Windkessel model of the pulmonary arterial tree shown in Figure 3.
  • PVR is known to be nonlinear over a wide pressure range [25], it may be approximated as linear over the more narrow range of PAP variations that are considered by various embodiments of the present invention.
  • PAP should decay like a pure exponential during each diastolic interval with a time constant ( ⁇ ) equal to the product of PVR and the pulmonary AC (PAC).
  • ⁇ time constant
  • PAC pulmonary AC
  • Windkessel model of Figure 3 suggests that both ⁇ and average LAP may be determined from a PAP waveform by fitting a single exponential function plus a constant term to each of its diastolic intervals.
  • PAC may be nearly constant over a wide pressure range
  • CO may also be determined to within a constant scale factor by dividing the time-averaged PAP-LAP with ⁇ .
  • the invention encompasses the recognition that this simple fitting procedure is not generally valid in practice, because exponential diastolic decays are usually obscured in physiologic PAP waveforms by complex wave and inertial effects (Figure 2c).
  • the invention further encompasses the recognition that the confounding wave and inertial dynamics are faster than the exponential Windkessel dynamics [55]. This implies that if pulsatile activity were to abruptly cease, then PAP would eventually decay like a pure exponential and ultimately equilibrate to the LAP once the faster wave and inertial dynamics vanished.
  • the Windkessel model of Figure 3 is specifically used to represent only the slow dynamical properties of the pulmonary arterial tree.
  • proportional CO, average LAP, and/or other hemodynamic variables are determined by mathematical analysis of each individual diastolic decay interval of a PAP waveform. For example, basis functions, e.g., multiple, complex exponential functions and a constant term are fitted to each diastolic decay interval of PAP to respectively determine the dynamical properties of the pulmonary arterial tree and the average LAP ( Figure 4). Then, the Windkessel time constant ⁇ of the pulmonary arterial tree may be determined by extrapolating the computed exponential functions to low-pressure values and fitting a mono-exponential function to the extrapolated pressure values for which the faster wave and inertial effects have dissipated (Figure 4). Finally, proportional CO may be determined over any number of beats via Ohm's law.
  • Figure 4 illustrates the details of this embodiment of the mathematical analysis, which is applied to a digitized PAP waveform sampled at, for example, 90 Hz. It will be appreciated that different sampling rates could be used. This embodiment is specifically employed in four steps.
  • the diastolic decay interval of each PAP pulse is identified as the entire downstroke (i.e., from maximum to minimum pressure) or by any other method known in the art.
  • each diastolic decay interval may be identified with a simultaneous phonocardiogram measurement.
  • each diastolic decay interval may be determined according to any formula based on the cardiac cycle length (T) such as the well- known Bazett formula (T - 0.3 ⁇ T ) [4].
  • Each cardiac cycle length may be determined from the PAP waveform and/or other simultaneously measured physiologic signals such as a surface ECG measurement.
  • any number of complex exponential functions and a constant term are fitted to each of the identified diastolic decay intervals of the PAP waveform (y(tj).
  • the estimated constant term represents the average LAP, while the estimated complex exponential functions characterize the wave, inertial, and Windkessel dynamical properties of the pulmonary arterial tree.
  • e(t) is the unmeasured residual error
  • the pair of parameters ⁇ cik, bk ⁇ completely specify each complex exponential function
  • n indicates the number of complex exponential functions
  • h(t) represents the temporal evolution of the complex exponential functions collectively for all time.
  • the parameters including c are estimated from the diastolic decay intervals of y(t) through the least-squares minimization of the residual error [43].
  • This optimization problem may be solved through a numerical search ⁇ e.g., Gauss Newton method) or the Stieglitz-McBride iteration [43].
  • the parameters may be more conveniently, but not optimally, estimated using other methods known in the art such as Prony's method and Shank's method [7,56].
  • an optimal number of complex exponential functions may be determined according to any of the methods known in the art that penalize for unnecessary parameters (e.g., root-normalized-mean- squared-error (RNMSE) threshold) [43].
  • RPMSE root-normalized-mean- squared-error
  • y(t) may be lowpass filtered in order to attenuate the complex wave and inertial effects.
  • any other parametric model with complex exponential basis functions ⁇ e.g., autoregressive exogenous input (ARX) model [43]) or any other functions ⁇ e.g., polynomials
  • ARX autoregressive exogenous input
  • any other minimization criterion e.g., absolute error
  • the parameters can be selected such that the error is below a predetermined value (e.g., 110-120% of the minimum error), in which the predetermined value is specifically selected so as to achieve an acceptable accuracy for the purposes at hand.
  • a predetermined value e.g. 110-120% of the minimum error
  • the estimated complex exponential functions are extrapolated to low-pressure values. This step is achieved by recursively solving for h(t) (until it is effectively zero) based on the estimated parameters ⁇ ⁇ k ,b k ⁇ as follows:
  • the Windkessel time constant ⁇ of the pulmonary arterial tree is then determined over the interval o ⁇ h(t) preferably over a time interval in which the faster wave and inertial effects have become minimal.
  • the contribution of the faster wave reflections and inertial effects becomes minimal within one second of the peak value of h(t).
  • h(t) may be accurately approximated as a mono-exponential.
  • the selected time interval begins approximately 0.75 seconds following the time of maximum h(t) or, more preferably, approximately one second following the time of maximum h(t).
  • a time interval of 1 to 2 seconds following the time of maximum value o ⁇ h(t) is suitable. Longer time intervals may also be used. Typically the appropriate time interval is predetermined, but, in certain embodiments of the invention, it may be selected as the measurements are being made.
  • the parameters A and ⁇ may be estimated according to any procedure known in the art.
  • the parameters may be determined by the closed-form, linear least squares solution after log transformation o ⁇ h(t).
  • ⁇ may be identified as the largest real valued time constant of the estimated complex exponential functions. Note that this step is unnecessary when only a single exponential function is utilized to fit the diastolic decay interval of the PAP pulse.
  • the average LAP is determined as the mean or median value of the estimated constant term c over any number of beats, while CO is determined to within a constant scale factor equal to 1/PAC as the difference between the mean value of PAP over any number of beats and the corresponding average LAP divided by the mean or median value of the corresponding ⁇ .
  • PVR is also trivially determined to within a constant scale factor via ⁇ .
  • the proportional, continuous CO and PVR estimates may be calibrated, if desired, with a single, absolute measurement of CO. Such a calibration may be conveniently implemented with the bolus thermodilution method, if a pulmonary artery catheter were employed. Otherwise, if an independent CO measurement is unavailable, then a nomogram may be utilized, if desired, to calibrate the proportional estimates.
  • proportional CO, average LAP, and other hemodynamic variables are determined by mathematical analysis of all temporal variations in a PAP waveform including those occurring over time scales greater than a cardiac cycle in which the confounding effects of wave and inertial phenomena are attenuated [55].
  • average LAP and the response of PAP minus average LAP to a single, solitary cardiac contraction are simultaneously estimated by fitting a PAP waveform segment of duration greater than a cardiac cycle ⁇ e.g., 30 seconds to 10 minutes).
  • Windkessel time constant ⁇ of the pulmonary arterial tree is determined by fitting a mono-exponential function to the tail end of h(t) once the faster wave and inertial effects have vanished (Figure 5).
  • proportional CO may be computed by dividing the time-averaged PAP-LAP with ⁇ .
  • an intra-beat embodiment will likely provide better temporal resolution ⁇ e.g., ability to detect beat-to-beat hemodynamic changes
  • an inter-beat embodiment is expected to be more accurate in terms of estimating average hemodynamic values as the beat-to-beat PAP variations are much more reflective of Windkessel dynamics than confounding wave and inertial phenomena (i.e., a larger signal-to-"noise" ratio) [55].
  • Figure 5 illustrates the details of this embodiment of the mathematical analysis, which is applied to a segment of a digitized PAP waveform (sampled at, e.g., 90 Hz) of duration greater than a cardiac cycle (e.g., 30 seconds to ten minutes). It will be appreciated that different sampling rates could be used. This embodiment is specifically employed in four steps.
  • a cardiac contractions signal is constructed by forming an impulse train in which each impulse is located at the onset of upstroke of a PAP pulse (R) and has an area equal to the ensuing pulse pressure (PP). PP is determined, for example, as the maximum PAP value minus the PAP value at the onset of upstroke.
  • each impulse may be placed at the R- wave of a simultaneous surface ECG measurement, and/or the area of each impulse may be set to an arbitrary constant or any other value based on the PAP pulse.
  • pulses of any shape e.g., rectangular
  • duration equal to the systolic ejection interval may be utilized in lieu of the transient impulses.
  • the relationship between the cardiac contractions signal (x(t)) and the PAP waveform segment iy(t)) is determined by estimating both a constant term and an impulse response (h(t)) which when convolved with x(t) "best" fits y(t) minus the constant term.
  • the estimated constant term represents the average LAP
  • the estimated h(t) characterizes the dynamical properties of the pulmonary arterial tree and is defined to represent the (scaled) PAP- LAP response to a single cardiac contraction.
  • the model order is determined by minimizing any criterion ⁇ e.g., Minimum Description Length criterion) or method known in the art that penalizes for unnecessary parameters [43].
  • criterion e.g., Minimum Description Length criterion
  • x(t) and y(t) may be lowpass filtered in order to amplify the contribution of long time scale energy such that the least squares estimation is prioritized at these time scales.
  • any other parametric model ⁇ e.g., autoregressive moving average with exogenous input (ARMAX) equation [43]) may be employed in various embodiments of the invention to represent the structure of h(t), and any other minimization criterion (e.g., absolute error) may be utilized to determine the "best" h(t) and average LAP.
  • ARMAX autoregressive moving average with exogenous input
  • the Windkessel time constant ⁇ of the pulmonary arterial tree is determined over the interval of h(t) for which the faster wave and inertial effects have dissipated For example, the interval ranging from one to two seconds following the time of the maximum value of h(t) may be selected. (See Figure 5 and discussion above for other exemplary time intervals.)
  • This step may be achieved based on Equation (3) as described above.
  • accurate determination of ⁇ as well as LAP are achieved by virtue o ⁇ h(t) coupling the long time scale variations inx(t) to y(t)-LAP.
  • proportional CO is computed via Ohm's law, and proportional PVR is given as ⁇ .
  • proportional CO may be determined as the product of the peak value of the estimated h(t) and the average heart rate and proportional PVR may be subsequently determined via Ohm's law.
  • the proportional, continuous CO and PVR estimates may be calibrated, if desired, as described above.
  • the aforementioned embodiments of the mathematical analysis may also be applied to a SAP waveform (or a related waveform such as a photoplethysmography signal) measured at any site in the systemic arterial tree.
  • a SAP waveform or a related waveform such as a photoplethysmography signal
  • proportional CO, proportional SVR, and average SVP or only proportional CO and proportional SVR may be continuously monitored.
  • proportional CO, average LAP, and other hemodynamic variables are determined by mathematical analysis of the contour of a RVP waveform.
  • RVP and PAP may be regarded as nearly equal during the systolic ejection interval of each beat provided that there is no significant stenosis of the pulmonic valve ( Figure 6).
  • the systolic ejection intervals of the observed RVP waveform are therefore identified so as to produce an "incomplete" PAP waveform without diastolic pressure information. Then, with this incomplete PAP waveform, the clinically significant hemodynamic variables may be determined similarly to embodiments described above.
  • Figure 6 illustrates one such embodiment of the mathematical analysis, which is applied to a segment of a digitized RVP waveform (sampled at, e.g. , 90 Hz) of duration greater than a cardiac cycle (e.g., 30 seconds to ten minutes).
  • a cardiac cycle e.g. 30 seconds to ten minutes.
  • each systolic ejection interval within the RVP waveform segment is identified.
  • the beginning of systole for each beat is determined as the time of the maximum temporal derivative of each RVP pulse [61], while the end of systole for each beat is identified as the time of the peak value of each RVP pulse.
  • any other method known in the art e.g., see above may be used to identify the systolic ejection intervals. This step produces an incomplete segment of a PAP waveform.
  • a cardiac contractions signal is constructed as described above. Note that the resulting cardiac contractions signal is defined for all values of time (i.e., both systole and diastole).
  • the relationship between the complete cardiac contractions signal (x(t)) and the incomplete PAP waveform (y(tj) is characterized by estimating both a constant term representing average LAP and the impulse response (h(t)) which when convolved withx(%) "best" fits y(t) minus the average LAP.
  • e(t) is the unmeasured residual error
  • the parameters ⁇ a t , b k ) completely specify h(t)
  • m and n limit the number of these parameters (model order) [43].
  • the parameters including c are estimated from x(t) and the incomplete y(t) through the least-squares minimization of the residual error during the systolic ejections intervals.
  • This optimization problem may be solved, for example, through a numerical search procedure (e.g., Gauss Newton method) or the Stieglitz-McBride iteration [43].
  • the model order may be determined similarly to that of Equation (1).
  • x(t) and y(t) may be lowpass filtered in order to amplify the contribution of long time scale energy such that the least squares estimation is prioritized at these time scales.
  • h(t) is computed according to Equation (6) and average LAP is given as c .
  • other parametric models may be employed in various embodiments of the invention to represent the structure o ⁇ h(t), and any other minimization criterion (e.g., absolute error) may be utilized to determine the "best" h(t) and average LAP.
  • ⁇ is determined from the estimated h(t) based on Equation (3) as described above. Again, in certain embodiments of the invention, accurate determination of ⁇ as well as average LAP is achieved by virtue of h(t) coupling the long time scale variations inx(t) to the incomplete y(t)-LAP.
  • the complete PAP waveform including diastolic information is constructed by convolving the cardiac contractions signal x(t) with the estimated h(t) and then summing this response (z(t)) to the average LAP. This step is mathematically achieved as follows:
  • proportional CO is determined via Ohm's law, and proportional PVR is trivially obtained with ⁇ .
  • proportional CO may also be determined as the product of the peak value of the estimated h(t) and the average heart rate and proportional PVR may be subsequently determined via Ohm's law.
  • the proportional, continuous CO and PVR estimates may be calibrated as described above.
  • the invention includes apparatus for performing the methods described above, e.g., for determining LAP.
  • the apparatus may comprise memory means that stores a program comprising computer-executable process steps and a processing unit that executes the computer-readable process steps so as to perform a mathematical analysis of the contour of a PAP waveform, RVP waveform, SAP waveform, LVP waveform or another circulatory signal (or any two or more of the foregoing) and uses the mathematical analysis to determine average LAP, proportional CO, proportional PVR, proportional SVR, average SVP, etc.
  • the apparatus may perform any one or more of the methods described herein to determine any one or more of the hemodynamic variables discussed herein, e.g., average LAP, proportional CO, proportional PVR, proportional SVR, average SVP.
  • an analog PAP waveform, RVP waveform, SAP waveform, LVP waveform or another circulatory signal is fed into an analog-to- digital converter as it is being measured.
  • the circulatory signal may be acquired using standard methods, such as those mentioned above.
  • a surface ECG is also measured, e.g., via standard ECG leads.
  • the digitized circulatory signal and the ECG, if measured, are stored in a buffer system.
  • the most recent time intervals of the digitized signals (e.g., one cardiac cycle to ten minutes) are transferred from the buffer system to a processing unit, which analyzes the signal according to the methods of the invention.
  • the buffer and processing unit may be implemented using, for example, any standard microcomputer or implanted circulatory monitoring device running appropriate software to implement the mathematical operations described above.
  • the software components of the invention may be coded in any suitable programming language and may be embodied in any of a range of computer-readable media including, but not limited to, floppy disks, hard disks, CDs, zip disks, DVD disks, etc.
  • processing unit is used herein to refer to any suitable combination of general and/or special purpose processors.
  • at least some of the processing steps may be implemented using hardware, e.g., signal processing chips.
  • the methods may be implemented using any suitable combination of general and/or special purpose processors and appropriate software.
  • Computer-readable media that store computer- executable process steps to perform all or part of one or more methods of the invention are also an aspect of the invention.
  • Outputs such as proportional CO, LAP or SVP, and proportional PVR or SVR may be displayed on a visual display such as a computer screen and/or may be printed or transmitted to a remote location.
  • the ECG, and analysis thereof, may also be displayed.
  • the process is continuously repeated thereby providing the on-line monitoring of proportional CO, LAP or SVP, proportional PVR or SVR, and/or other hemodynamic variables (e.g., with a delay equal to half the selected analysis interval).
  • absolute CO and PVR or SVR may be computed and displayed through a nomogram or a single, independent measurement of absolute CO.
  • an alarm is triggered upon excessive changes in any of the estimated variables.
  • the methods may further comprise the step of selecting, recommending, suggesting, or administering a therapy to the subject, or modifying the subject's therapy, based on values for one or more hemodynamic variables obtained according to the methods and apparatus.
  • the therapy may be, for example, any medical or surgical therapy known in the art that is suitable for treating a subject having a physiological state consistent with the determined average LAP, average SAP, proportional CO, proportional PVR and/or proportional SVR.
  • Exemplary therapies include pharmaceutical agents, e.g., pressors or diuretics, fluids, etc.
  • therapy is administered or ongoing therapy is modified (e.g, the dose of a pharmaceutical agent is increased or decreased) automatically.
  • the apparatus may interface with or include a device that modifies the infusion rate of a solution (optionally containing a therapeutic agent) in response to values for one or more of the hemodynamic variables measured according to the invention.
  • a device that modifies the infusion rate of a solution (optionally containing a therapeutic agent) in response to values for one or more of the hemodynamic variables measured according to the invention.
  • the inventive system can operate using feedback, e.g., to provide closed-loop therapy.
  • Specific desired values, or ranges of desired values, for the hemodynamic variables can be selected, e.g., by a patient's health care provider, and the apparatus can modify therapy in order to achieve these values.
  • the apparatus monitors and optionally records, stores, and/or analyzes the response of one or more of the hemodynamic variables to changes in therapy.
  • the analysis can be used to make further adjustments or modifications to the therapeutic regimen.
  • the system can learn how particular therapies or alterations in therapy affect one or more hemodynamic variables and can select future therapy accordingly.
  • suggested or recommended therapies or modifications to ongoing therapies are displayed on a display device.
  • a system or apparatus of the present invention may also include means for acquiring a circulatory signal from a subject.
  • a system or apparatus of the invention may include a catheter, e.g., a pulmonary artery catheter.
  • certain of the signal processing steps may be performed by the acquisition means itself.
  • the acquisition means may include hardware for performing filtering, analog-to-digital conversion, analysis, etc., of the acquired signal.
  • the invention comprises apparatus and computer-executable process steps for performing the steps of the method and also comprises a method for monitoring a subject using the method for determining one or more hemodynamic variables and further comprises a method of treating a subject comprising monitoring a subject using the method and recommending, suggesting, selecting, modifying, and/or administering a therapy based at least in part on data and/or information acquired or obtained using the method, e.g., based at least in part on the subject's average LAP, average SVP, proportional CO, proportional PVR, and/or proportional SVR as determined according to the method.
  • the methods and/or apparatus of the invention may be used to determine or monitor any one or more of these hemodynamic variables, e.g., any subset of these hemodynamic variables.
  • All references cited herein are incorporated by reference. In the event of a conflict or inconsistency between any of the incorporated references and the instant specification, the specification shall control, it being understood that the determination of whether a conflict or inconsistency exists is within the discretion of the inventors and can be made at any time.
  • Critchley, LAH Impedance cardiography, the impact of new technology. Anaesthesia, 53:677-684, 1998. 12. Critchley, LAH, JAJH Critchley. A meta-analysis of studies using bias and precision statistics to compare cardiac output measurement techniques. J. Clin. Monit. Comput., 15:85-91, 1999.
  • Marik, PE The systolic blood pressure variation as an indicator of pulmonary capillary wedge pressure in ventilated patients. Anaesth. Intensive Care, 21(4):405-408, 1993.

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Abstract

L'invention concerne un procédé et un appareil qui déterminent un débit cardiaque proportionnel (CO), une pression auriculaire gauche absolue (LAP) et/ou d'autres variables hémodynamiques importantes depuis le contour d'une forme d'onde de pression circulatoire ou un signal en rapport. Certains modes de réalisation de l'invention comprennent l'analyse mathématique d'une forme d'onde de pression artérielle pulmonaire (PAP) ou d'une forme d'onde de pression ventriculaire droite (RVP) pour déterminer un CO proportionnel de battement à battement ou moyenné au cours du temps, une résistance vasculaire pulmonaire proportionnelle (PVR) et/ou une LAP. L'invention permet la surveillance continue et automatique de variables hémodynamiques critiques avec un niveau d'invasion adapté pour une application clinique routinière. L'invention peut être utilisée par exemple pour surveiller en continu des patients malades critiques ayant des cathéters d'artère pulmonaire installés et pour surveiller de manière chronique des patients cardiaques pourvus de dispositifs implantés pour mesurer une RVP.
PCT/US2007/076351 2007-08-21 2007-08-21 Détermination du débit cardiaque et de la pression ventriculaire gauche WO2009025667A1 (fr)

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Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103298412A (zh) * 2010-10-21 2013-09-11 尤伦·帕提 使用经胸肺部多普勒超声测量肺部血压
US8827913B2 (en) 2011-05-03 2014-09-09 Medtronic, Inc. Verification of pressure metrics
US9241640B2 (en) 2010-07-28 2016-01-26 Medtronic, Inc. Measurement of cardiac cycle length and pressure metrics from pulmonary arterial pressure
US9301702B2 (en) 2012-11-19 2016-04-05 Pacesetter, Inc. Systems and methods for exploiting pulmonary artery pressure obtained from an implantable sensor to detect cardiac rhythm irregularities
US9314205B2 (en) 2011-04-28 2016-04-19 Medtronic, Inc. Measurement of cardiac cycle length and pressure metrics from pulmonary arterial pressure
US9566442B2 (en) 2012-11-19 2017-02-14 Pacesetter, Inc. Systems and methods for using pulmonary artery pressure from an implantable sensor to detect mitral regurgitation and optimize pacing delays
US20200315467A1 (en) * 2017-02-02 2020-10-08 Edwards Lifesciences Corporation Hemodynamic monitor providing enhanced cardiac output measurements

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4986277A (en) * 1988-08-24 1991-01-22 Sackner Marvin A Method and apparatus for non-invasive monitoring of central venous pressure
US5265011A (en) * 1989-04-03 1993-11-23 Eastern Medical Testing Services, Inc. Method for ascertaining the pressure pulse and related parameters in the ascending aorta from the contour of the pressure pulse in the peripheral arteries
US20050027322A1 (en) * 2003-07-29 2005-02-03 Medtronic, Inc. Mechanically-based interval optimization for a biventricular pacing engine
US20060149330A1 (en) * 2004-12-30 2006-07-06 Brian Mann Digitally controlled cardiac rhythm management
US20060173248A1 (en) * 2005-01-27 2006-08-03 Mustafa Karamanoglu Derivation of flow contour from pressure waveform

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4986277A (en) * 1988-08-24 1991-01-22 Sackner Marvin A Method and apparatus for non-invasive monitoring of central venous pressure
US5265011A (en) * 1989-04-03 1993-11-23 Eastern Medical Testing Services, Inc. Method for ascertaining the pressure pulse and related parameters in the ascending aorta from the contour of the pressure pulse in the peripheral arteries
US20050027322A1 (en) * 2003-07-29 2005-02-03 Medtronic, Inc. Mechanically-based interval optimization for a biventricular pacing engine
US20060149330A1 (en) * 2004-12-30 2006-07-06 Brian Mann Digitally controlled cardiac rhythm management
US20060173248A1 (en) * 2005-01-27 2006-08-03 Mustafa Karamanoglu Derivation of flow contour from pressure waveform

Cited By (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9241640B2 (en) 2010-07-28 2016-01-26 Medtronic, Inc. Measurement of cardiac cycle length and pressure metrics from pulmonary arterial pressure
US9254091B2 (en) 2010-07-28 2016-02-09 Medtronic, Inc. Measurement of cardiac cycle length and pressure metrics from pulmonary arterial pressure
US10226630B2 (en) 2010-07-28 2019-03-12 Medtronic, Inc. Measurement of cardiac cycle length and pressure metrics from pulmonary arterial pressure
CN103298412A (zh) * 2010-10-21 2013-09-11 尤伦·帕提 使用经胸肺部多普勒超声测量肺部血压
CN103298412B (zh) * 2010-10-21 2017-05-31 尤伦·帕提 使用经胸肺部多普勒超声测量肺部血压
US9314205B2 (en) 2011-04-28 2016-04-19 Medtronic, Inc. Measurement of cardiac cycle length and pressure metrics from pulmonary arterial pressure
US10362946B2 (en) 2011-04-28 2019-07-30 Medtronic, Inc. Measurement of cardiac cycle length and pressure metrics from pulmonary arterial pressure
US11399725B2 (en) 2011-04-28 2022-08-02 Medtronic, Inc. Measurement of cardiac cycle length and pressure metrics from pulmonary arterial pressure
US8827913B2 (en) 2011-05-03 2014-09-09 Medtronic, Inc. Verification of pressure metrics
US9301702B2 (en) 2012-11-19 2016-04-05 Pacesetter, Inc. Systems and methods for exploiting pulmonary artery pressure obtained from an implantable sensor to detect cardiac rhythm irregularities
US9566442B2 (en) 2012-11-19 2017-02-14 Pacesetter, Inc. Systems and methods for using pulmonary artery pressure from an implantable sensor to detect mitral regurgitation and optimize pacing delays
US20200315467A1 (en) * 2017-02-02 2020-10-08 Edwards Lifesciences Corporation Hemodynamic monitor providing enhanced cardiac output measurements

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