Technical Classification

A practical classification is to categorize sensors according to the technical methods that are used to measure the sensed parameter (Table 5-1). Body movements during exercise result in changes in acceleration forces that are transmitted to the pacemaker. Sensors that are capable of measuring the acceleration or vibration forces in the pulse generator are broadly referred to as activity sensors. Technically, detection of body movement can be achieved using a piezoelectric crystal, an accelerometer, a tilt switch, or an inductive sensor. Each of these devices transduces motion of the sensor either directly into a voltage or indirectly into measurable changes in the electrical resistance of a piezoresistive crystal. Activity sensing is the most widely used control parameter in rate-adaptive pacing because of its ease of implementation and its compatibility with standard unipolar and bipolar pacing leads. Additionally, activity sensors can be used for either atrial or ventricular pacing modes.

Impedance is a measure of all factors that oppose the flow of electric current and is derived by measuring resistivity to an injected current across a tissue. The impedance principle has been extensively used for measuring respiratory parameters and those associated with ventricular contractility, such as relative stroke volume or the right ventricular preejection interval. Transthoracic impedance can be used to assess respiratory rate and tidal volume by measuring the continuous impedance between the pacemaker casing and an intracardiac electrode. The product of respiratory rate and tidal volume, minute ventilation (MV), is used as the sensed parameter. When using unipolar impedance from a distal electrode of a pacing lead, impedance reflects myocardial contractility, as used in the closed-loop stimulation (CLS) sensor.

The intracardiac ventricular electrogram (EGM) resulting from a suprathreshold pacing stimulus has been used to provide several parameters to guide rate modulation. The total duration of depolarization and repolarization can be estimated by the interval from the pacing stimulus to the intracardiac T wave: the QT interval, or stimulus-T interval. This parameter is sensitive to changes in heart rate and circulating catecholamines and can be derived from the paced EGM with conventional pacing electrodes. This was developed as a QT-sensing pacemaker, based on the QT interval shortening during exercise and stress.⁵

The last group of sensors is incorporated into the pacing lead itself. These specialized leads include thermistors (used to measure blood temperature), piezoelectric crystals (right ventricular pressure), optical sensors (mixed-venous oxygen level), and accelerometers at the tip of pacing leads. Some of these sensors measure highly physiologic parameters. For example, oxygen saturation is closely related to oxygen consumption during exercise. Physical activities increase cardiac output and oxygen extraction from the blood, and the tissue arteriovenous oxygen difference widens during increased tissue oxygen consumption. The fall in oxygen saturation will trigger an increase in rate that will improve cardiac output and minimize the decrease in mixed-venous oxygen saturation.⁶ The mixed-venous oxygen sensor is a true closed-loop system, although its technical complexity limits its use for rate-adaptive pacing. Sensing of changes in blood pH during exercise has also been suggested as a possible sensor, although the requirement for a specialized lead has impeded its clinical implementation.⁷

Using an accelerometer incorporated at the tip of a unipolar ventricular electrode, the contractile state of the right ventricle can be assessed indirectly from the endocardial pressure generated during isovolumic contraction of the heart, a parameter known as peak endocardial acceleration (PEA). PEA is significantly increased by exercise and other inotropic stimuli (e.g., mental stress).

Over the years, many of these sensors have been implemented in implantable devices. Significant differences in rate response were found among sensors, notably between their sensitivity and specificity (Table 5-2). However, only activity, MV, and CLS sensors are currently used for rate response. The activity sensor has the advantage of reliability and ease of implementation; its lack of proportionality to exercise workload has not been a major clinical disadvantage for most patients. Sensors in special leads are no longer used for rate adaptation because of their uncertain long-term reliability and difficulty during pacemaker replacement. However, these sensors are now used for hemodynamic monitoring in heart failure.

Current Activity-Sensing Devices

Medtronic (Kappa 700/900/400, Adapta, Advisa, EnRhythm)

The Medtronic Activitrax and Thera devices were the first generation of activity-sensing pacemakers to use a piezoelectric crystal bonded to the inside of the pacemaker casing to detect activity. Activity levels that exceed a programmable threshold are counted, and the number of counts that exceed a programmable threshold is used to determine the rate response. The clinician adjusts the overall rate response by programming the activity threshold and the rate-response slope. Typically, this instrumentation allows a good response from the programmed lower rate to about 100 beats per minute (bpm) during daily activities. The response to the upper rate is often less accurate and depends on the patient and the programmed settings. Despite their limitations, these piezoelectric devices were clinically highly effective when first introduced.

The current Medtronic activity-sensing device uses an accelerometer attached to the circuit board to detect movement in the anteroposterior (AP) plane. Instead of a fixed threshold, a rolling threshold is used to provide a count of activity that depends not only on the frequency of counts that cross a threshold value, but also on the amplitude (strength) of these counts. This rolling threshold minimizes the detection of low-intensity but high-frequency accelerations, as during motor vehicle travel, but allows detection of high-intensity signals during physical activity.

The sensor-driven rate is adjusted by the use of a triphasic rate curve that incorporates two rate ranges, activity of daily living (ADL) and exertion response (ER) programming (Fig. 5-4). The physician determines the lower rate limit (LRL), the ADL rate, and the sensor-driven upper rate limit (SURL). With the nominal ADL response of 3 (I-5), counts between 12 and 20 will give the ADL rate, during which the rate response will be stable. When counts are greater than 20, ER will occur to the maximum programmed SURL. The flat portion of the response curve corresponds to 25% of the total counts. Adjustment of the ADL and ER to a more sensitive setting will decrease the number of counts needed to reach between ADL rate and SURL, and shorten the ADL portion of the response curve. The actual number of counts to effect a change in pacing rate is not fixed and differs among patients. Rather, an ADL response of 3 implies that the patient will spend up to 30 minutes daily at a sensor rate at or above the ADL. This is achieved by adjusting the rate/count relationship to achieve this percentage of rate response, the ADL set point. Similarly, an ER response of 3 means that the patient will be spending about 20 minutes weekly at the higher rates, 105 to 120 bpm, the upper-rate set point.

Figure 5-4 Triphasic rate-responsive curve.

Medtronic Kappa 600/700/900, Enrhythm, and Enpulse accelerometer activity-sensing pacemakers; ADL, activity of daily living; ER, exertion response.

The acceleration signal input can be adjusted by changing the threshold (lower threshold allows detection of more acceleration signals) and slope. These two parameters affect the sensitivity to the acceleration detected. The physician can manually program these parameters to achieve a faster or slower response in both the ADL and ER ranges.

With automatic rate response, rate profile optimization will adjust these rate curves automatically, using daily comparison of the rate histogram with the target-rate histogram. The device adjusts more quickly in the first 10 days after a programming change so that the new setting will be achieved more quickly (Fig. 5-5).

Figure 5-5 Optimization using target rate histogram.

The sensor rate profile is matched against a target rate profile. The activity of daily living (ADL) range includes moderate pacing rates between the lower rate limit (LRL) and the ADL rate. The exertion rates range from the ADL rate to the upper rate limit (URL). By comparing the sensor rate profile with the target rate profile once daily, the pacemaker automatically controls how rapidly the sensor-indicated rate increases and decreases in these ranges.

(From Leung SK, Lau CP, Tang MO, et al: An integrated dual sensor system automatically optimized by target rate histogram. Pacing Clin Electrophysiol 21:1559-1566, 1998.)

The Kappa 400 is a combined activity/MV-sensing device. The general hardware and software implementation is similar to the Kappa 700/600 series. However, actual time spent in ADL and ER is longer in the Kappa 400 because a more aggressive rate response is allowed.

St. Jude Medical (Identity, Vitality, Zephyr, Accent)

These activity devices use an Omnisense accelerometer bonded to the circuit board and are sensitive to accelerations that occur in the AP axis. Activity counts above a programmable threshold (1 = most sensitive; 7 = least sensitive) are integrated and translated to a rate response using a rate-response slope (1 = least sensitive; 16 = most sensitive) (Fig. 5-6).

Figure 5-6 Rate-response and “Auto” slopes.

A, Rate-response curves from St. Jude Medical activity sensors. B, Automatic threshold (Auto) slope ensures that about 1% of the pacing rate will reach more than 23% of the heart rate reserve (HRR) over time. Note that the sensor-driven upper rate limit (SURL) may not be reached at a low slope setting. LRL, Lower rate limit.

The threshold level can be adjusted manually or automatically (Auto). In the Auto setting, the device measures the sensor activity level over the preceding 18 hours to determine the threshold parameter. The Auto threshold can be adjusted using “Auto threshold offset.” Similarly, the slope of response can be calibrated manually or automatically. In the slope Auto adjustment, the device records the activity variance occurring above the threshold over the last 7 days, and the slope is adjusted to achieve a rate response such that almost 1% heart rate occurs beyond 23% of heart rate reserve. Typically, the slope adjusts by a factor of 2 each week. If the patient has been immobile for the previous week, as indicated by the small activity variance, the slope setting will be held constant, to avoid undue rate response when the patient resumes activity. In addition, rapid manual adjustment of the slope can be achieved by instructing the patient to perform an exercise at a prescribed slope. The Prediction Model will attempt to suggest an alternative slope based on the detected rate response. In addition, the onset and recovery kinetics are separately programmable. These devices also feature a “rest rate” that may be programmed below the LRL. The rest rate is attained when the acceleration sensor does not register significant counts (the “activity variance” level) over an extended period, implying the patient is resting or asleep.

Clinical Results of Activity Sensors

Clinical studies have demonstrated that activity-based pacing systems improve exercise capacity and reduce symptoms compared with VVI pacemakers. In an early study of a piezoelectric vibration-based sensor pacemaker, Benditt et al.⁸ compared exercise tolerance during VVI and VVIR pacing using treadmill tests. Sensor-driven pacing prolonged exercise duration by 35% and led to similar increments in peak oxygen consumption and oxygen consumption at anaerobic threshold. Activity sensor–driven pacing also reduced the patient’s perception of exertion at comparable exercise levels, and the benefit was sustained when exercise testing was repeated after an average 5 months of follow-up. Further, at follow-up exercise testing, reversion of the pacing system to a VVI mode resulted in prompt deterioration of both observed oxygen consumption and exercise duration. Crossover studies comparing VVIR mode to DDD pacing found no significant difference in symptom scores, maximal exercise performance (treadmill), or plasma concentrations of epinephrine, norepinephrine, and atrial natriuretic peptide, suggesting rate adaptation was the most important factor for exercise in the patient population studied.^9,10

In a study of the efficacy of automatic “rate profile optimization” over time, 11 patients with Kappa 700 pacemakers performed treadmill testing at 1 month, 1 year, and 2 years after implantation.¹¹ Based on the sinus profile at follow-up, a more aggressive slope was needed to match the sinus rate profile. This required a change in ADL response from 3 to 4 and in ER from 3 to 4 at 1 year, and a change in activity threshold from medium-low to low at 2 years. These adjustments enabled better approximation of pacing rate to sinus rate during treadmill exercise. Exercise capacity was maintained during the 2 years of follow-up. Variation in activity level (Activity Variance) as detected by an accelerometer is used to determine the rest rate in the St. Jude Medical devices,¹² with an overall appropriate rate response.

Limitations of Activity-Sensing Devices

Activity sensing may give inappropriate heart rate responses when subjected to environmental vibrations, such as from motor vehicle movement over rough terrain, air travel, or use of vibrating appliances or machinery. The piezoelectric vibrational sensor also responds to the application of static pressure on the pulse generator, which may cause inappropriate rate increase when the patient lies prone. This false-positive response to pressure is no longer a problem with pacemakers that incorporate an accelerometer.

The effects of various means of locomotion on pacing rate were assessed for different activity-based pacemakers.¹³ Three different activity-based pacing systems (peak counting algorithm, integration type, and accelerometers) were strapped to the chests of volunteers. Bicycling on the street resulted in higher pacing rates than did stationary bicycling for each type of pacemaker, although none of the pacemakers reached the heart rate achieved by the normal sinus node. During driving, the pacemakers increased the pacing rate, although the intrinsic sinus rate continued to be higher. In passively riding passengers, the pacemakers tended to produce a higher pacing rate than that of the normal sinus node. Independent of the sensor, activity-initiated rate response depends on the manner in which activity is performed rather than the exercise workload, and proportionality is generally limited.¹⁴ Activity sensors typically produce a higher heart rate walking downhill than uphill because of the greater force of heel-strike in the descending direction. Nonexercise stresses such as emotional changes are not detected.

Current Minute Ventilation–Sensing Devices

Clinical Experience of MV Sensor Pacemakers

Minute ventilation is an indirect but reliable marker of metabolic demand, and in the first generation of MV pacemakers (Meta MV, Telectronics), the rate response was proportional to the level of exertion and correlated with the normal sinus response.^20,21 Compared with VVI pacing, MV-based VVIR pacing increased exercise capacity by 33%,²¹ and maximal oxygen consumption and cardiac output were significantly improved. In one study of 10 patients with the first version of MV-driven VVIR pacing, pacing rate was highly correlated with measured MV (r = 0.89), respiratory quotient (r = 0.89), Vco₂ (r = 0.87), tidal volume (r = 0.87), Vo₂ (r = 0.84), and respiratory rate (r = 0.84). Maximum oxygen consumption also increased from 13.4 ± 3.4 to 16.3 ± 4.1 mL/kg/min (P = .0004) using MV-driven over VVI pacing.

Improvement in symptoms were also documented in the VVIR mode.²¹ The MV sensor has good long-term stability; programming of the sensor is relatively simple; and the rate response is appropriate during daily activities. Compared with activity pacing, MV is significantly better in achieving a near-normal pacing rate–workload relationship, whereas activity sensing tends to overpace at low-level exercise and underpace at peak exercise and in the recovery period.

Limitations of Minute Ventilation Sensing

As with all impedance systems, the MV sensor will likely be affected by electromagnetic interference, arm swinging, coughing, and hyperventilation.¹⁶ Artificial ventilation will induce an unphysiologic rate, so MV sensing needs to be disabled in such patients (e.g., general anesthesia, mechanical ventilation). The use of MV devices in patients with lung disease and heart failure remain controversial. Early generations of MV-sensing devices limited the maximum detectable respiratory rates to less than 48 to 60 breaths/min to minimize the cardiac effects of changes in impedance. Because of this filtering of the cardiac component of changes in impedance, MV sensors may not accurately reflect rate adaptation at very high respiratory rates, as may occur in children. A bipolar ventricular lead is needed for MV sensing in several models. The battery current for MV sensing may consume approximately 2% of the total current of a dual-chamber pacemaker.

Some amplifiers may sense the small impedance pulses unless preventive steps are taken. In some products, a blanking period of about 1 msec is applied to the amplifiers to “blind” them to these pulses. In other cases, special balancing of the pulse achieves the same objective.

Sensing of the impedance pulses by a surface electrocardiogram (ECG) monitor may occur, depending on the ECG machine’s frequency response as well as pulse width and balancing of the impedance pulse. Also, frequencies above a few kilohertz (kHz), such as generated by electrocautery and electrosurgery, are detected by the rate-response circuitry and could drive an MV-sensing pacemaker to its maximum rate. It is recommended that the rate-response function be inactivated whenever electrosurgery will be used. Respiration may also be influenced by phonation and coughing that have no direct relevance to change in cardiac output.

Sensor and Algorithm

The CLS sensor is based on unipolar impedance at the tip of a pacing lead.²² Subthreshold pulses of automatically selected outputs, ranging from 100 to 400 microamperes (µA), with biphasic duration of 46 msec are emitted 50 to 300 msec after a sensed or paced ventricular event. During late diastole immediately after a ventricular paced (Vp) or sensed (Vs) event, the blood volume of the right ventricle is highest and RV impedance is lowest. On the other hand, as contraction occurs, the walls surrounding the electrode tip draw closer, and impedance rises (Fig. 5-7, A). A baseline waveform will depend on the conduction state of the heart: AsVs, AsVp, ApVs, ApVp (As, atrial sensed; Ap, atrial paced event). Baseline CLS waveforms will be acquired only when the associated accelerometer indicates “no activity,” and a waveform will be discarded within 48 hours if not referenced. An average template of the baseline CLS waveform will take 2 to 3 days to optimize.

Figure 5-7 Closed-loop stimulation (CLS) sensor and algorithm.

A, Changes in CLS parameter during exercise. Hatched area represents the difference between baseline and exercise CLS waveforms and is converted to a rate using the exertion threshold rate (ETR). B, Impact of ETR on rate response of CLS. “Medium” ETR corresponds to a rate of 80 beats per minute (bpm; 20 bpm above lower rate limit). Programming this rate will ensure a rate response of 80% less than this rate and 20% above this rate. A higher or lower ETR will result in different rate responses.

As contractility increases during exercise, unipolar impedance will change. The time-integrated difference between the exercise and baseline impedance waveforms is converted to a pacing rate using an auto response factor, which is continually adapted and patient specific. The magnitude of rate response is then determined by a programmable exertion threshold rate (ETR; very low, low, medium, high, and very high) (Fig. 5-7, B). The ETR, acting through the auto response factor, will determine that 80% of the heart rate will occur below the ETR and 20% above the ETR. An active young individual will probably require a higher ETR than an inactive elderly patient. Again, the type of rate profile attained will be determined by the patient’s cardiac condition, physical state, and specific automatic response factor.

Although not strictly a dual-sensor pacemaker, the incorporated accelerometer performs an “on-off” function to decide on the acquisition of the baseline CLS waveform and the CLS-driven response. Full CLS-driven rate according to the programmed ETR will be allowed only if the accelerometer registers “exercise”; otherwise, only 20 bpm above the LRL is allowed to enable a nonexercise rate increase. In neurocardiogenic syncope, this rate-limiting algorithm can be inactivated for full overdrive response, as during a syncopal episode.

Current Closed-Loop Stimulation Devices: Biotronik (Inos, Protos, Cyclos, Entovis, Evia)

Acute measurements of the CLS parameter (previously known as “ventricular inotropic index”) were taken in 82 patients with chronically implanted unipolar ventricular leads at pulse generator replacement.²² A wide fluctuation of baseline impedance was observed (500-1500 Ω), whereas CLS fluctuated by about 4 to 25 ohms (Ω), with a good correlation between CLS and the baseline impedance. A clinical study of 205 patients evaluating the CLS pacemaker included a significant number of young subjects with complete AV block caused by Chagas’ disease.²³ Satisfactory rate modulation was reported in 93% of patients. In the remaining 7% of patients, rate adaptation could not be achieved because of poor exercise tolerance, severe myocardial dysfunction, and intermittent intrinsic AV conduction. In a multicenter study that included 178 VVIR (Biotronik Neos-PEP) and 84 DDDR (Biotronik Diplos-PEP, InosDR) devices, physiologic rate adaptation was possible in 93% and 96% of patients with these devices, respectively.²⁴ Apart from exercise rate response, this study also involved mental stress testing using color-word matching and the infusion of inotropic agents. A moderate level of rate response was documented in some patients with CLS pacemakers during these nonexercise conditions that was greater than during accelerometer-guided pacing. The benefit of CLS sensor pacing during mental stress and cognitive function has also been studied.²⁵

Considerable interest surrounds the use of the CLS sensor to detect changes in posture. Passive head-up tilt, which depletes intravascular volume, increases the inotropic state of the heart. In a multicenter study, Inotropy Controlled Pacing in Vasovagal Syncope (INVASY), 50 patients with severe vasovagal syncope and positive head-up tilt test were randomized between DDD-CLS and DDI mode at 40 bpm.²⁶ Whereas 7 of 9 patients in the DDI arm experienced syncope within 1 year, only 4 of 41 patients in the DDD-CLS arm had presyncope. The authors suggested the efficacy of this approach, although a placebo effect of pacing was suspected in 22% of patients. In 131 patients with chronotropic incompetence, CLS pacing resulted in a higher pacing rate compared with accelerometer sensor, but no difference in 6-minute walking distance (6MWD) test.²⁷ However, twice as many patients preferred the CLS mode. The use of CLS in the left ventricle, as in a CRT device for monitoring, may be a useful application of this technology (see later discussion).

Advantages and Limitations

Closed-loop stimulation appears to be a good sensor to measure cardiac contractility using a conventional ventricular pacing electrode. The demand on pacing energy is acceptable. As a contractility sensor, CLS is sensitive not only to exercise but also to nonexercise requirements, and it may therefore be used for monitoring cardiac contractility for non–rate augmentation purposes. CLS can be used only in a pacing mode that incorporates a ventricular lead. Ventricular ischemia and cardioactive medications likely influence CLS rate adaptation, although automatic adjustment may permit long-term function. A small proportion of patients are not suitable for CLS sensors because of severely impaired RV function. Such patients may be identified preoperatively, and a backup activity sensor is always available.

Sensor and Algorithm

The contractile state of the heart can be identified by the maximal velocity of shortening of unloaded myocardial contractile elements, which can be measured with a catheter tip accelerometer attached to the ventricular wall. The “peak endocardial acceleration” represents the endocardial vibration measured by the accelerometer in the right ventricle during isovolumetric contraction phase of the ventricles. This signal is closely associated with the intensity of the first heart sound. The ELA-Sorin BEST (Biomechanical Endocardial Sorin Transducer) sensor is a microaccelerometer consisting of an acceleration sensor built into a nondeformable capsule on the tip of a standard unipolar ventricular pacing lead. The lead is placed against the RV wall so as to be sensitive to its acceleration and insensitive to the pressure of blood and myocardium (Fig. 5-8). This system has a frequency response up to 1 kHz and a sensitivity of 5 mV/G (1 G = 9.8 m/sec/sec).

Figure 5-8 Biomechanical Endocardial Sorin Transducer.

The BEST sensor (Sorin Biomedica Cardio) consists of a microaccelerometer located inside a rigid capsule at the tip of a standard ventricular pacing lead, which is connected to a triple header. PEA, Peak endocardial acceleration.

In early animal experience using an external system and an implantable radiotelemetry system, the PEA was not affected by heart rate but significantly increased by emotional stress, exercise stress testing, and inotropic stimulation.²⁸ The PEA signal changes in parallel to the maximal LV dP/dt and appears to measure the global LV contractile performance rather than the regional mechanical function. The PEA signal that occurs 150 msec after the R wave corresponds to the isovolumetric contraction phase of the left ventricle (PEA-I)²⁹ (Fig. 5-9). A smaller signal also occurs in the 100-msec period after the T wave, the so-called PEA-II, which corresponds to the isovolumetric LV relaxation. PEA-II is related to peak negative dP/dt (r = 0.92) and aortic diastolic pressure (r = 0.91).³⁰ To enable the PEA sensor to be used in patients requiring an ICD lead, the sensor has been incorporated into a right atrial (RA) lead (SonR sensor). Preliminary results suggest that the SonR sensor is similar to the RV PEA signal and that it might be useful in patients receiving cardiac resynchronization therapy with defibrillation (CRT-D).²⁹ This offers the potential to measure cardiac hemodynamics in heart failure patients with an ICD.

Figure 5-9 BEST tracings.

Electrocardiogram (ECG), left ventricular (LV) dP/dt, aortic pressure (Ao Press), LV pressure, and endocardial accelerometer tracing (EA) recordings in a sheep with the BEST sensor (see Fig. 5-8). The peak of the accelerometer tracing during the isovolumic diastole (PEA-II) occurs in a 100-msec period after the T wave on the ECG.

(From Plicchi G, Mercelli E, Parlapiano M, et al: PEA-I and PEA-II based implantable haemodynamic monitor: preclinical studies in sheep. Europace 4:49, 2002.)

Current PEA Devices: BEST Sensor Rate–Adaptive Pacemakers (Sorin Best-Living Systems: Miniliving D and S)

These PEA devices use a dedicated unipolar ventricular pace/sense lead, which is IS-1 compatible. Together with the two electrodes for PEA signals, a tripolar connector is necessary. These devices also incorporate an activity sensor detecting the vibration (gravitational sensor). In the PEA mode, continuous PEA signal collected over time is used as a reference, against which the change in PEA is compared. A linear pacing rate response curve is used to relate the change in PEA signal and the rate response.

In the dual-sensor mode, the combined output from both sensors is used to drive the rate to an intermediate level, and further rate increases are guided by the PEA sensor alone. In addition, prolonged absence (about 45 minutes) of signals from both the gravitational and the PEA sensor will allow the basic rate to decrease to the programmable rest rate.

Clinical Results

Clinical studies show good correlation between the sinus rate and PEA sensor–indicated rate during daily life activities and submaximal stress testing.^31,32 Similar results were obtained in patients tested during electrophysiologic studies using an external system; changes in PEA were linearly related to the RV dp/dt during dobutamine infusion. PEA signals have been used to monitor hemodynamic function and program the A-V interval. In 13 patients with end-stage heart failure implanted with a DDD-PEA device with a custom lead arrangement, PEA level during RV, LV, and biventricular (BiV) pacing were compared.³² Both LV and BiV pacing increased stroke volume (21% and 37%, respectively) compared with RV pacing, and mean PEA changes over 15 minutes were also higher (43% and 38%). In addition, an apparent minimum PEA level at the optimal A-V interval has shown promise in automatically detecting the optimal A-V interval in a dual-chamber device.³³ The algorithm is now automatic. An increase in PEA during head-up tilt-table testing has been observed, and the use of PEA-driven overdrive pacing in patients with vasovagal syncope has been reported.³⁴ Patients randomized to DDDR have a reduced frequency of syncope compared with DDI pacing. In 15 patients with a CRT pacemaker, the PEA correctly indentified the optimal AV interval in 75% of patients.³⁵ These data suggest the potential use of PEA sensor for hemodynamic monitoring (see later).

Advantages and Limitations

PEA is a proportional sensor that shows good correlation to cardiac workload, especially at higher ranges. The PEA sensor is limited by the need for a specialized lead, leading to concerns about its long-term stability and its use at pacemaker replacement (when a standard header pacemaker is used). Development of the PEA sensor in an atrial lead allows its use in patients requiring an ICD lead.

Medtronic Pacemakers

Medtronic marketed two dual-sensor pacemakers: the combined activity and QT sensors (Vitatron) and the combined activity and MV sensors (Kappa 400). Both are no longer manufactured. In the activity/QT device, a “faster win” algorithm was used, with highest rate of two sensors used to determine actual pacing rate. Since the QT sensor is more specific for physiologic changes, an increase in activity sensor level in the absence of QT documenting exercise was used as a cross-check, resulting only in a brief and limited rate response. Using an adaptive sensor level to the SURL, the QT sensor level was continuously scaled down if, at the SURL, QT continued to shorten, suggesting the sensor level had reached the upper rate too soon. The converse was also operative. The combined sensor rate was found to be closer to the sinus rate during daily activities.³⁶

In the Kappa 400, a piezoelectric sensor is used for activity sensing, and MV is sensed from a bipolar ventricular lead. Differential sensor blending is used. Up to the ADL rate, activity input predominates, whereas MV-driven pacing will predominate at the SURL. Activity and MV sensors were checked against one another. In the absence of piezoelectric sensor indicating exercise, MV pacing only reached the ADL rate, and vice versa. Only when both MV and activity signified exercise would pacing occur above the ADL rate.

The dual-sensor rate response has been reported to be reliable for both maximal and submaximal activities, as well as resistant to nonphysiologic interference.³⁷ Compared with MV sensor alone, dual-sensor mode reduces oxygen deficit acquired during exercise by enhancing the initial rate response.³⁸ “Quantitative rate adaptation” is also superior in the dual-sensor mode.^39,40 “Rate profile optimization” was found to be a useful method for rate-adaptive programming, comparable to manual programming,⁴¹ and may be superior to accelerometer alone for rate optimization.¹¹

Boston Scientific (Insignia, Pulsar Max, Altrua)

An accelerometer activity sensor is integrated with the MV sensor, using differential sensor blending. At low heart rates, the blended sensor rate is approximately 80% accelerometer and 20% MV sensor. This ratio changes to 40%/60% near the SURL. In addition, if the MV rate is higher than the accelerometer rate, the dual-sensor rate follows the MV level. In a study involving 120 patients with Insignia, the programmed sensor modes were randomized to the accelerometer sensor alone, the MV sensor alone, or the dual-sensor mode, each for a 3-month period.⁴² Using the implanted Activity Log to determine the mean percentage and intensity of activity, quality of life (QOL), and New York Heart Association (NYHA) classes were assessed at the end of each period. Overall, either single-sensor DDDR mode improved Activity Log, QOL, and NYHA scores compared with DDD pacing, but with no difference between the two sensors. The dual-sensor mode did not improve these measurements. This study may have been limited by the prolonged, triple-crossover design but does suggest that clinical differences are likely minimal between sensors and their combinations.

The Limiting Chronotropic Incompetence for Pacemaker Recipients (LIFE) study of 1256 patients with chronotropic incompetence found that the blended sensor improved metabolic-chronotropic slope compared with the activity sensor alone⁴³ (Fig. 5-12). However, besides improved physical activity time/energy expenditure, there was no measurable difference in QOL between the blended sensor and the activity sensor alone. A prospective randomized parallel study on activity and MV with the primary outcome of Vo₂ is planned (APPROPRIATE study).⁴⁴ This study will randomize 1000 patients who will be screened for CI using a 6MWD and treadmill heart rate at 1 month. Patients with confirmed CI will have their sensors optimized with a brief walking test. Apart from Vo₂ max, rate changes during daily activities will be assessed. This study will shed light in the role of different sensors on exercise oxygen uptake. (Unfortunately, the study was prematurely terminated because of suboptimal recruitment.)

Figure 5-12 Sensors in patients with chronotropic incompetence (CI).

Overall sensor response (blended sensor [BS] and activity sensor [XL]) from 1 to 6 months in CI patients with adequate exercise tests. Blue lines indicate paired BS responses from 1 month (dashed line) to 6 months (solid line). Orange lines indicate paired XL responses from 1 month (dashed line) to 6 months (solid line). The black solid line indicates a normal metabolic-chronotropic relationship (MCR) slope; black dashed lines, 96% confidence interval CI (0.8-1.3).

(From Coman J, Freedman R, Koplan BA, et al: A blended sensor restores chronotropic response more favorably than an accelerometer alone in pacemaker patients: the LIFE study results. Pacing Clin Electrophysiol 31:1433-1442, 2008.)

ELA-Sorin (Chorus, Talent, Symphony, Rhapsody, Reply)

An accelerometer and a MV sensor are combined in these devices. Sensor blending and cross-checking are both operative to effect rate adaptation during exercise (Fig. 5-13). When the accelerometer is active but MV has not increased, as may occur at the beginning of exercise, rate response occurs according to a fixed activity response curve to a limited rate. When MV increases, rate response follows the MV sensor–driven rate. Persistent absence of accelerometer signal is considered the cessation of exercise, and this allows a decrease in the pacing rate using a recovery curve to the LRL, even though MV remains higher than baseline.

Figure 5-13 Algorithm of dual-sensor device (ELA-Sorin).

A, Combination of activity (ACT) and minute ventilation (MV) inputs during exercise. B, Autocalibration of the sensor. If the maximum sensor level is reached before the sensor-driven upper rate limit (SURL; indicated by X), then the slope is adjusted in steps to Y to match the SURL to the maximum sensor level. LRL, Lower rate limit.

A multicenter study involved 81 patients with the ELA dual-sensor pacemakers.¹⁹ In patients who underwent exercise stress testing at 1-month follow up, sensor-driven rate had good correlation with the sinus rate (r = 0.92 ± 0.07; P < .001), with the slope of linearity at 1.0 ± 0.2. Using metabolic reserve to relate to heart rate reserve, a slope of 1.1 ± 0.2 was obtained, suggesting a close relation between the dual-sensor rate and metabolic workload.

Limitations of Symptoms, Signs, and Investigations

Although the most common presenting complaint for hospitalization in ADHF patients, dyspnea occurs relatively late in relation to changes in hemodynamics and intravascular volume. Until the era of implantable devices, it was not possible to evaluate the hemodynamic changes leading to ADHF except by repeated catheterization. Adamson et al.⁶³ implanted an RV pressure sensor to measure RV systolic and diastolic pressure during heart failure exacerbation in 32 patients. They found that at a mean of 4 ± 2 days before admission, RV systolic pressure started to increase in 9 of 12 heart failure events (Fig. 5-15). As a group, RV systolic pressure increased by 25% ± 4% and heart rate by 11% ± 2% during ADHF, with substantial changes also during minor exacerbation. This study suggests that intracardiac pressure changes precede symptoms of heart failure exacerbation. Likewise, an implantable intrathoracic impedance sensor to assess pulmonary fluid showed that fluid overload occurred 18.3 ± 10.1 days before dyspnea.⁶⁴ Thus, dyspnea is a late event and does not allow either the clinician or the patient enough time for intervention to avert hospitalization.

Figure 5-15 Right ventricular (RV) sensor to measure RV pressure during heart failure exacerbation in 32 patients.

A, Pressure changes occurred in 9 of 12 events 4 ± 2 days before hospitalization (major events). B, Pressure changes before minor exacerbations (n = 24) that did not require hospitalization. Percent changes in RV systolic pressure (black circles), estimated pulmonary artery diastolic pressure (green diamonds), and heart rate (red triangles).

(From Adamson PB, Magalski A, Braunschweig F, et al. Ongoing right ventricular hemodynamics in heart failure: clinical value of measurements derived from an implantable monitoring system. J Am Coll Cardiol 41:565-571, 2003.)

The cardinal physical signs of congestive heart failure are a third heart sound, pulmonary crackles, raised jugular venous pressure, and pedal edema. However, these signs have poor sensitivity to detect heart failure. In a study of 50 patients with increased pulmonary artery wedge pressure (PAWP ≥22 mm Hg), lung crackles were identified in 19% of patients, and higher jugular venous pressure and peripheral edema were present in only 50% and 20% of patients, respectively.⁶⁵ A third heart sound was heard in most patients, but it was also detected in those with a low PAWP. This combination of signs carries a sensitivity of 58% and specificity of 100% for congestive heart failure. Physical examination of jugular pressure is difficult and often inaccurate.⁶⁶

Body weight change is both a symptom and a sign that predicts ADHF. Some suggest this may be an unreliable sign because body weight not only reflects body fluid, but also may depend on amount of food/fluid intake and other causes of weight loss or weight gain. In a recent study, 134 patients with heart failure hospitalization were compared with a case-matched group without hospitalization.⁶⁷ Body weight gain 1 week before hospitalization was associated with increasing risk of hospitalization (relative risk: Δ2-5 lb = 2.77; Δ5-10 lb = 4.46; and >10 lb = 7.65). Therefore, monitoring of body weight remains useful to identify a high-risk group for intervention and provides supportive evidence for ADHF. Radiologic evidence of ADHF tends to occur late.

Brain natriuretic peptide (BNP) has been proposed as a means to monitor and improve heart failure management. In a randomized study on the N-terminal BNP to guide heart failure therapy (TIME-CHF) study, 499 patients 60 years or older with systolic heart failure were randomized either to monitoring of BNP to maintain a level twice or less the upper limit or to conventional management without BNP guidance.⁶⁸ There was no significant difference in the probability of remaining free from all-cause hospitalization between BNP-guided and conventional therapy (41% vs. 40%). Both groups had similar quality of life (QOL). However, the secondary endpoint of heart failure hospitalization was significantly reduced (72% vs. 62%), and outcomes were better in patients age 60 to 74 but not in those 75 or older.

Although vigilant monitoring of symptoms and signs (and BNP levels) is useful, this strategy is not a guarantee for accurately predicting ADHF. On the other hand, frequent monitoring of some signs and symptoms and the use of external physiologic (and implantable) data may be superior to conventional care. A meta-analysis of both cohort (2354 patients) and randomized trials (6258 patients), with 6 to 12 months of follow-up, found a significantly lower rate of mortality and hospitalization compared with conventional management.⁶⁹ Relative reduction in heart failure hospitalization of 0.93 and 0.52 was seen in randomized and cohort studies, respectively, and mortality was reduced by 0.83 and 0.53. The Cochrane Database Systematic Review^69a reviewed 25 studies and 5 abstracts and suggested that telephone support and telemonitoring are effective in reducing all-cause mortality and heart failure hospitalization, and thus improve QOL and reduce cost and evidence-based prescribing.

Several prospective randomized studies have been published since these meta-analyses. The Randomized Trial of Phone Intervention in Chronic Heart Failure (DIAL) trial^69b randomized 1518 outpatients to either nurse-led telephone-based intervention or conventional treatment. The three main supervision areas were weight, diet, and medication compliance, and nurse specialists were allowed to change diuretic doses according to specified criteria. Patients were organized to call once every 14 days for three times, and thereafter at a frequency depending on the severity of heart failure. This protracted study followed patients up to 3 years after trial completion. The primary end point (death or heart failure hospitalization) was reduced in the intervention versus conventional arm, with the main benefit being a reduction in hospitalization (28.5% vs 35.1% at 3 years). An educational effect and adherence to the above three supervision areas are considered the main reasons for improvement.

The Telemedical Interventional Monitoring in Heart Failure (TIM-HF) trial^69c also randomized stable Class II or III heart failure patients who had a history of heart failure hospitalization within 2 years to either remote data monitoring (ECG, blood pressure, body weight) and sent these data via a personal digital assistant to the monitoring center daily, with physician-led response. Over a median follow up of 26 months, there was no difference in heart failure hospitalization or death, nor in overall QOL score. However, physical functioning was improved. The study documented an 81% compliance in ≥70% daily transmission of data.

The Telemonitoring in Patients with Heart Failure (TELE-HF) trial^69d randomized 1653 patients who had recently been admitted with ADHF. A daily telephone-based interactive voice response system on symptoms and weight was reviewed by the patients’ physicians. At the end of 180 days there was no significant difference in the primary end point of death and heart failure hospitalization between the telephone-based intervention versus the usual care group (52.3% vs 51.5%, respectively). Again, this study shows only a 55.1% adherence to interventional therapy at the end of 26 weeks in the 85.6% of patients who made at least one call.

The different efficacies of telemonitoring reported between meta-analyses and prospective studies may be attributable to differences in severity of patients involved in the studies, the types of clinical variables measured, and the intervention offered. Among these, sub-optimal compliance and lack of rapid therapeutic intervention (which often varies between studies) are important drawbacks. Furthermore, these studies have mainly been limited to easily measurable clinical variables that occur relatively late in the course of ADHF. Because many patients with LV dysfunction require cardiac implantable electronic devices (CIEDs) for arrhythmia prevention or therapy (implantable cardioverter-defibrillator, ICD) or for heart failure treatment (cardiac resynchronization therapy [CRT] or CRT-defibrillation [CRT-D]), implantable sensors for heart failure monitoring may be added in these devices. The use of implantable sensors allows continuous monitoring of physiologic parameters with less labor-intensive efforts. Furthermore, the ability of these sensors to detect earlier physiologic changes before ADHF may help prevent heart failure hospitalization. Such sensors can also measure hemodynamic values in different body positions and on an ambulatory basis, and may obviate the need for invasive monitoring on admission for ADHF therapy.

Monitoring of Pathophysiologic Changes

The three pathophysiologic areas for heart failure monitoring are electrical remodeling, mechanical remodeling, and neurohormonal changes that occur with heart failure (Table 5-6).

TABLE 5-6 Monitoring for Heart Failure Pathophysiology

ERP, Effective refractory period.

Electrical remodeling in either the atrium or the ventricle will result in changes in normal automaticity, conduction properties, and refractory period and will predispose to atrial fibrillation (AF) and ventricular tachyarrhythmias. Arrhythmias are routinely monitored and treated by CIED, either by pacing or defibrillation. The effective refractory period (ERP) can be monitored by physician-activated electrical stimulation through a programmer. Monophasic action potential duration could be assessed by telemetry in some early devices.⁷⁰ Using fractal-coated iridium electrodes, the paced unipolar ventricular signal was found to correlate with acutely measured monophasic potential. However, the implications of ERP monitoring remain uncertain. Intrachamber and interchamber conduction times in heart failure are important because they are either the result or the cause of electrical remodeling in heart failure. A wide left bundle branch block (LBBB) QRS complex is associated with ventricular dyssynchrony and impaired LV function. In a postmortem series of 34 patients with premorbid serial ECGs, progressive PR and QRS prolongation occurred with worsening of heart failure. Cardiac mass index was also significantly correlated with V1-V6 R-wave amplitudes.⁷¹ Optimal left-sided atrioventricular (AV) and cross-chamber sequencing are important for the proper systolic function of the heart (see Chapter 30). Although relatively simple, these conduction parameters have not been examined as long-term predictors of cardiac decompensation. The major development of sensors in heart failure monitoring is to track mechanical remodeling, including chamber size, pressure changes, and pulmonary congestion consequent on heart failure. Such sensors use either impedance or specialized pressure-sensing leads or devices.

A variety of neurohormonal changes result from the compensating mechanisms of heart failure. These changes are not easily measurable directly but may be reflected through heart rate variability and electrical repolarization such as the QT interval. This will be an interesting new area for monitoring and as a guide to therapy.

Feasibility Study

The long-term stability of the pressure sensor has been previously reported.^89,90 In one study, serial Swan-Ganz catheterizations at 3, 6, and 12 months after implant showed a small baseline error at 12 months of less than 1 mm Hg from the time of implantation.⁹¹ Furthermore, the accuracy of pressure measured is not affected by body posture.

As mentioned earlier, Adamson et al.⁶³ studied 32 patients with heart failure who received a Chronicle IHM and found that long-term RV pressure was stable in most patients. In some, however, it showed significant variability despite measurements being taken at 4 am with no activity level registered. During a total of 36 volume-overloaded events, RV systolic pressure increased by 25% ± 4%, heart rate by 11% ± 2%, and estimated PA diastolic pressure by 26% ± 4%. In all events, pressures were increased 1 day before the required clinical intervention. In patients with heart failure hospitalization, increases in one of the pressures occurred in 9 of 12 events, whereas this occurred in 9 of 24 patients during a nonhospitalized episode (see Fig. 5-15). During a volume-depleted state in seven patients, RV pressure parameters were reduced. All patients returned to baseline levels after therapeutic intervention. The authors further reported that sustained increase in one of the pressures (>20% from baseline) occurred in patients subsequently admitted, at a mean of 4.2 days before admission. When the device data were available to the monitoring physician, a reduction in heart failure hospitalization was subsequently observed. This important study also documents the time sequence of RV pressure changes that occurred before heart failure exacerbation, suggesting that pressures increase for several days and reduce the patient’s “tolerable reserve” before the final increase in pressures leading to clinical heart failure exacerbation.

Zile et al.⁹² compared the ongoing RV hemodynamics between patients with systolic and diastolic heart failure during heart failure events. RV diastolic pressure was elevated in both conditions, although there was a trend for more rapid RV diastolic pressure elevation to occur in diastolic heart failure with less compliant ventricles than during systolic heart failure.

Clinical Outcome Studies

The COMPASS-HF (Chronicle Offers Management to Patients with Advanced Signs and Symptoms of Heart Failure) study prospectively randomized 274 NYHA Class III or IV heart failure patients into a conventional care group or a group with therapy also guided by Chronicle-derived RV pressure parameters.⁹³ The two safety endpoints documented no pressure sensor failure and an 8% implanted system complication. During 6-month follow-up, there was a statistically insignificant trend for reduction of either heart failure hospitalization or the need of intravenous diuretics (primary endpoint) by 21%. Later analysis showed a 36% prolongation in time to the final heart failure-related hospitalization in the Chronicle-guided treatment group (Fig. 5-21). Bourge et al.⁹³ suggest that the lack of significance in the primary endpoint may be caused by the lower-than-expected number of heart failure events (predicted 1.2, actual 0.85 per 6 patient-months), thus decreasing the power of the study. The lower event rate may result from enrollment in specialized centers with high compliance for heart failure treatment. Importantly, Chronicle-guided therapy resulted in 54% more adjustment in diuretic doses, without an increase risk in hypovolemic heart failure events. The study also included 70 of 274 patients with diastolic heart failure. A subgroup analysis found a 20% nonsignificant reduction in heart failure events when diastolic heart failure patients were managed with Chronicle-guided information.⁹⁴ A large outcome study involving 850 patients with Class I to III patients with a single-lead ICD integrated with IHM using weekly transmission will examine the effect on heart failure events.^94a The Chronicle ICD (Model 7286, Medtronic, Inc) uses a single RV apical shock coil and a pressure sensor electrode in the RV outflow track for pressure measurement from which PA diastolic pressure is estimated.

Figure 5-21 Time to first heart failure hospitalization in COMPASS-HF Study.

Results showed a 33% improvement in the time to the first heart failure events. Hazard ratio (HR) from Cox proportional hazards regression model.

(From Bourge RC, Abraham WT, Adamson PB, et al: Randomized controlled trial of an implantable continuous hemodynamic monitor in patients with advanced heart failure: the COMPASS-HF study. J Am Coll Cardiol 51:1073-1079, 2008.)

Left Atrial Sensor

The PA diastolic pressure is an indirect assessment of the LV filling pressure, and measurement of left atrial (LA) pressure may reflect an earlier pressure change that triggers pulmonary congestion. This may allow a longer time window for physician intervention to avert ADHF.

The HeartPOD LA pressure monitoring device (St. Jude Medical) comprises an implantable sensor lead that is attached to a coil antenna for telemetry of sensor signals (Fig. 5-22). The sensor has a titanium pressure-sensing membrane of 3 × 7 mm and is capable of high-fidelity pressure, temperature, and EGM measurement. An external patient advisory module (PAM) sends a 125-kHz radiofrequency transmission to the antenna, which then captures 20 seconds of sensor data. The PAM has 13 megabytes of memory and can store about 3 months’ data of six recordings per day.

Figure 5-22 Left atrial (LA) pressure sensing device.

A, Patient advisory module. B, LA pressure sensing device. C, Close-up image of the sensor tip.

(From Ritzema J, Melton IC, Richards AM, et al: Direct left atrial pressure monitoring in ambulatory heart failure patients: initial experience with a new permanent implantable device. Circulation 116:2952-2959, 2007.)

In a single-center feasibility study, eight patients received the LA pressure device using a transseptal approach from the femoral vein.⁹⁵ Venous entry at 1 cm above the inguinal ligament was achieved by conventional guidewire introduction in the femoral vein below the ligament as a landmark. After standard transseptal puncture, an 11-French sheath was placed in the LA, and the sensor was deployed until the distal set of anchors was on the left side of the interatrial septum. The sheath was then removed, and the sensor membrane was positioned 1 to 2 mm on the LA septum. All patients received dual-antiplatelet therapy for 6 months (aspirin, 160 mg, and clopidogrel, 75 mg, daily). The device was calibrated over time using Valsalva maneuver, with the PAM-measured expiratory pressure to equal LA pressure. Over 6 months, the net drift was 0.2 ±1.9 mm Hg per month, although much more in one patient. The authors emphasized the need to maintain the sensor orthogonal to the septum to avoid distortion of LA pressure waveform.

The Hemodynamically Guided Home Self-Therapy in Severe Heart Failure Patient (HOMEOSTASIS) trial enrolled 40 patients with NYHA Class III to IV heart failure.⁹⁶ All patients had the LA pressure device implanted successfully, although sensor failure occurred in four, which was subsequently replaced in three patients. The study started after an initial 3-month period in which heart failure hospitalization, related events, and medications were documented. LA pressure data were then used to adjust the diuretic dosages. Survival without heart failure events occurred in 61% of patients at 3 years. Mean daily pressure therapy reduced LA pressure (from 17.6 to 14.8 mm Hg), frequency of high-pressure events (>25 mm Hg by 67%), and diuretic dosage, with better NYHA class, LVEF, and more frequent uptitration of angiotensin-converting enzyme (ACE) inhibitors.

The role of LA pressure monitoring needs to be confirmed in prospective randomized trials. At present, issues remain about sensor stability, ease of implant (subclavian implant tools are now available), and risk of thromboembolism (which is probably low and comparable to occluder for closing atrial septal defect).

Pulmonary Arterial Pressure Sensor

Diastolic PA pressure is often used as a surrogate measure of PAWP. An implantable wireless PA pressure transducer (W-IHM) has been developed (Cardio-MENS, Atlanta, GA, USA), which is capable of transmitting continuous PA pressure readings when powered by radiofrequency signal from outside (Fig. 5-23, A). In one study, the device has been shown to correlate with direct PA pressure measured invasively and with echocardiographic Doppler data.⁹⁷ The cardioMENS Heart Sensor Allows Monitoring of Pressure to Improve Outcomes in NYHA Class III Heart Failure Patients (CHAMPION)^97a,97b trial investigated the use of such a sensor in 550 patients in the U.S. Compared to 280 patients randomized to have the sensor information blinded and treated in the conventional manner, daily measurement of PA pressure with W-IHM in the 270-patient active group resulted in significant 39% reduction of heart failure hospitalizations (Fig. 5-23, B). There was no device failure, and system-related complications occurred in only eight patients, with a 1% implant related complication. All patients were either continued on warfarin or aspirin after 1 month of dual antiplatelet therapy. No episodes of pulmonary infarction or embolism were reported related to the sensor.

Figure 5-23 Wireless implantable pulmonary arter (PA) pressure sensor.

A, CardioMENS sensor for implanting in a distal branch of PA artery. B, Cumulative heart failure–related hospitalizations during entire period of randomized single-blind follow-up. C, Freedom from first heart failure–related hospitalization or mortality during the entire period of randomized follow-up.

(From Abraham WT, Adamson PB, Bourge RC, et al: Wireless pulmonary artery haemodynamic monitoring in chronic heart failure: a randomized controlled trial. Lancet 377:658-666, 2011.)

The CHAMPION study is the first large study to confirm the role of implantable pressure sensor data to reduce heart failure morbidity. Unlike telemonitoring that involves only clinical and non-invasive heart failure parameters, the invasively derived PA pressure allows the physician to adjust neurohormonal, diuretic, or vasodilator drugs, with an aim to reduce PA pressure. In addition to the primary end point of hospitalization rate, there are also encouraging secondary outcomes, such as reduction in mortality (Fig. 5-23, C), improvement in QOL, and shorter duration of heart failure–related hospitalizations. There were more changes in medications, and the benefit occurred in both the systolic and non-systolic heart failure groups. Other implanted PA pressure devices are also under development. For example, an external ultrasound-activated PA pressure sensor in the right pulmonary artery that is fixed with a self-expanding wire mesh has been tested in 31 patients with chronic heart failure (PAPIRUS study) (InPressure, Remon Medical Technologies, Boston Scientific). Pressure values are reported to be similar to Millar catheter–measured data with no short term acute issues.^97c

Device Description

The concept of impedance to monitor pulmonary congestion is based on a canine experiment.⁹⁸ The Medtronic OptiVol fluid management system uses transthoracic impedance to measure pulmonary fluid (Fig. 5-24). Low-voltage, nonstimulating currents are injected between RV ICD electrode (e.g., InSyn Sentry) or RV bipolar pacing electrode (e.g., Advisa) to the ICD or pacemaker casing between noon and 5 pm, at a time when the subject is presumably ambulant and upright. Sampling every 20 minutes is averaged to establish a baseline impedance level. The algorithm is inactive for the first 34 days after device implantation to allow time for postimplant pocket healing and electrode stabilization. When pulmonary fluid has accumulated beyond a programmable threshold, an alarm alerts the patient (or the physician via remote monitoring) (Fig. 5-25).

Figure 5-24 Intrathoracic impedance measurement by implantable system.

(From Yu CM, Wang L, Chau E, et al: Intrathoracic impedance monitoring in patients with heart failure: correlation with fluid status and feasibility of early warning preceding hospitalization. Circulation 112:841-848, 2005.)

Figure 5-25 OptiVol level changes in patient with recurrent heart failure.

At the nominal level of 60 ohms per day (Ω/day, Fluid), the algorithm detected an episode of impedance fall which was not corroborated with brain natriuretic peptide (BNP) level. A higher OptiVol threshold accurately detected all heart failure episodes.

Feasibility Studies

The feasibility of using intrathoracic impedance to monitor fluid status has been tested in 34 patients with NYHA Class III or IV heart failure in the MID-Heft Study.⁶⁴ A defibrillation lead in the RV apex was connected to a special pacemaker capable of injecting and sourcing impedance. Three impedance current vectors were tested: RV lead ring to device case and sampled from coil to device case; RV coil to device case and sampled from RV coil to device case; and RV ring electrode to device case and sampled from RV tip electrode to device case. The electrode pairs that use RV coil to device case are most suitable. An initial decrease in impedance, followed by an increase to steady state, is observed during pocket healing, which peaks by about 4 weeks.

During a follow-up period of 20 ± 8.4 months, 25 adjudicated heart failure hospitalizations occurred in 10 patients (Fig. 5-26). Intrathoracic impedance started to decrease before worsening symptoms at 15.3 ± 10.6 days, whereas dyspnea was reported, at the earliest, only 3 days before hospitalization. During 17 heart failure hospitalizations, PAWP was found to correlate significantly with impedance (r = −0.61, P < .001), and impedance increased as fluid removal occurred with diuresis (Fig. 5-27).

Figure 5-26 Intrathoracic impedance to monitor fluid status in patients with NYHA Class III or IV heart failure (MID-Heft Study).

A, Operation of algorithm for detecting decreases in impedance over time. Differences between measured impedance (bottom) and reference impedance (solid line) are accumulated over time to produce fluid index (top). Threshold is then applied to fluid index to detect sustained decreases in impedance. B, Example of impedance reduction before heart failure hospitalization (arrow) for fluid overload and impedance increase during intensive diuresis during hospitalization. Label indicates reference baseline (initial reference impedance value when daily impedance value consistently falls below reference impedance line before admission). Magnitude and duration of impedance reduction are also shown. Days in hospital are shaded.

(From Yu CM, Wang L, Chau E, et al: Intrathoracic impedance monitoring in patients with heart failure: correlation with fluid status and feasibility of early warning preceding hospitalization. Circulation 112:841-848, 2005.)

Figure 5-27 Data form heart failure patients (MID-Heft Study).

A, Example from one patient. Relationship between intrathoracic impedance, pulmonary capillary wedge pressure (PCWP), and net fluid loss (I/O) during 4 days of intensive diuresis in cardiac care unit (CCU). B, Pooled data from all patients. Relationship between intrathoracic impedance and PCWP during intense diuresis in CCU pooled from 14 heart failure hospitalizations in five patients. C, Relationship between intrathoracic impedance measurement at admission to CCU and overall amount of fluid loss that occurred during CCU stay from 17 heart failure hospitalizations in six patients.

(From Yu CM, Wang L, Chau E, et al: Intrathoracic impedance monitoring in patients with heart failure: correlation with fluid status and feasibility of early warning preceding hospitalization. Circulation 112:841-848, 2005.)

An algorithm for detection of heart failure was derived from 6.2 patient-years of monitoring from 10 patients and tested in the remaining cohort (see Fig. 5-27). Depending on the set threshold for impedance crossing, a receiver-operator curve was constructed (Fig. 5-28). Lower detection thresholds lead to higher sensitivity to detect ADHF, but also to a higher false-positive rate of detection. Conversely, a higher threshold will be more specific but may underdetect some ADHF events. A level of 60 Ω/day was suggested, to give a sensitivity of 76.9% at the cost of 1.5 false-positives per patient-year of monitoring. Early warning occurred at 13.4 ± 6.2 days of heart failure hospitalization event. This landmark study shows that intrathoracic impedance is correlated with pulmonary congestion and changes days before ADHF.

Figure 5-28 Algorithm performance on validation data set.

Detector performance curve shows trade-off between sensitivity and false-positive rate as threshold for detection changes. For validation data set, nominal threshold of 60 Ω/day resulted in sensitivity of 76.9% and false-positive rate of 1.5 false-positive per patient-year of monitoring, as highlighted by circle.

(From Yu CM, Wang L, Chau E, et al: Intrathoracic impedance monitoring in patients with heart failure: correlation with fluid status and feasibility of early warning preceding hospitalization. Circulation 112:841-848, 2005.)

Clinical Outcome Studies

The impact of automatic OptiVol alert to guide therapy was observed in 532 patients with heart failure in the Italian OptiVol Study.⁹⁹ With the OptiVol alert “on,” 67% of heart failure patients were detected who required hospitalization or therapy adjustment. Interestingly, in the patients with OptiVol alert “off,” heart failure hospitalization was significantly more frequent (20% vs. 7%). The study also showed a false-positive detection rate of 0.5 per patient-year of follow up.

Although impedance monitoring from RV coil to device case detects lung edema, measurement of RV and LV lead vectors may be able to assess LV volumes better. In 170 patients, 43 with replacement devices, Maines et al.¹⁰⁰ showed that a 12-week maturation period was required for the pocket and the leads in first-time implants. However, a similar adaptation, but stabilizing earlier, was still required for the replacement group, suggesting the adaptation partly results from the leads or algorithm itself. Using the RV-LV impedance vectors, this study suggests that significant differences exist in impedance in the volume responder versus nonresponder groups, with a higher BiV-measured impedance in the responders, indicating a role for impedance in tracking responders to CRT.

The ability of OptiVol to reflect heart failure outcome has been examined in several cohort studies. In a multicenter studies of 558 heart failures with InSync Sentry from 34 Italian centers, device-recorded OptiVol fluid index above 60 Ω/day was associated with a 36% increased risk of heart failure hospitalization over 326 ± 216 days of follow-up.¹⁰¹ Multivariate analysis showed that in addition to OptiVol level, a higher percentage of days with low activity, low HRV, and increased nighttime heart rate were independent predictions of hospitalization. In 62 patients with OptiVol algorithm, prospective observational measurements of NT-pro-BNP and clinical heart failure status were collected over 27 ± 2 weeks.¹⁰² There was a significant but weak relationship in all pooled change in impedance and change in BNP level over all the visits (r = 0.30; P < .001). However, BNP level increased significantly when an OptiVol alert was associated with clinical signs of ADHF (89 ±25% increase) versus an insignificant increase in those without signs (25% increase). In patients with an alert, BNP increased by more than 10% in most events. By the time of patient medical visit, impedance continued to fall, suggesting worsening heart failure status (Fig. 5-29). In 42% of cases, a device alert was not related to clinical signs of heart failure, although BNP overall increased by 25% in these patients. Furthermore, the number of days and the duration of time that OptiVol fluid level exceeds threshold are reported to have positive prediction of the subsequent frequency of ADHF^102a (Fig. 5-30).

Figure 5-29 Increased brain natriuretic peptide (NT-proBNP) concentration and decreasing impedance suggest worsening heart failure status.

A, Algorithm alerts and NT-proBNP changes in subcategories. Percentage of alerts associated with a decrease in NT-proBNP concentration (<−10%; n = 8), number of alerts with almost stable NT-proBNP concentration (0 ± 10%; n = 12), and number of alerts with an increase in NT-proBNP concentration (>10%; n = 32). B, Intrathoracic impedance change from the alert onset to patient evaluation in the three subgroups in A with a decreasing, stable, or increasing NT-proBNP concentration compared with the preceding visit. Upper and lower margins of the box represent the upper and lower quartiles; the line within, the median; and the whiskers, the data spread.

(From Lüthje L, Vollmann D, Drescher T, et al: Intrathoracic impedance monitoring to detect chronic heart failure deterioration: relationship to changes in NT-proBNP. Eur J Heart Fail 9:716-722, 2007.)

Figure 5-30 Comparison (Poisson regression) of acute decompensated heart failure (ADHF) hospitalization rates between groups of subjects.

A, Subjects with no intrathoracic impedance fluid index threshold crossing events (TCEs; n = 197), subjects with one to three TCEs (n = 79), and subjects with more than three TCEs (n = 28). B, Subjects with 0 (n = 1910), subjects with 1 to 30 (n = 31), and subjects with more than 30 (n = 82) intrathoracic impedance fluid index threshold crossing days per year. Error bars indicate 95% confidence intervals.

(From Small RS, Wickemeyer W, Germany R, et al: Changes in intrathoracic impedance are associated with subsequent risk of hospitalizations for acute decompensated heart failure: clinical utility of implanted device monitoring without a patient alert. J Card Fail 15:475-481, 2009.)

The usefulness of OptiVol to prevent heart failure admissions was reported in a single-center case-control study of 27 patients with InSync Sentry compared with a clinically similar group of 27 patients with CRT-D without OptiVol.¹⁰³ In patients with OptiVol monitoring, 12 of 27 had alerts resulting in intervention. Hospitalization occurred in only 1 of 27 over 1-year follow-up. In contrast, in the control patients, 7 of 27 had heart failure hospitalizations. When coupled with remote patient monitoring (Medtronic Carelink), 20 of 28 OptiVol alerts (71%) in 67 patients could be remotely managed.¹⁰⁴ In one study, crossing the OptiVol threshold (>60 Ω/day) was related to a higher risk of atrial fibrillation.¹⁰⁵ Atrial tachycardia occurred in 43% of patients before and in 29% after OptiVol level crossing. This relationship was not observed in another study, which did show a higher prevalence of ventricular tachycardia and ventricular fibrillation (VT/VF) at a lower level of OptiVol (15-45 Ω/day), suggesting VT/VF occurred at a time of volume overload.¹⁰⁶

The threshold for OptiVol alert was also tested in 115 patients implanted with the Medtronic InSync Sentry CRT-D.¹⁰⁷ During follow-up of 9 ± 5 months, 45 OptiVol alerts occurred in 30 patients; 15 alerts (33%) were correlated with clinical signs and symptoms of heart failure, and the authors suggested an increase of threshold to 90 Ω/day may increase the specificity to 73%. They found no cause for false-positive alerts, but heart failure patients had significantly higher OptiVol level versus those without. On the other hand, in the European InSync Sentry Observational Study on 373 subjects,¹⁰⁸ the level of 60 Ω/day was associated with a 60% sensitivity and 60% positive prediction of ADHF. Nine of 53 events (17%) were not associated with an OptiVol alert, and in an additional 11 events, an increase in OptiVol level occurred but did not exceed the programmed detection threshold. When compared to daily body weight measurement, OptiVol crossing has a higher sensitivity (76% vs 23%), a lower rate of unexplained detection (1.9 vs 4.3/patient-year), suggesting that impedance is a useful and better marker to weight change for heart failure monitoring.^108a These studies confirm the usefulness of intrathoracic impedance to monitor ADHF but emphasize the need for fine-tuning the detection algorithm and individual programming of OptiVol detection level.

Advantages and Limitations

Intrathoracic impedance is one of the most extensively used sensors for monitoring heart failure. Its advantages include the relative ease of instrumentation, requiring no additional leads or complex implantation. The battery energy expenditure is low. Intrathoracic impedance has been relatively well characterized in acute setting and for long-term monitoring. Although sensitive, its specificity may be limited because impedance in the vector used may be affected by clinical events that do not indicate pulmonary congestion, such as pleural effusion¹⁰⁹ (Table 5-8).

TABLE 5-8 Possible Causes of Increased OptiVol Fluid Index in Absence of Pulmonary Congestion

Unipolar Impedance from Right Ventricle

Unipolar impedance from the RV apex to the CIED casing samples a small region in the cardiac apex. This results in a signal recorded by the closed-loop stimulation (CLS) sensor (see earlier). Because most current is lost over a distance of about 1 cm from the apex, the signal reflects regional contractility of the ventricle rather than a change in stroke volume. While during acute induction of ventricular fibrillation, the fall in unipolar RV impedance reflects the fall in arterial pressure, the sensitivity is insufficient to discriminate between hemodynamically stable ventricular tachycardia and supraventricular tachycardia.¹¹¹ These results suggest that unipolar impedance reflects LV contractility only when the changes are significant, and it may not be able to detect small changes in cardiac contractility, as in heart failure monitoring.

Multipolar Impedance

Several groups and manufacturers have investigated the optimal electrode arrangement for detecting ventricular volumes. With currents flowing between intracardiac electrodes (RV, LV, and RA) and to the CIED casing, enlargement in ventricular volumes will decrease impedance as more of the heart is encompassed. Examining four intrathoracic and two intracardiac vectors in 16 dogs and five sheep, Panescu et al.¹¹² monitored cardiac function with biweekly cardiac catheterization and echocardiography and LA pressure with an implantable pressure sensor. After several weeks of high-rate pacing to induce heart failure, LVEF decreased significantly (52% to 34%), with increases in LV end-diastolic volume (65 to 97 mL), LV end-diastolic pressure (7 to 16 mm Hg), and LA pressure (7 to 26 mm Hg). Impedance value measured by all vectors decreased with the onset of heart failure (Fig. 5-31). The maximum decrease occurred with LV-can and LV-RV vectors. Importantly, LV-can impedance changes more with heart failure than vectors involving the right-sided heart electrodes (RA-can, RV-can, and RV coil-can), and RV-LV and LV-RA changes were intermediate. LA pressure correlated best with LV-can impedance (r² = 0.73) than RV-can (r² = 0.43) and RV coil-can (r² = 0.52). Circadian variation in impedance also decreased in heart failure (5% ± 2% to 2% ± 1%). Thus, in these animal models, incorporation of an LV vector significantly improved the detection of LV volume increase in heart failure.

Figure 5-31 Impedance value measured by all vectors.

Animal model shows left ventricular (LV) vector significantly improves detection of LV volume increase in heart failure. The changes in intracardiac impedance trend inversely with left atrial pressure (LAP).

(From Panescu D, Naware M, Siou J, et al: Usefulness of monitoring congestive heart failure by multiple impedance vectors. Proc IEEE Eng Med Biol Soc 2008:5668-5670, 2008.)

Biventricular impedance has been measured using a quadripolar electrode arrangement.^113,114 In nine mini-pigs with pacing-induced heart failure, biphasic pulses (15 µsec pulse width, 600 µA constant current amplitude) were injected between the RV ring and tip electrode, and impedance was sourced using the LV ring and tip electrode.¹¹⁴ The impedance signal (measured as voltage divided by 600 µA current) was recorded using 8-bite resolution, and the mean impedance was calculated over the entire cardiac cycle. “Stroke impedance” was calculated by the difference between impedance values during systole and diastole. “Systolic impedance” was defined as the highest impedance 50 to 500 msec after the R wave, whereas diastolic impedance was measured by a 20-msec window within the R wave. After 20 days of heart failure induction by rapid pacing in these animals, the increase in LV end-diastolic pressure was found to be significantly correlated with the end-diastolic impedance, which decreased by 30% (r = −0.81; P < .001). End-diastolic volume also trended in the same direction as the impedance value, which decreased by 20%. The corresponding measured intrathoracic impedance decreased by 8%, which had a poorer correlation with the end-diastolic pressure. The less striking change of intrathoracic impedance versus BiV-measured impedance might be attributed to the countering effect of lead/device casing maturation, which did not occur with BiV impedance, and pulmonary fluid collection being relatively less in the porcine model of mild heart failure studied (Fig. 5-32).

Figure 5-32 Variation in intrathoracic impedance depends on time of day.

In this animal model (pig #12), circles depict the 4-hour-averaged impedances as recorded by the pacemaker, normalized to the daily mean. Squares depict the means of summarized 4-hour averages. The line estimates diurnal variation by spline interpolation of the means.

(From Stahl C, Beierlein W, Walker T, et al: Intracardiac impedance monitors hemodynamic deterioration in a chronic heart failure pig model. J Cardiovasc Electrophysiol 18:985-990, 2007.)

These animal experiments suggest that biventricular impedance can be used to monitor the LV size and pressure changes that occur with heart failure. The theoretical advantages over transthoracic impedance are no significant time lag for lead/pocket maturation and no influence of changes in pulmonary condition on impedance values (e.g., pleural effusion, pneumonia). Because LV end-diastolic pressure increases before pulmonary edema occurs, this sensor can be used to detect deterioration of early heart failure that has not resulted in significant pulmonary fluid accumulation, and to monitor LV function. The limitations include the need for an LV lead (which restricts its use to a CRT device), dependence on the relative position of RV-LV leads (only relative changes rather than absolute value can be detected), and significant diurnal (and possibly postural) changes that must be considered in an implantable system (see Fig. 5-32).

Clinical Studies

An acute study of BiV impedance in 14 heart failure patients during implantation of a CRT device also tested the effect of different LV lead locations on BiV impedance measurements; changes in stroke volume were induced with overdrive pacing¹¹⁵ (Fig. 5-33). Data from 20 overdrive pacing episodes and six lead locations showed good correlation between measured stroke impedance and stroke volume (r = 0.82 ± 0.10) and pulse pressure (r = 0.81 ± 0.16). The authors reported no significant effect of LV lead positions on the efficacy of impedance measurement, although accuracy and signal size tended to be better in the midventricular region than in either the basal or the apical region. Lack of lead fixation was suggested for the one outlier in the study. At present, limited data are available on long-term outcome of these devices.

Figure 5-33 Biventricular (BiV) impedance in study of 14 heart failure patients.

Example of raw data recording: ECG, surface electrocardiogram; AortaP, aortic blood pressure; Z, intracardiac impedance; vertical lines 100 msec in front of QRS complex. The respiratory influence is clearly visible in the pressure and impedance tracings.

(From Bocchiardo M, Meyer zu Vilsendorf D, Militello C, et al: Intracardiac impedance monitors stroke volume in resynchronization therapy patients. Europace 12:702-707, 2010.)

Table 5-9 summarizes the relative merits and limitations of intrathoracic and biventricular (intracardiac) impedance. In patients with a suitable device (i.e., LV lead), combined transthoracic and BiV impedance likely can be used.

TABLE 5-9 Intrathoracic vs. Intracardiac (Biventricular) Impedance

CRT, cardiac resynchronization therapy; D, defibrillation ; ICD, implantable cardioverter-defibrillator; LV, Left ventricular; N/A, not available; P, pacing; RV, right ventricular.