Method and apparatus to optimize pacing heart rate

The present disclosure provides an apparatus and method of optimizing a pacing heart rate. The method can include obtaining a preload-frequency relation and a force-frequency relation from histogram data for a patient condition and determining an optimal pacing heart rate for the patient condition. The optimal pacing heart rate can be substantially between a first heart rate corresponding to a minimum preload condition based on the preload-frequency relation and a second heart rate corresponding to a sustained ionotropic reserve condition based on the force-frequency relation.

TECHNICAL FIELD

This disclosure relates generally to a method and apparatus to optimize pacing heart rates.

BACKGROUND

Pacing therapy can be used in the treatment of heart failure, which refers to a clinical syndrome in which an abnormality of cardiac function causes a below normal cardiac output that can fall below a level adequate to meet the metabolic demand of peripheral tissues. When uncompensated, it usually presents as congestive heart failure due to the accompanying venous and pulmonary congestion. It has been shown that some heart failure patients suffer from intraventricular and/or interventricular conduction defects (e.g., bundle branch blocks) such that their cardiac outputs can be increased by improving the synchronization of ventricular contractions with electrical stimulation. Cardiac rhythm management devices have therefore been developed which provide electrical stimulation to the ventricles in an attempt to improve the coordination of cardiac contractions, termed cardiac resynchronization therapy (CRT).

The degree to which a heart muscle fiber is stretched before it contracts is termed the preload, while the degree of tension or stress on a heart muscle fiber as it contracts is termed the afterload. When a myocardial region contracts late relative to other regions, the contraction of those other regions stretches the later contracting region and increases its preloading, thus causing an increase in the contractile force generated by the region. Because pressure within the ventricles rises rapidly from a diastolic to a systolic value as blood is pumped out into the aorta and pulmonary arteries, the parts of the ventricles that contract later during systole do so against a higher afterload than do parts of the ventricles contracting earlier. Thus, a ventricular region that contracts later than other regions is subjected to both an increased preload and afterload, both of which act to increase the mechanical stress experienced by the region relative to other regions.

Resynchronization pacing may be delivered in a manner that pre-excites one or more hypertrophied regions in order to subject the regions to a lessened preload and afterload. For example, the ventricles may be paced at multiple sites using a multi-site resynchronization pacing mode, where the delivery of paces to multiple ventricular sites during a cardiac cycle is used to not only enforce a minimum ventricular heart rate, but also to alter the depolarization patterns of the ventricles during systole and improve the coordination of the ventricular contraction. The pulse output sequence can be specified so that one or more hypertrophied regions are paced before other regions during systole and hence mechanically unloaded. By unloading such hypertrophied regions in this way over a period of time, reversal of undesirable ventricular remodeling is effected.

Implantable medical devices have been developed that provide appropriately timed electrical stimulation to one or more heart chambers in an attempt to improve the coordination of ventricular contractions during CRT. Ventricular resynchronization is useful in treating heart failure because resynchronization results in a more coordinated contraction of the ventricles with improved pumping efficiency and increased cardiac output. Currently, a common form of CRT applies stimulation pulses to both ventricles, either simultaneously or separated by a specified biventricular offset interval, and after a specified atrio-ventricular delay interval with respect to the detection of an intrinsic atrial contraction.

In summary, current optimization strategies in cardiac pacing aim to ensure an optimal loading of the ventricles (e.g., atrio-ventricular delay optimization). Also in CRT, an inter-ventricular optimization can lead to an improved cardiac performance as measured by left ventricular pressure gradient.

SUMMARY

In one or more embodiments, an apparatus and method is provided for optimizing a pacing heart rate. The method can include obtaining a preload-frequency relation and a force-frequency relation from a histogram for a patient condition and determining an optimal pacing heart rate for the patient condition. The optimal pacing heart rate can be substantially between a first heart rate corresponding to a minimum preload condition based on the preload-frequency relation and a second heart rate corresponding to a sustained ionotropic reserve condition based on the force-frequency relation.

DETAILED DESCRIPTION

The present disclosure describes a method and apparatus to optimize a pacing heart rate or to diagnose exercise tolerance and other cardiovascular disease state indicators using algorithms combining physiological measures and including hemodynamic sensor information. The present disclosure also describes a method of optimizing a pacing heart rate for cardiac resynchronization therapy (CRT) by an implantable medical device (IMD) that measures and analyzes right ventricle diastolic pressure (RVDP).

The following detailed description is merely illustrative only and is not intended to limit the application and uses of the present disclosure. Furthermore, there is no intention to be bound by any expressed or implied theory presented in the preceding technical field, background, brief summary or the following detailed description.

The following description refers to elements or features being “connected” or “coupled” together. As used herein, unless expressly stated otherwise, “connected” means that one element/feature is directly or indirectly connected to another element/feature, and not necessarily mechanically. Likewise, unless expressly stated otherwise, “coupled” means that one element/feature is directly or indirectly coupled to another element/feature, and not necessarily mechanically. Thus, although the schematic shown inFIG. 4depicts one example arrangement of processing elements, additional intervening elements, devices, features, or components may be present in an actual embodiment (assuming that the functionality of the system is not adversely affected).

In connection with the operation of an IMD, implantable sensors may be expected to provide diagnostic data to the IMD and/or to facilitate automated feedback control of the IMD. For example, direct measurement of RVDP may be well suited to monitor ventricular preload. It would also be useful, however, if the same implantable RVDP sensor could be used to optimize device timing. In this regard, an example embodiment incorporates real-time RVDP signals for use as feedback control (preferably closed loop, but also applicable to open loop) of IMD settings or operational parameters.

FIG. 1is an illustration of an exemplary implantable medical device (IMD)100connected to monitor a patient's heart102. IMD100may be configured to integrate both monitoring and therapy features, as will be described below. IMD100collects and processes data about heart102from one or more sensors including a pressure sensor and an electrode pair for sensing cardiac electrogram (EGM) signals. IMD100may further provide therapy or other response to the patient as appropriate, and as described more fully below. As shown inFIG. 1, IMD100may be generally flat and thin to permit subcutaneous implantation within a human body, e.g., within upper thoracic regions or the lower abdominal region. IMD100is provided with a hermetically-sealed housing that encloses a processor104, a digital memory106, and other components as appropriate to produce the desired functionalities of the device. In various embodiments, IMD100is implemented as any implanted medical device capable of measuring the heart rate of a patient and a ventricular or arterial pressure signal, including, but not limited to a pacemaker, defibrillator, electrocardiogram monitor, blood pressure monitor, drug pump, insulin monitor, or neurostimulator. In some embodiments, the IMD100can be a pacemaker system including a hemodynamic sensor together with memory function and software download capability for optimization algorithms. An example of a suitable IMD that may be used in various exemplary embodiments is the CHRONICLE® monitoring device available from Medtronic, Inc. of Minneapolis, Minn., which includes a mechanical sensor capable of detecting a pressure signal. In a further embodiment, IMD100is any device that is capable of sensing a pressure signal and providing pacing and/or defibrillation or other electrical stimulation therapies to the heart. Another example of an IMD capable of sensing pressure-related parameters is described in commonly assigned U.S. Pat. No. 6,438,408B1 issued to Mulligan et al. on Aug. 20, 2002.

Processor104may be implemented with any type of microprocessor, digital signal processor, application specific integrated circuit (ASIC), field programmable gate array (FPGA) or other integrated or discrete logic circuitry programmed or otherwise configured to provide functionality as described herein. Processor104executes instructions stored in digital memory106to provide functionality as described below. Instructions provided to processor104may be executed in any manner, using any data structures, architecture, programming language and/or other techniques. Digital memory106is any storage medium capable of maintaining digital data and instructions provided to processor104such as a static or dynamic random access memory (RAM), or any other electronic, magnetic, optical or other storage medium.

As further shown inFIG. 1, IMD100may receive one or more cardiac leads for connection to circuitry enclosed within the housing. In the example ofFIG. 1, IMD100receives a right ventricular endocardial lead118, a left ventricular coronary sinus lead122, and a right atrial endocardial lead120, although the particular cardiac leads used will vary from embodiment to embodiment. In addition, the housing of IMD100may function as an electrode, along with other electrodes that may be provided at various locations on the housing of IMD100. In alternate embodiments, other data inputs, leads, electrodes and the like may be provided. Ventricular leads118and122may include, for example, pacing electrodes and defibrillation coil electrodes (not shown) in the event IMD100is configured to provide pacing, cardioversion and/or defibrillation. In addition, ventricular leads118and122may deliver pacing stimuli in a coordinated fashion to provide biventricular pacing, cardiac resynchronization, extra systolic stimulation therapy or other therapies.

IMD100suitably collects and processes data about heart102from one or more sources (e.g., RVDP sensor, heart rate monitor, blood pressure monitor, electrocardiogram (ECG) waveform, electrogram waveform (EGM), etc.). IMD100obtains pressure data input from a pressure sensor that is carried by a lead, such as right ventricular endocardial lead118. The right ventricular lead118can provide a real-time RVDP signal to IMD100from the right ventricle of heart120. The RVDP sensor may be contained on an independent lead, or may be integrated into a pacing or defibrillation lead. In alternate embodiments, other data inputs, leads, electrodes and the like may be provided. The right ventricular lead118may include, for example, pacing electrodes and defibrillation coil electrodes (not shown) for purposes of pacing, cardioversion, and/or defibrillation. IMD100may also obtain input data from other internal or external sources (not shown) such as an oxygen sensor, pH monitor, accelerometer or the like.

In operation, IMD100obtains data about the heart102via the leads118,120,122, and/or other sources. This data is provided to processor104, which suitably analyzes the data, stores appropriate data in memory106, and/or provides a response or report as appropriate. In particular, IMD100generates one or more therapy signals that are preferably optimized in accordance with the obtained data. In the example embodiment, IMD100selects or adjusts an optimized pacing heart rate and coordinates the delivery of the optimized pacing heart rate by IMD100or another appropriate device.

Any identified cardiac episodes (e.g. an arrhythmia or heart failure decompensation) can be treated by intervention of a physician or in an automated manner. In various embodiments, IMD100activates an alarm upon detection of a cardiac event. Alternatively or in addition to alarm activation, IMD100selects or adjusts a therapy and coordinates the delivery of the therapy by IMD100or another appropriate device. Optional therapies that may be applied in various embodiments may include drug delivery or electrical stimulation therapies such as cardiac pacing, CRT, extra systolic stimulation, and neurostimulation.

FIG. 2is a diagram illustrating changes in aortic pressure200, atrial pressure202, ventricular pressure204, and ventricular volume206as related in time to an electrocardiogram208and a phonocardiogram210for two cardiac cycles. Each cardiac cycle is divided into diastole, which represents ventricular filling, and systole, which represents contraction and ejection of blood from the ventricles. In some embodiments, RVDP can be measured by right ventricular lead118during diastole when the right ventricle is being filled and preloaded.

FIG. 3is a diagram showing an example graph of a RVDP signal300along with an example graph of a secondary signal302that represents the first derivative of the RVDP signal (i.e., the RV dP/dt signal). It should be appreciated that these graphs are merely examples and that the actual RVDP characteristics will vary from patient to patient, vary according to the current patient condition, and vary over time.

FIG. 4is a schematic representation of a portion of an IMD100configured in accordance with an example embodiment of the present disclosure. In particular,FIG. 4depicts an exemplary data processing layout for an IMD processor architecture400, which may be located within the housing of a suitable IMD as described herein. In this example, processor architecture400includes at least a data collection module402, a data processing module404, a suitable amount of memory406, a therapy module408, and/or a communication module410. These modules may be coupled to each other via a suitable data communication bus or arrangement411. Each of the various modules may be implemented with computer-executable instructions stored in memory406and executing on processor architecture400, or in any other practical manner. The exemplary modules and blocks shown inFIG. 4are intended to illustrate one logical model for implementing an IMD in accordance with the invention, and should not be construed as limiting. Indeed, the various practical embodiments may have widely varying software modules, data structures, applications, processes and the like. As such, the various functions of each module may in practice be combined, augmented, optimized or otherwise differently-organized in any fashion.

In accordance with the practices of persons skilled in the art of computer programming, the present disclosure may be described herein with reference to symbolic representations of operations that may be performed by the various computing components, modules, or devices. Such operations are sometimes referred to as being computer-executed, computerized, software-implemented, or computer-implemented. It will be appreciated that operations that are symbolically represented include the manipulation by the various microprocessor devices of electrical signals representing data bits at memory locations in the system memory, as well as other processing of signals. The memory locations where data bits are maintained are physical locations that have particular electrical, magnetic, optical, or organic properties corresponding to the data bits.

When implemented in software or firmware, various elements of the IMDs described herein are essentially the code segments or instructions that perform the various tasks. The program or code segments can be stored in a processor-readable medium or transmitted by a computer data signal embodied in a carrier wave over a transmission medium or communication path. The “processor-readable medium” or “machine-readable medium” may include any medium that can store or transfer information. Examples of the processor-readable medium include an electronic circuit, a semiconductor memory device, a ROM, a flash memory, an erasable ROM (EROM), a hard disk, a fiber optic medium, or the like. The computer data signal may include any signal that can propagate over a transmission medium such as electronic network channels, optical fibers, air, electromagnetic paths, or RF links.

Data collection module402suitably interacts with one or more data sources412to obtain data about the patient. Data sources412include any source of information about the patient's heart and possibly other physiologic information. In various embodiments, data sources412may include an ECG source414that provides electrical impulses or other observed signals that can be used to model the patient's ECG waveform. Other data sources412may include a heart rate sensor416, a RVDP sensor or monitor418, and an accelerometer419. In practice, an IMD may also utilize a sensor for determining cardiac conduction time, temperature sensors, blood pH sensors, and/or other known data sources. The various data sources412may be provided alone or in any combination with each other, and may vary widely from embodiment to embodiment.

RVDP sensor418is suitably configured to measure the real-time RVDP of the patient's heart and to provide raw RVDP data to data collection module402. In turn, data collection module402and/or data processing module404can convert the raw RVDP data into a usable RVDP signal for analysis as described herein. A practical IMD can utilize any suitable RVDP sensor418, including, without limitation: RVDP sensors that are mounted through the wall of the heart; RVDP sensors that utilize structures of the heart as a transducer membrane; and RVDP sensors that are inserted through appendages or through cardiac valves. Indeed, processor architecture400can be configured to accommodate the specific RVDP signal format and characteristics associated with the particular RVDP sensor or sensors deployed with the IMD.

The accelerometer419can be connected to the IMD100by lead wires and designed to be affixed to walls of the left atrium, right ventricle, or left ventricle in order to detect mechanical contractions of those chambers. In an exemplary implementation, the accelerometer lead wires are advanced to the heart intravenously. A right ventricular accelerometer may be affixed to the endocardial surface of the right ventricle at the septal wall, while left atrial and ventricular accelerometers may be placed in the coronary sinus and cardiac veins, respectively, to sense movement of the free walls of those chambers. The accelerometer419can be interfaced to the data processing module404by the data collection module402.

The data collection module402suitably receives data from each of the data sources412by polling each of the data sources412, by responding to interrupts or other signals generated by the data sources412, by receiving data at regular time intervals, or according to any other temporal scheme. In particular, the data collection module402is configured to obtain a RVDP signal from the patient for processing. Data may be received at the data collection module402in digital or analog format according to any protocol. If any of the data sources412generate analog data, the data collection module402suitably translates the analog signals to digital equivalents using any form of analog-to-digital conversion scheme presently known or subsequently developed. The data collection module402may also convert data from protocols used by the data sources412to data formats acceptable to the data processing module404, as appropriate. It should be appreciated that the RVDP sensor418, the processor architecture400, the data collection module402, and any corresponding logical elements, individually or in combination, are example means for obtaining a RVDP signal of a patient as used herein.

The data processing module404is any circuit, programming routine, application or other hardware/software module that is capable of processing data received from the data collection module402. In various embodiments, the data processing module404is a software application executing on processor architecture400to implement the processes described below. Accordingly, the data processing module404interprets received RVDP signals300, generates or analyzes signals based upon or derived from received RVDP signals300, and/or handles other data to adjust one or more operating parameters of the IMD100.

In an exemplary embodiment, the data processing module404receives RVDP signal data and/or other appropriate information from the data collection module402and interprets the data using conventional digital signal processing techniques. For example, the data processing module404may generate a secondary signal302that is based upon the first derivative of the RVDP signal (such a secondary signal302may be referred to herein as a RV dP/dt signal as depicted inFIG. 3). In this regard, the data processing module404, the processor architecture400, and any corresponding logical elements, individually or in combination, are example means for generating secondary signals302based upon the RVDP signal300.

As described in more detail below, the data processing module404is configured to identify at least one attribute of the RVDP signal300, and/or at least one attribute of a secondary signal302based upon the RVDP signal300, and correlate the identified attributes to a hemodynamic status or cardiac performance of the patient. In this manner, the RVDP signal300data can be utilized as a feedback control mechanism to adjust the therapy delivered by the IMD100. It should be appreciated that the data processing module404, the processor architecture400, and any corresponding logical elements, individually or in combination, are example means for identifying attributes of the RVDP signal300and/or the RV dP/dt signal302.

The communication module410is any circuit or routine that facilitates the transfer of data, information, reports, or programming instructions between the IMD100and an external device, system, or person (e.g., the patient, a physician, or a caregiver). In various embodiments, communication module410may be configured to generate an audible or visible alarm420, handle wireless messages via a telemetry circuit422, or manage the transmission of other data using any suitable interface424. In this regard, the communication module410may facilitate open-loop feedback control of the IMD operating parameters by transmitting RVDP signals300or RVDP signal attributes to an external processing system that responds with programming instructions to adjust the AV delay or other IMD parameters in the manner described herein. In some embodiments, the alarm420and/or the telemetry module422can be used to provide a warning feature for disease progression, cardiac reserve, exercise tolerance, and/or congestive cardiac failure.

The therapy module408is any suitable circuit, software application or other component that is configured to deliver cardiac therapy426to the patient. In the example embodiment, the therapy module408is configured to provide an optimized pacing heart rate as one form of cardiac therapy426. In some embodiments, therapy module408may be alternatively or additionally configured to deliver various modes of pacing, post-extrasystolic potentiation, cardioversion, defibrillation and/or any other therapy. It should be appreciated that the therapy module408, the cardiac therapy426, the processor architecture400, and any corresponding logical elements, individually or in combination, are example means for automatically optimizing the pacing heart rate of the therapy signal generated by the IMD100.

The various components and processing modules of the IMD100may be housed in a common housing such as that shown inFIG. 1. Alternatively, portions of the IMD100may be housed separately. For example, portions of the therapy module408could be integrated with the IMD100or provided in a separate housing. In this case, the therapy module408may interact with therapy electrodes via an electrical cable, wireless link, or the interface424.

FIG. 5is a flow diagram of an IMD parameter control process500, which may be performed by an IMD100configured in accordance with an example embodiment of the present disclosure. The various tasks performed in connection with process500may be performed by software, hardware, firmware, or any combination thereof. For illustrative purposes, the following description of process500may refer to elements mentioned above in connection withFIGS. 1-4. In practical embodiments, portions of process500may be performed by different elements of the described system, e.g., data sources412, processor architecture400, or any component thereof. It should be appreciated that process500may include any number of additional or alternative tasks, the tasks shown inFIG. 5need not be performed in the illustrated order, and process500may be incorporated into a more comprehensive procedure or process having additional functionality not described in detail herein.

IMD parameter control process500represents a method for analyzing a patient's RVDP data and optimizing a pacing heart rate provided by the IMD100. Process500includes measuring RVDP, heart rate, and accelerometer data (task502). Process500includes collecting data for different patient conditions, including ranges of heart rates, activity levels, and/or circadian periods, such as day-time or night-time (task504). For example, data can be collected for an extended time period, such as 14 months, with a suitable monitoring device, such as the CHRONICLE® monitoring device available from Medtronic, Inc. of Minneapolis, Minn. In some embodiments, the CHRONICLE® monitoring device can be used to obtain the RVDP signals300, to extract the secondary signal302for RV dP/dt, to obtain heart rate, and to obtain accelerometer data per beat.

Histograms can be filled with the data collected for the patient during the extended time period (task506). Histograms can be filled with data representing different heart rate ranges and activity conditions based on the accelerometer data. A histogram corresponding to each patient condition and each heart rate can be created for the patient's RVDP data. For example, as shown inFIGS. 6A and 6B, a histogram of RVDP data can be created for a resting heart rate of 60 beats per minute and a histogram of RVDP data can be created for a resting heart rate of 70 beats per minute, respectively. In other words, the RVDP data for the extended time period can be summarized in a histogram for each heart rate (task508). The histograms can then be used to identify the RVDP value that has the highest percentage of occurrences during the extended time period for each particular heart rate (e.g., a RVDP of 6 mmHg occurs 50% of the time at 60 beats per minute, as shown inFIG. 6A, while a RVDP of 5 mmHg occurs 50% of the time at 70 beats per minute, as shown inFIG. 6B). A typical range for RVDP is 0-8 mmHg (without reference to atmospheric pressure).

Similarly, histograms can be generated for the first derivative RV dP/dt (task510). For example, as shown inFIGS. 7A and 7B, a histogram of RV dP/dt data can be created for a resting heart rate of 60 beats per minute and a histogram of RV dP/dt data can be created for a resting heart rate of 70 beats per minute, respectively. The histograms can then be used to identify the RV dP/dt value that has the highest percentage of occurrences during the extended time period for each particular heart rate (e.g., a RV dP/dt of 0 mmHg/ms occurs 50% of the time at 60 beats per minute, as shown inFIG. 7A, while a RV dP/dt of −3 mmHg/ms occurs 50% of the time at 70 beats per minute, as shown inFIG. 7B). The RVDP and RV dP/dt histograms can also be created for a patient condition in which the patient is exercising (e.g., at a heart rate of 120 or 130 beats per minute), as shown inFIGS. 8A-9B.

In some embodiments, the data for the histograms can be based on information that is stored in the memory106of the IMD100and subsequently re-arranged into blocks that represent the specific patient conditions based on the heart rate or accelerometer data. In some embodiments, the data for the histograms can be stored from test periods during stable patient conditions reflecting the desired patient condition that needs to be optimized (e.g., previous stable resting conditions can be used to optimize future resting conditions and previous stable exercise conditions can be used to optimize future exercise conditions).

Although only two examples of patient conditions and corresponding histograms are shown and described herein, any suitable number of RVDP and RV dP/dt histograms can be created for as many patient conditions as desired. The histograms can be categorized according to suitable patient conditions, such as rest exercise, fluid-overload, day-time, night-time, etc. The various patient conditions can be based on data from the heart rate monitor416and/or data obtained from the accelerometer419, as shown inFIG. 4. The accelerometer419can generate data regarding whether the patient is lying down, standing, or moving while the RVDP, heart rate, and/or ECG data is being gathered by the cardiac sensors and sources412.

Using the RVDP histograms, a preload-frequency relation graph can be generated for a particular patient condition (task512). As shown inFIGS. 10 and 12, graphs can be created using data points representing the RVDP with the highest percentage of occurrences for a particular heart rate (i.e., a graph of highest occurrence RVDP values versus heart rate values). Using the preload-frequency relation graph ofFIG. 10orFIG. 12depending on the patient's current activity level, a first heart rate can be identified that corresponds to the optimal minimum RVDP (or the estimate of an optimal diastolic pulmonary artery pressure) for the cardiac preload condition. This heart rate can be the heart rate on the graph ofFIG. 10where the minimum pressure occurs.

Using the RV dP/dt histograms, a force-frequency relation graph can also be generated for a particular patient condition (task514). As shown inFIGS. 11 and 13, graphs can be created using data points representing the RV dP/dt with the highest percentage of occurrences for a particular heart rate (i.e., a graph of highest occurrence RV dP/dt values versus heart rate values). Using the force-frequency relation graph ofFIG. 11orFIG. 13depending on the patient's current activity level, a second heart rate can be identified that corresponds to the point of the curve representing the upstroke in dP/dt versus heart rate (i.e., a heart rate that achieves sustained ionotropic reserve which can correspond to the steepness of the pressure increase during systole).

An optimized pacing heart rate according to which the IMD100should pace the heart102can be identified between the first heart rate taken from the preload-frequency relation graph ofFIG. 10orFIG. 12and the second heart rate taken from the force-frequency relation graph ofFIG. 11orFIG. 13(task516). In this manner, an optimization of pacing heart rates can lead to optimized pre-load conditions while sustaining the ionotropic reserve of the heart102and the ability to modulate the heart rate by the neuro-hormonal system.

Digital data analysis can be performed to generate curves corresponding to the data ofFIGS. 10-13. In some embodiments, the digital data analysis can include performing multi-dimensional polygonal fitting and/or using waveform algorithms to generate a curve for the data based on rules for each patient condition. The waveform algorithms can be similar to trigger algorithms used for ECG analysis or the Simpson's Rule method (in which the volume is divided into slices and the slices are summed in order to determine the whole).

If the patient is experiencing a fluid-overload condition, the optimized heart rate can be the heart rate at the point in the force-frequency relation graph representing the upstroke in the dP/dt versus heart rate curve based on the resting heart rate histograms. For the patient's ability to perform exercise, the optimized heart rate can be the heart rate at the point in the force-frequency relation graph representing the highest offset in the dP/dt versus heart rate curve based on the exercise heart rate histograms.

The IMD100can then pace the heart102according to the optimized pacing heart rate (task518). In some embodiments, the process500is a closed-loop feedback control scheme performed by the IMD100in which the process500can return to tasks512and514or other previous tasks after performing task518in order to identify a new optimized pacing heart rate when the patient's current condition changes (e.g., the patient condition changes from resting to exercising).

In accordance with the example embodiment of the present disclosure, task516is associated with optimizing the pacing heart rate of a dual-chamber pacing device. Of course, task516may additionally (or alternatively) adjust other IMD parameters, including, without limitation: AV delay timing; Vv delay timing, which is the delay between pacing of both ventricles; AA delay timing, which is the delay between pacing of both atria; intra-atrium pacing delays for IMDs supporting multiple pacing leads in an atrium; intra-ventricle pacing delays for IMDs supporting multiple pacing leads in a ventricle; heart rate; lead location selection for IMDs supporting configurable activation of a plurality of leads in a single chamber (either the atrium and ventricle), which includes both therapy delivery and sensing leads. The IMD100can adjust the hemodynamic parameter or parameters (or can maintain its current operating status) in response to the RVDP and/or RV dP/dt analysis. Of course, the specific adjustment mode, amount of adjustment, and frequency of adjustment will depend upon the current status of the patient, and the particular performance specifications of the IMD100itself.