CA2300078A1 - Heart rate variability as an indicator of exercise capacity - Google Patents
Heart rate variability as an indicator of exercise capacity Download PDFInfo
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- CA2300078A1 CA2300078A1 CA002300078A CA2300078A CA2300078A1 CA 2300078 A1 CA2300078 A1 CA 2300078A1 CA 002300078 A CA002300078 A CA 002300078A CA 2300078 A CA2300078 A CA 2300078A CA 2300078 A1 CA2300078 A1 CA 2300078A1
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
- A61N1/00—Electrotherapy; Circuits therefor
- A61N1/18—Applying electric currents by contact electrodes
- A61N1/32—Applying electric currents by contact electrodes alternating or intermittent currents
- A61N1/36—Applying electric currents by contact electrodes alternating or intermittent currents for stimulation
- A61N1/362—Heart stimulators
- A61N1/365—Heart stimulators controlled by a physiological parameter, e.g. heart potential
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
- A61N1/00—Electrotherapy; Circuits therefor
- A61N1/18—Applying electric currents by contact electrodes
- A61N1/32—Applying electric currents by contact electrodes alternating or intermittent currents
- A61N1/36—Applying electric currents by contact electrodes alternating or intermittent currents for stimulation
- A61N1/362—Heart stimulators
- A61N1/3627—Heart stimulators for treating a mechanical deficiency of the heart, e.g. congestive heart failure or cardiomyopathy
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
- A61N1/00—Electrotherapy; Circuits therefor
- A61N1/18—Applying electric currents by contact electrodes
- A61N1/32—Applying electric currents by contact electrodes alternating or intermittent currents
- A61N1/36—Applying electric currents by contact electrodes alternating or intermittent currents for stimulation
- A61N1/362—Heart stimulators
- A61N1/365—Heart stimulators controlled by a physiological parameter, e.g. heart potential
- A61N1/36592—Heart stimulators controlled by a physiological parameter, e.g. heart potential controlled by the heart rate variability
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- Electrotherapy Devices (AREA)
- Medicines Containing Material From Animals Or Micro-Organisms (AREA)
- Pharmaceuticals Containing Other Organic And Inorganic Compounds (AREA)
- Measuring Pulse, Heart Rate, Blood Pressure Or Blood Flow (AREA)
Abstract
Based upon patient studies, a high degree of correlation was found between HRV, and VO2max, i.e., the patient's exercise capacity. A pacing therapy optimization protocol for treating patients with CHF has been devised. An HRV index is derived during a first pacing mode, then the mode is changed, and the steps repeated for all modes. The pacemaker mode with the highest HRV index is then programmed. Alternatively the method can apply to changes in drug therapy instead, or in combination with pacing therapy.
Description
BEART RATE VARIABILITY AS AN
INDICATOR OF EXERCISE CAPACITY
I. ~~,Z,d Q~ the T,D,yention: This invention relates generally to a method and apparatus for assessing patient well-being, and more particularly to a method and apparatus for indirectly determining a patient's peak oxygen uptake (V02,,~) by measuring his/her heart rate variability (HRV).
II. n;~c,mainn of the Prior Art: It is known in the art that HRV, i.e., the beat-to-beat variance in sinus cycle length over a period of time, is a predictor of mortability and morbidity. Patient s exhibiting low HRV
show a significantly increased risk of sudden cardiac death. See "Heart Rate Variability" by Zsolt Ori, et al., Cardiolocnr Clinics, Vol. 10, No. 3, August 1992, pp. 499-537 and "Depressed Heart Rate Variability As An Independent Predictor of Death in Chronic Congestive Heart Failure Secondary to Ischemic or Idiopathic Dilated Cardiomyopathy"
by Piotr Ponikowski, et al., The American JoLrnal of Cardioloav, Vol. 79, June 15, 1997, pp. 1645-1650. See also "Correlations Among Time and Frequency Domain Measures of Heart Period Variability Two Weeks After Acute Myocardial Infarction" by J. Thomas Bigger et al., Am__e-r,'_can ~~~yal of Cardi of ocrv, Vol . 69, April 1, 1992 . In addition, the Spinelli et al. U.S. Patent 5,466,245 provides a very detailed method for automatically determining AV delay based on evaluating a frequency domain measure of heart rate variability (HRV).
In the Heemels et al. U.S. Patent 5,603,331, assigned to applicant's assignee, a method and apparatus is described for efficiently processing, logging and disseminating essential features relating to HRV
accumulated from a continuous, long-term monitoring of cardiac activity. As pointed out in that patent, the method is sufficiently conserves data memory, program memory and power consumption that it may be incorporated' within an implantable pacemaker or defibrillator to log a r.
INDICATOR OF EXERCISE CAPACITY
I. ~~,Z,d Q~ the T,D,yention: This invention relates generally to a method and apparatus for assessing patient well-being, and more particularly to a method and apparatus for indirectly determining a patient's peak oxygen uptake (V02,,~) by measuring his/her heart rate variability (HRV).
II. n;~c,mainn of the Prior Art: It is known in the art that HRV, i.e., the beat-to-beat variance in sinus cycle length over a period of time, is a predictor of mortability and morbidity. Patient s exhibiting low HRV
show a significantly increased risk of sudden cardiac death. See "Heart Rate Variability" by Zsolt Ori, et al., Cardiolocnr Clinics, Vol. 10, No. 3, August 1992, pp. 499-537 and "Depressed Heart Rate Variability As An Independent Predictor of Death in Chronic Congestive Heart Failure Secondary to Ischemic or Idiopathic Dilated Cardiomyopathy"
by Piotr Ponikowski, et al., The American JoLrnal of Cardioloav, Vol. 79, June 15, 1997, pp. 1645-1650. See also "Correlations Among Time and Frequency Domain Measures of Heart Period Variability Two Weeks After Acute Myocardial Infarction" by J. Thomas Bigger et al., Am__e-r,'_can ~~~yal of Cardi of ocrv, Vol . 69, April 1, 1992 . In addition, the Spinelli et al. U.S. Patent 5,466,245 provides a very detailed method for automatically determining AV delay based on evaluating a frequency domain measure of heart rate variability (HRV).
In the Heemels et al. U.S. Patent 5,603,331, assigned to applicant's assignee, a method and apparatus is described for efficiently processing, logging and disseminating essential features relating to HRV
accumulated from a continuous, long-term monitoring of cardiac activity. As pointed out in that patent, the method is sufficiently conserves data memory, program memory and power consumption that it may be incorporated' within an implantable pacemaker or defibrillator to log a r.
24-hour period of cardiac activity accumulated for subsequent telemetry to an external monitor. The patent further describes a method of processing and displaying HRV
data in a manner that is readily understandable by clinicians which provides an improved graphical contrast between normal and abnormal HRV patterns.
Further studies which we have recently conducted on several patients has revealed a high correlation between HRV and a patient's exercise capacity as measured by V02,,~,X.
Based upon this realization, a method has been established for indirectly assessing a patient's maximum oxygen uptake by computing the standard deviation of five minute mean RR
intervals, i.e., the SDANN Index. In an alternative approach, a two-dimensional histogram array is plotted with RR intervals along one axis and the absolute value of the time difference between successive RR intervals plotted along the second axis. By measuring the area on the plot occupied by the two-dimensional histogram, V02,.~,X can be estimated.
SUMMARY OF THE INVENTION
In accordance with a first aspect of the invention, an estimation of a patient's maximum oxygen uptake can be derived by the following method:
First, a patient's ECG waveform is sensed and recorded over a 24-hour period. In a pacemaker implementation, the whole 24-hour recording is not possible. Instead, the R-R
interval is calculated in real time (on the fly?. The recording is then analyzed and a determination is made as to the average length of normal RR intervals in 288 five minute intervals. When the standard deviation of the 288 averages is computed, it yields an index exhibiting a high correlation with the patient's peak oxygen consumption.
In an alternative method, rather than computing the SDANN Index, the length of RR intervals in the recorded ECG
waveform during a plurality of time segments of a predetermined length are measured and the absolute value of the time difference between successive RR intervals is determined. By plotting this data as a two-dimensional histogram and then measuring the area on the plot occupied by the two-dimensional histogram, the patient's peak oxygen uptake can be inferred. That is to say, studies have shown that there is a high correlation between the area or "footprint" of the histogram and the patient's peak oxygen uptake.
Irrespective of which of the above methods is employed, the information arrived at can be utilized in assessing the efficacy of a given mode of drug therapy or electrical cardiac stimulation on a patient's exercise capacity. By comparing the HRV Index computed in accordance with the first method or the footprint area determined in accordance with the alternative method, improvements in a patient's peak oxygen uptake resulting from a predetermined therapy regimen can be determined.
This is achieved without the need for conducting a breath-by-breath analysis of ventilatory flow and subjecting the patient to a treadmill test or the like.
DESCRIPTION OF THE DRAWINGS
Figure 1 is a graphical representation of a patient data collection schedule for ECG waveforms and V02roaX
measurements;
Figure 2 is a plot . of V02max and the computed SDANN
index plotted on the same time axis and showing the correlation of each as the pacing protocol is changed;
Figure 3 is a pseudo three-dimensional histogram plot of RR interval vs. the absolute value of the difference in RR interval between successive heart beats;
Figure 4 is a two-dimensional histogram plot taken prior to pacer implant where frequency of occurrence of predetermined HRV values are represented by a gray scale;
Figure 5 is a plot like that of Figure 4 but representing HRV data taken following four weeks of pacing therapy;
data in a manner that is readily understandable by clinicians which provides an improved graphical contrast between normal and abnormal HRV patterns.
Further studies which we have recently conducted on several patients has revealed a high correlation between HRV and a patient's exercise capacity as measured by V02,,~,X.
Based upon this realization, a method has been established for indirectly assessing a patient's maximum oxygen uptake by computing the standard deviation of five minute mean RR
intervals, i.e., the SDANN Index. In an alternative approach, a two-dimensional histogram array is plotted with RR intervals along one axis and the absolute value of the time difference between successive RR intervals plotted along the second axis. By measuring the area on the plot occupied by the two-dimensional histogram, V02,.~,X can be estimated.
SUMMARY OF THE INVENTION
In accordance with a first aspect of the invention, an estimation of a patient's maximum oxygen uptake can be derived by the following method:
First, a patient's ECG waveform is sensed and recorded over a 24-hour period. In a pacemaker implementation, the whole 24-hour recording is not possible. Instead, the R-R
interval is calculated in real time (on the fly?. The recording is then analyzed and a determination is made as to the average length of normal RR intervals in 288 five minute intervals. When the standard deviation of the 288 averages is computed, it yields an index exhibiting a high correlation with the patient's peak oxygen consumption.
In an alternative method, rather than computing the SDANN Index, the length of RR intervals in the recorded ECG
waveform during a plurality of time segments of a predetermined length are measured and the absolute value of the time difference between successive RR intervals is determined. By plotting this data as a two-dimensional histogram and then measuring the area on the plot occupied by the two-dimensional histogram, the patient's peak oxygen uptake can be inferred. That is to say, studies have shown that there is a high correlation between the area or "footprint" of the histogram and the patient's peak oxygen uptake.
Irrespective of which of the above methods is employed, the information arrived at can be utilized in assessing the efficacy of a given mode of drug therapy or electrical cardiac stimulation on a patient's exercise capacity. By comparing the HRV Index computed in accordance with the first method or the footprint area determined in accordance with the alternative method, improvements in a patient's peak oxygen uptake resulting from a predetermined therapy regimen can be determined.
This is achieved without the need for conducting a breath-by-breath analysis of ventilatory flow and subjecting the patient to a treadmill test or the like.
DESCRIPTION OF THE DRAWINGS
Figure 1 is a graphical representation of a patient data collection schedule for ECG waveforms and V02roaX
measurements;
Figure 2 is a plot . of V02max and the computed SDANN
index plotted on the same time axis and showing the correlation of each as the pacing protocol is changed;
Figure 3 is a pseudo three-dimensional histogram plot of RR interval vs. the absolute value of the difference in RR interval between successive heart beats;
Figure 4 is a two-dimensional histogram plot taken prior to pacer implant where frequency of occurrence of predetermined HRV values are represented by a gray scale;
Figure 5 is a plot like that of Figure 4 but representing HRV data taken following four weeks of pacing therapy;
Figure 6 is a plot showing the correlation between histogram of footprint size and V02",ax for the data collection schedule of Figure 1; and Figure 7 is a flow chart of the algorithm for determining an optimum pacing mode based upon the relationship of HRV to peak oxygen uptake.
DESCRIPTION OF THE PREFERRED EMBODIMENT
Referring to Figure 1, there is graphically illustrated the data collection approach used in establishing the relationship between heart rate variability and V02maX. Twenty-four hour surface ECG data was collected on seven CHF patients at four time points during a period of twelve weeks. Specifically, the data was collected just prior to the implant of a cardiac pacemaker, then again at the end of four weeks of pacing, at the end of four weeks of no pacing (eight weeks), and at the end of four weeks of pacing (twelve weeks). The pacing mode was randomized between best univentricular pacing and biventricular pacing, during the two four-week periods during which pacing took place. ECG data was sampled at 500 Hz and recorded on a modified 16-bit solid state digital holter recorder. At each of the four time points, the patients also performed symptom-limited maximal exercise tests . V02maX, VO2max at the anaerobic threshold, maximum power attained and total exercise duration were some of the exercise parameters collected.
The surface ECG data was filtered to remove any premature ventricular contractions and other ectopic beats, to obtain normal RR intervals. Various HRV parameters were calculated from the measured and filtered RR intervals.
The well-known SDANN .index, which is the standard deviation of five-minute intervals averaged over 288 five-minute intervals in a 24-hour period, was computed for the four 24-hour sampling periods illustrated in Figure 1. The SDANN indices for these four sampling periods are plotted as curve 2 in Figure 2 and also plotted on the same graph as curve 4 are the values of V02,~ex measured at the same time. The change in SDANN index correlated well with the change in V02",ax. Also apparent is the fact that the pacing therapy proved effective in improving these patient's exercise capacity.
The HRV data collected in accordance with the protocol of Figure 1 was also plotted as a two-dimensional histogram where the RR intervals and absolute value of the difference between successive RR intervals are quantized into a plurality of bins and then plotted against one another as shown in Figure 3. Through logarithmic compression, as described fully in U.S. Patent 5,603,331, and which is hereby incorporated by reference, the frequency value to be plotted on the Z axis can be limited to a number of levels compatible with the amount of memory available.
In the graphs of Figures 4 and 5, the histogram is plotted with a gray scale utilized to identify the frequency parameter. As in the case of Figure 3, the RR
interval number is plotted against the absolute value of the difference between successive RR intervals and rather than having the distance along a Z axis as a measure of the frequency value, a gray scale color is used instead. Thus, the plots of Figures 4 and 5 can be considered as contour maps of the pseudo three-dimensional histogram with different shades of gray representing various heights of the Z axis found in the pseudo three-dimensional plot. We have found the area subtended by the plot, i.e., its footprint, to be an indicator of V02~,aX with changes in footprint area due to pacing also tracking changes in V02m~.
Comparing Figures 4 and 5, it is readily apparent that pacing the patient suffering CHF had the effect of increasing that patient's maximum exercise capacity.
Footprint area is determined by counting the number of non-zero pixels in the two-dimensional plot.
Figure 7 is a software flow diagram for optimizing the pacing mode of an implantable programmable cardiac pacer based upon observed improvements in a patient's exercise' capacity and which does not require cardiopulmonary exercise monitoring equipment in carrying out the method.
This flow diagram is in sufficient detail such that a programmer of ordinary skill can write software code for allowing a microprocessor to carry out the indicated functions. Such microprocessor program may be implemented in the implantable pacemaker device itself or, alternatively, may comprise equipment external to the patient.
It is contemplated that the implantable pacemaker is of the type that allows its mode to be reprogrammed via a transcutaneous telemetry link. Most present-day pacemakers incorporate this capability. The first step in carrying out the process is to initialize a pacing mode table, a therapy time table and an evaluation period table as represented by block 20 in Figure 7. The implanted pacemaker is capable of operating in a plurality of modes Mk , k= 0 , 1, . . . N . For example , a f first mode may be VDD
with a first AV interval and a second mode may be VDD with a second, different AV interval. A mode change may also be based upon the pacing site (or sites in the case of a biventricular pacemaker). In fact, any change in the pacing regimen may be assigned as a mode in the pacing mode table.
The therapy time Tk determines the time that a mode change takes place and will typically be measured in terms of days, weeks or months. The evaluation period ~Tk establishes the length of time over which heart rate variability data is collected and will typically be measured in terms of hours.
Once the initialization steps reflected in block 20 have been programmed, the pacemaker will be set to the first mode Mo (block 22) and the patient will continue to be paced in accordance with that first mode until the therapy time Tk has elapsed (block 24). At this time, the evaluation period timer oTk is initialized to a starting point. With the evaluation period timer running, each RR
interval (RRi) is extracted from the ECG waveform (block 28) and repetitive calculations are made to measure heart rate variability as the absolute value of the difference between two successive RR intervals lRRi-RRi_11. This is represented by block 30 in Figure 7. Each time a new HRV value is computed, it is stored in an appropriate bin of a histogram memory (block 32). A test is then made at decision block 34 to determine whether the evaluation period ~Tk has expired. If not, control loops back via path 36 to the input of block 28 so that steps 28, 30 and 32 are repeated iteratively until the time interval ~Tk has expired.
At that point, the histogram is effectively plotted (block 36). Next, either the 2D histogram footprint area or some other feature of the 2D histogram is calculated as a measure of HRVk, i.e., the heart rate variability measure for the particular mode involved. While the 2D histogram footprint area has been determined to be a measure of V02max.
other features of the 2D histogram may also be indicative of V02max. For example, the slope of the diagonal that is tangent to the base of the 2D plot is believed to be an indicator of HRV as well.
Irrespective of the approach used in deriving HRVk, as represented by block 40, the next step in the algorithm is to compare the current HRV measure with that earlier derived relating to the immediately previous mode to determine whether HRVk is greater than HRV k_1 . If it is, then the current mode is shown to have provided improved V02max and the previous mode is discarded as an option.
However, had the current heart rate variability index been less than the index derived for the previous mode, then the current mode would be disregarded.
As indicated by decision block 42, a test is made to determine whether all of the possible modes in the pacing mode table have been considered and, if not, the mode index is incremented (block 44) and control loops back over path 46 to the input of block 22 whereby the routine is repeated until all modes have been exercised.
_g_ By way of conclusion, then, we have determined, based upon patients' studies, that change in V02maX correlates directly with change in heart rate variability and that information concerning the patient's exercise capacity can be derived from ECG signals. Moreover, the patient's exercise capacity can be inferred from the SDANN index or, alternatively, from the area of the footprint of a two dimensional histogram where heart rate variability is plotted against RR interval over a predetermined time interval.
This invention has been described herein in considerable detail in order to comply with the patent statutes and to provide those skilled in the art with the information needed to apply the novel principles and to construct and use such specialized components as are required. However, it is to be understood that the invention can be carried out by specifically different equipment and devices, and that various modifications, both as to the equipment and operating procedures, can be accomplished without departing from the scope of the invention itself. For example, while the present invention has been described and illustrated in connection with patient therapy being carried out by electrical stimulation from an implantable pacemaker, it is also contemplated that the different therapy modes can be based on the administration of various drugs where such drugs have an influence on cardiac performance. Thus, the mode table can include a series of different drugs or the same drug but with differing dosages. Periodically, and in accordance with the entries in the therapy time table and the evaluation period table, the drug therapy mode would be changed and the effect on HRV, as measured by SDANN or a feature of the 2D histogram used to assess the efficacy of each mode.
What is claimed is:
DESCRIPTION OF THE PREFERRED EMBODIMENT
Referring to Figure 1, there is graphically illustrated the data collection approach used in establishing the relationship between heart rate variability and V02maX. Twenty-four hour surface ECG data was collected on seven CHF patients at four time points during a period of twelve weeks. Specifically, the data was collected just prior to the implant of a cardiac pacemaker, then again at the end of four weeks of pacing, at the end of four weeks of no pacing (eight weeks), and at the end of four weeks of pacing (twelve weeks). The pacing mode was randomized between best univentricular pacing and biventricular pacing, during the two four-week periods during which pacing took place. ECG data was sampled at 500 Hz and recorded on a modified 16-bit solid state digital holter recorder. At each of the four time points, the patients also performed symptom-limited maximal exercise tests . V02maX, VO2max at the anaerobic threshold, maximum power attained and total exercise duration were some of the exercise parameters collected.
The surface ECG data was filtered to remove any premature ventricular contractions and other ectopic beats, to obtain normal RR intervals. Various HRV parameters were calculated from the measured and filtered RR intervals.
The well-known SDANN .index, which is the standard deviation of five-minute intervals averaged over 288 five-minute intervals in a 24-hour period, was computed for the four 24-hour sampling periods illustrated in Figure 1. The SDANN indices for these four sampling periods are plotted as curve 2 in Figure 2 and also plotted on the same graph as curve 4 are the values of V02,~ex measured at the same time. The change in SDANN index correlated well with the change in V02",ax. Also apparent is the fact that the pacing therapy proved effective in improving these patient's exercise capacity.
The HRV data collected in accordance with the protocol of Figure 1 was also plotted as a two-dimensional histogram where the RR intervals and absolute value of the difference between successive RR intervals are quantized into a plurality of bins and then plotted against one another as shown in Figure 3. Through logarithmic compression, as described fully in U.S. Patent 5,603,331, and which is hereby incorporated by reference, the frequency value to be plotted on the Z axis can be limited to a number of levels compatible with the amount of memory available.
In the graphs of Figures 4 and 5, the histogram is plotted with a gray scale utilized to identify the frequency parameter. As in the case of Figure 3, the RR
interval number is plotted against the absolute value of the difference between successive RR intervals and rather than having the distance along a Z axis as a measure of the frequency value, a gray scale color is used instead. Thus, the plots of Figures 4 and 5 can be considered as contour maps of the pseudo three-dimensional histogram with different shades of gray representing various heights of the Z axis found in the pseudo three-dimensional plot. We have found the area subtended by the plot, i.e., its footprint, to be an indicator of V02~,aX with changes in footprint area due to pacing also tracking changes in V02m~.
Comparing Figures 4 and 5, it is readily apparent that pacing the patient suffering CHF had the effect of increasing that patient's maximum exercise capacity.
Footprint area is determined by counting the number of non-zero pixels in the two-dimensional plot.
Figure 7 is a software flow diagram for optimizing the pacing mode of an implantable programmable cardiac pacer based upon observed improvements in a patient's exercise' capacity and which does not require cardiopulmonary exercise monitoring equipment in carrying out the method.
This flow diagram is in sufficient detail such that a programmer of ordinary skill can write software code for allowing a microprocessor to carry out the indicated functions. Such microprocessor program may be implemented in the implantable pacemaker device itself or, alternatively, may comprise equipment external to the patient.
It is contemplated that the implantable pacemaker is of the type that allows its mode to be reprogrammed via a transcutaneous telemetry link. Most present-day pacemakers incorporate this capability. The first step in carrying out the process is to initialize a pacing mode table, a therapy time table and an evaluation period table as represented by block 20 in Figure 7. The implanted pacemaker is capable of operating in a plurality of modes Mk , k= 0 , 1, . . . N . For example , a f first mode may be VDD
with a first AV interval and a second mode may be VDD with a second, different AV interval. A mode change may also be based upon the pacing site (or sites in the case of a biventricular pacemaker). In fact, any change in the pacing regimen may be assigned as a mode in the pacing mode table.
The therapy time Tk determines the time that a mode change takes place and will typically be measured in terms of days, weeks or months. The evaluation period ~Tk establishes the length of time over which heart rate variability data is collected and will typically be measured in terms of hours.
Once the initialization steps reflected in block 20 have been programmed, the pacemaker will be set to the first mode Mo (block 22) and the patient will continue to be paced in accordance with that first mode until the therapy time Tk has elapsed (block 24). At this time, the evaluation period timer oTk is initialized to a starting point. With the evaluation period timer running, each RR
interval (RRi) is extracted from the ECG waveform (block 28) and repetitive calculations are made to measure heart rate variability as the absolute value of the difference between two successive RR intervals lRRi-RRi_11. This is represented by block 30 in Figure 7. Each time a new HRV value is computed, it is stored in an appropriate bin of a histogram memory (block 32). A test is then made at decision block 34 to determine whether the evaluation period ~Tk has expired. If not, control loops back via path 36 to the input of block 28 so that steps 28, 30 and 32 are repeated iteratively until the time interval ~Tk has expired.
At that point, the histogram is effectively plotted (block 36). Next, either the 2D histogram footprint area or some other feature of the 2D histogram is calculated as a measure of HRVk, i.e., the heart rate variability measure for the particular mode involved. While the 2D histogram footprint area has been determined to be a measure of V02max.
other features of the 2D histogram may also be indicative of V02max. For example, the slope of the diagonal that is tangent to the base of the 2D plot is believed to be an indicator of HRV as well.
Irrespective of the approach used in deriving HRVk, as represented by block 40, the next step in the algorithm is to compare the current HRV measure with that earlier derived relating to the immediately previous mode to determine whether HRVk is greater than HRV k_1 . If it is, then the current mode is shown to have provided improved V02max and the previous mode is discarded as an option.
However, had the current heart rate variability index been less than the index derived for the previous mode, then the current mode would be disregarded.
As indicated by decision block 42, a test is made to determine whether all of the possible modes in the pacing mode table have been considered and, if not, the mode index is incremented (block 44) and control loops back over path 46 to the input of block 22 whereby the routine is repeated until all modes have been exercised.
_g_ By way of conclusion, then, we have determined, based upon patients' studies, that change in V02maX correlates directly with change in heart rate variability and that information concerning the patient's exercise capacity can be derived from ECG signals. Moreover, the patient's exercise capacity can be inferred from the SDANN index or, alternatively, from the area of the footprint of a two dimensional histogram where heart rate variability is plotted against RR interval over a predetermined time interval.
This invention has been described herein in considerable detail in order to comply with the patent statutes and to provide those skilled in the art with the information needed to apply the novel principles and to construct and use such specialized components as are required. However, it is to be understood that the invention can be carried out by specifically different equipment and devices, and that various modifications, both as to the equipment and operating procedures, can be accomplished without departing from the scope of the invention itself. For example, while the present invention has been described and illustrated in connection with patient therapy being carried out by electrical stimulation from an implantable pacemaker, it is also contemplated that the different therapy modes can be based on the administration of various drugs where such drugs have an influence on cardiac performance. Thus, the mode table can include a series of different drugs or the same drug but with differing dosages. Periodically, and in accordance with the entries in the therapy time table and the evaluation period table, the drug therapy mode would be changed and the effect on HRV, as measured by SDANN or a feature of the 2D histogram used to assess the efficacy of each mode.
What is claimed is:
Claims (10)
1. A method of indirectly assessing a patient s maximum oxygen uptake (VO2 MAX) comprising the steps of:
(a) sensing and recording RR intervals from ECG
waveform of a patient over a 24-hour period;
(b) determining from the recording the average length of R-to-R intervals in 288 five-minute intervals;
and (c) computing the standard deviation of the 288 averages determined in step (b) to create an index correlating with VO2 MAX for the patient.
(a) sensing and recording RR intervals from ECG
waveform of a patient over a 24-hour period;
(b) determining from the recording the average length of R-to-R intervals in 288 five-minute intervals;
and (c) computing the standard deviation of the 288 averages determined in step (b) to create an index correlating with VO2 MAX for the patient.
2. A method of assessing the efficacy of a given mode of cardiac therapy on a patient's exercise capacity, comprising the steps of:
(a) applying cardiac therapy to the patient's heart in accordance with said given mode;
(b) recording ECG waveforms from the patient over a predetermined time period;
(c) measuring the average length of R-to-R
intervals in said waveforms during a plurality of predetermined segments of the predetermined time period;
(d) computing the standard deviation of the plurality of said segment averages to create a HRV index;
(e) repeating steps (b)-(d) at a time subsequent to said first time; and (f) comparing the HRV index computed in step (d) associated with ECG waveforms recorded at said first time with the HRV index computed in step (d) associated with the EGG waveforms recorded at said subsequent time to determine whether the given mode of therapy improves ar degrades the patient's exercise capacity.
(a) applying cardiac therapy to the patient's heart in accordance with said given mode;
(b) recording ECG waveforms from the patient over a predetermined time period;
(c) measuring the average length of R-to-R
intervals in said waveforms during a plurality of predetermined segments of the predetermined time period;
(d) computing the standard deviation of the plurality of said segment averages to create a HRV index;
(e) repeating steps (b)-(d) at a time subsequent to said first time; and (f) comparing the HRV index computed in step (d) associated with ECG waveforms recorded at said first time with the HRV index computed in step (d) associated with the EGG waveforms recorded at said subsequent time to determine whether the given mode of therapy improves ar degrades the patient's exercise capacity.
3. The method of Claim 2 and further including the step of:
(g) changing the mode of cardiac therapy so as to cause an increase in the HRV index computed in step (d) associated with the ECG wavaforms recorded at said subsequent time over the HRV index computed in step (d) associated with the ECG waveforms recorded at said first time.
(g) changing the mode of cardiac therapy so as to cause an increase in the HRV index computed in step (d) associated with the ECG wavaforms recorded at said subsequent time over the HRV index computed in step (d) associated with the ECG waveforms recorded at said first time.
4. The method as in any one of Claims 1-3 wherein the mode of cardiac therapy comprises a mode of electrical cardiac stimulation.
5. The method as in any one of Claims 1-3 wherein the mode of cardiac therapy comprises a mode of drug applications.
6. A method for indirectly assessing a patient's maximum oxygen uptake (VO2 max), comprising the steps of:
(a) sensing and recording RR intervals obtained from ECG waveforms from the patient over a predetermined period;
(b) determining from the recording, the average length of RR intervals in said waveforms during a plurality of time segments of predetermined length in said predetermined period;
(c) calculating the absolute value of the time difference between successive RR intervals determined in step (b);
(d) plotting as a two-dimensional histogram array the RR intervals as a function of said absolute value of the time difference; and (e) measuring a feature of the two-dimensional histogram.
(a) sensing and recording RR intervals obtained from ECG waveforms from the patient over a predetermined period;
(b) determining from the recording, the average length of RR intervals in said waveforms during a plurality of time segments of predetermined length in said predetermined period;
(c) calculating the absolute value of the time difference between successive RR intervals determined in step (b);
(d) plotting as a two-dimensional histogram array the RR intervals as a function of said absolute value of the time difference; and (e) measuring a feature of the two-dimensional histogram.
7. The method of Claim 6 wherein the feature measured comprises an area on the plot occupied by the two-dimensional histogram.
8. A method of optimizing a mode of therapy applied to a patient, comprising the steps of:
(a) measuring and recording ECG waveforms over a predetermined time interval at a first point in time;
(b) computing from said ECG waveforms the absolute value of the difference in the length of successive RR intervals;
(c) plotting a two-dimensional histogram of the values computed in step (b) vs. RR intervals;
(d) measuring the area subtended by the plot of step (c) as an indicator of a patient's exercise capacity;
(e) subsequently changing the mode of therapy applied to the patient;
(f) repeating steps (a) through (d) at a later time;
(g) comparing the area measured in step (d) at the first point in time to the area measured in step (d) at the later time to assess which area is the greater; and (h) adjusting the mode of therapy to increase the patient's exercise capacity.
(a) measuring and recording ECG waveforms over a predetermined time interval at a first point in time;
(b) computing from said ECG waveforms the absolute value of the difference in the length of successive RR intervals;
(c) plotting a two-dimensional histogram of the values computed in step (b) vs. RR intervals;
(d) measuring the area subtended by the plot of step (c) as an indicator of a patient's exercise capacity;
(e) subsequently changing the mode of therapy applied to the patient;
(f) repeating steps (a) through (d) at a later time;
(g) comparing the area measured in step (d) at the first point in time to the area measured in step (d) at the later time to assess which area is the greater; and (h) adjusting the mode of therapy to increase the patient's exercise capacity.
9. The method of Claim 8 wherein the mode of therapy applied to the patient comprises electrical cardiac stimulation.
10. The method of Claim 8 wherein the mode of therapy applied to the patient comprises drug application.
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- 1999-06-04 JP JP2000553171A patent/JP4383664B2/en not_active Expired - Fee Related
- 1999-06-04 WO PCT/US1999/012588 patent/WO1999064108A1/en active IP Right Grant
- 1999-06-04 AT AT99928404T patent/ATE368420T1/en not_active IP Right Cessation
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