A device for monitoring the operation of leads in implantable active cardiac devices.

Abstract

The present invention provides a device for monitoring the operation of leads of an implantable active cardiac device, particularly an implantable automatic defibrillator or cardiac resynchronization defibrillator. [Solution] The present invention relates to a device comprising: a parameter determination device for determining the values ​​of a plurality of parameters that characterize a read; and a processing unit configured to determine a representative value of at least one of the plurality of parameters that characterize the read based on at least two different time scales, wherein the processing unit is further configured to compare a so-called analytical value of at least one of the plurality of parameters that characterize the read with a representative value of the parameter.

Description

Technical Field

[0001] The present invention relates to a device for monitoring the operation of a lead in an implantable active cardiac device, particularly an implantable automatic defibrillator or a cardiac resynchronization defibrillator.

Background Art

[0002] Leads are an important part of an implantable active device system. In fact, patients with an implantable active device, particularly an implantable automatic defibrillator or a cardiac resynchronization defibrillator, are at a significant risk of complications (up to 30%), most of which are related to inappropriate shocks. These shocks are often due to changes in the defibrillation lead, weakened detection of the heartbeat signal, and consideration of noise for arrhythmias.

[0003] Such problems can occur due to wear (resulting in insulation failure) due to friction between two leads, wire breakage, or poor contact between the lead tip and the heart wall due to displacement. Description of the Invention

[0004] An object of the present invention is to better predict a lead in which a problem has occurred.

[0005] This object of the present invention is achieved by a device for monitoring the operation of a lead in an implantable active cardiac device, particularly an implantable automatic defibrillator or a cardiac resynchronization defibrillator, comprising a parameter determination device for determining values of a plurality of parameters characterizing the lead. This monitoring device includes a processing unit configured to determine a value representative of at least one of the plurality of parameters characterizing the lead based on at least two different time scales. The processing unit is further configured to compare a so-called analysis value of at least one of the plurality of parameters characterizing the lead with the representative value of the one parameter.

[0006] The device is configured to detect read failures by comparing the analyzed values ​​with representative values ​​of at least one parameter characterizing the read across two different time scales.

[0007] Since the parameters used for comparison with the analyzed values ​​are the characteristics of the lead, a discrepancy between the representative value and the analyzed value indicates a problem with the lead, rather than, for example, a cardiac abnormality. In this way, this device can better predict defective leads.

[0008] Comparing two different time scales can further improve the reliability of read failure detection.

[0009] The present invention relating to a device for monitoring the operation of leads in an implantable active cardiac device can be further improved by the following embodiments.

[0010] According to one embodiment, the first representative value may be the average value of a predetermined number of representative values ​​determined before the analysis value, and this average value is compared by the processing unit.

[0011] Therefore, the first representative value is determined to represent the trend of the parameters characterizing the read prior to the analysis value. Thus, the first representative value can constitute a comparison value.

[0012] According to one embodiment, the second representative value may be the average value of a second predetermined number of representative values ​​determined before the analysis value, and this average value is compared by the processing unit, wherein the second predetermined number is greater than the first predetermined number.

[0013] In this way, two representative values ​​can be determined based on two different time scales.

[0014] By comparing analytical values ​​while considering two different time scales, the reliability of read failure detection can be further improved. In fact, the determination of read failure may depend on the time scale considered in relation to the analytical values.

[0015] According to one embodiment, the third representative value may be a rolling average based on the average of a third predetermined number of representative values ​​determined prior to the analysis value, the average of which is compared by the processing unit, and the average of the third predetermined number of values ​​corresponds to one of the plurality of parameters. A rolling average is a type of statistical average that is particularly well suited to time series analysis by suppressing transient fluctuations in order to emphasize longer-term trends.

[0016] Furthermore, this device is capable of determining three representative values ​​based on three different time scales.

[0017] According to one embodiment, the processing unit can be configured not to consider one of the values ​​of the multiple parameters that characterize the read that exceeds a predetermined limit value when determining the representative value.

[0018] In this way, values ​​that are not considered usable or that do not fall within the applicable range can be discarded. Such values ​​that are considered abnormal are beneficial to discard when determining representative values ​​in order to improve reliability.

[0019] According to one embodiment, the processing unit may be configured to compare the analytical value of at least one of the plurality of parameters characterizing the read with a value representative of the at least one parameter, such that the most recent value of the analytical value considered when determining the representative value falls within a first predetermined time interval.

[0020] In this way, a first time interval can be determined in which only values ​​for determining representative values ​​that are not considered too old for the analysis can be considered.

[0021] By doing so, the reliability of the device, and consequently, the prediction of defective leads, can be improved.

[0022] According to one embodiment, the processing unit may be configured to compare the analytical value of at least one of the plurality of parameters characterizing the read with a value representative of the at least one parameter, such that the oldest value of the analytical value considered in determining the representative value falls within a second predetermined time interval.

[0023] In this way, a first time interval can be determined in which only the values ​​necessary for determining representative values ​​can be considered by going back to events that are not considered too old for the analytical values.

[0024] By doing so, the reliability of the device, and consequently, the prediction of defective leads, can be improved.

[0025] According to one embodiment, the parameters may be those of the amplitude of the detection signal, the conductivity of the lead, the detection rate per day, the number of non-sustained ventricular fibrillation episodes, the number of untreated ventricular fibrillation episodes, the number of treated ventricular fibrillation episodes, the number of isolated premature contractions, the total number of premature contractions, the impedance of the lead, and the pacing threshold. In this way, the device is configured to determine the parameters that characterize the lead and to consider only those parameters.

[0026] According to one embodiment, the plurality of parameters characterizing the read may include at least two different parameters, and in particular at least three different parameters.

[0027] By considering two different parameters, preferably three, that characterize the lead, the reliability and sensitivity of this lead monitoring device can be further improved.

[0028] According to one embodiment, the device may further include an alarm unit that issues an alarm when the analysis value exceeds a limit value of at least one representative value of the plurality of parameters or / and increases or decreases a threshold limit of at least one parameter.

[0029] Thus, when it is determined that there is a failure in the lead when the analysis value is exceeded, the device is configured to issue an alarm. The term "threshold limit" of a parameter includes two aspects: a limit value (for example, the parameter exceeds the limit value) and a limit variation (for example, the parameter varies beyond this limit variation).

[0030] According to one embodiment, each parameter of the plurality of parameters may have a respective threshold limit, and the threshold limit is a first group of threshold limits in which the alarm unit is configured to issue an alarm when a threshold limit of one parameter is exceeded, or a second group of threshold limits in which the alarm unit is configured to issue an alarm when threshold limits of at least two different parameters are exceeded in parallel.

[0031] Thus, the present device can distinguish whether it is necessary to issue an alarm according to the parameter that exceeds the threshold limit. In this way, only alarms considered to be legitimate are issued. As described above, the term "threshold limit" of a parameter includes two aspects: a limit value (for example, the parameter exceeds the limit value) and a limit variation (for example, the parameter varies beyond this limit variation).

[0032] According to one embodiment, when the threshold limits of the parameters assigned to the second group are continuously exceeded a predetermined number of times, the threshold limits can be transferred to the first group.

[0033] Thus, it is possible to adapt the sensitivity and specificity of the alarm during the monitoring of the lead according to the fact that the identified threshold limit is exceeded.

[0034] According to one embodiment, threshold limits relating to the impedance of the lead, the conductivity of the lead, and the total number of premature contractions may be part of the first group, and threshold limits relating to the amplitude of the detection signal, the detection rate, the pacing threshold, the number of isolated premature contractions, the number of treated ventricular fibrillation, the number of persistent but untreated ventricular fibrillation, and the number of non-persistent ventricular fibrillation may be part of the second group.

[0035] Thus, the device is adapted to identify threshold limits related to parameters that are sufficient on their own to ensure that an alarm is triggered.

[0036] According to one embodiment, weighting values ​​may be assigned to each parameter of the second group, and the alarm unit may be configured to activate an alarm when the sum of the weighting values ​​of at least two parameters exceeds a predetermined number.

[0037] By weighting the parameters against each other, it is possible to determine whether the simultaneous exceeding of each threshold limit is sufficient to trigger an alarm.

[0038] According to one embodiment, the alarm unit may include a memory unit configured to store the fact that a threshold limit has been exceeded for a specified period and delete it after the expiration of this specified period.

[0039] Furthermore, by examining past events that triggered or could have triggered an alarm, it becomes possible to better predict defective reads.

[0040] According to one embodiment, one of the plurality of parameters may include a first threshold limit and a second threshold limit, wherein the first threshold limit is part of the first group and the second threshold limit is part of the second group.

[0041] Each of the threshold limits may correspond to a threshold limit associated with a different time scale, for example. Thus, the first threshold limit may be associated with discrete time values, and the second threshold limit may be associated with parameter variations.

[0042] According to one embodiment, some of the threshold limits of the second group may be linked to each other, while other threshold limits may not be linked to each other. In this way, the alarm unit may be configured to activate an alarm when the threshold limits of the second group that are not linked to each other are exceeded at least twice.

[0043] Parameter threshold limits can be linked to each other if they reflect the same problem (e.g., detection rate and detection amplitude). Therefore, exceeding two linked threshold limits is considered insufficient to trigger an alarm.

[0044] Thus, in order to trigger an alarm, it may be necessary to exceed at least two threshold limits of a second group that are not linked to each other (for example, the number of ventricular fibrillation episodes per day and the pacing threshold).

[0045] The present invention and its advantages will be described in more detail below, using preferred embodiments as examples and with reference to the accompanying drawings.

[0046] The embodiments used herein are merely examples of possible configurations, and it should be noted that when carrying out the present invention, the individual features described above may be provided independently of each other or may be omitted entirely.

[0047] Figure 1 shows an implantable active cardiac device 1 and a processing unit 2 that form a device 4 for monitoring the operation of a lead according to the present invention.

[0048] The implantable active cardiac device 1 may be an implantable automatic defibrillator or a defibrillator adapted for cardiac resynchronization.

[0049] The implantable cardiac device 1 comprises a housing 3. The housing 3 comprises, in particular, an electronic circuit and, for example, a lithium / iodine type battery. The housing 3 further comprises a connector portion 5 into which an implantable lead 7 can be inserted and screwed in.

[0050] Figure 1 shows an example of an implantable active cardiac device equipped with implantable leads 7, but it should be noted that in modified versions (not shown), multiple implantable leads can be connected to the connector portion 5 of the housing 3. The lead operation monitoring device 4 is configured for implantable active cardiac devices equipped with multiple leads. The lead operation monitoring device 4 is thus configured to determine a failure caused by frictional wear between two leads (causing at least partial loss of their insulation).

[0051] The implantable lead 7 comprises multiple electrodes 8a, 8b, and 8c. The number of electrodes shown in Figure 1 is not limited, and these constitute means for detection, pacing, and / or defibrillation in the implantable cardiac device 1.

[0052] The implantable lead 7 may be a defibrillation lead.

[0053] The embedded lead 7 is configured to measure the values ​​of several parameters that characterize the lead, such as the impedance value.

[0054] According to the present invention, a plurality of parameters characterizing the implantable lead 7 may include, at a minimum, the amplitude of the detection signal, the conductivity of the lead, the detection rate per day, the number of non-sustained ventricular fibrillations, the number of untreated ventricular fibrillations, the number of treated ventricular fibrillations, the number of isolated premature contractions, the total number of premature contractions, the impedance of the lead, and the pacing threshold.

[0055] A solitary premature contraction is defined as a cardiac cycle involving a single premature contraction.

[0056] In embodiments where the implanted lead 7 is a defibrillation lead, further parameters such as the conductivity of the defibrillation lead, the number of treated ventricular fibrillation episodes, the number of persistent but untreated ventricular fibrillation episodes, and the number of non-persistent ventricular fibrillation episodes may also be considered.

[0057] Treated ventricular fibrillation is defined as persistent ventricular fibrillation that has been treated with electrical shock.

[0058] Untreated ventricular fibrillation is defined as persistent ventricular fibrillation that has not been treated with electrical shock therapy.

[0059] Non-sustained ventricular fibrillation is defined as ventricular fibrillation that is not sustained and is not treated with electrical shock.

[0060] It should be noted that not all of the aforementioned parameters characterizing a read are available for all types of reads, and this does not affect the multifactor analysis performed by the read behavior monitoring device 4 of the present invention, as will be further explained below.

[0061] Thus, the implantable cardiac device 1 provides a parameter determination device that determines the values ​​of multiple parameters that characterize the implantable lead 7.

[0062] The length of the embedded lead 7 is omitted by the dividing line 9, indicating that it is not fully shown in Figure 1 due to the scale of the drawing.

[0063] The implantable lead 7 is connected to the connector 5 of the housing 3 by the male contact portion 11. Partial screwing or insufficient insertion of the male contact portion 11 into the connector 5 of the implantable cardiac device 1 may cause connectivity problems.

[0064] As will be described in more detail below, the device 4 for monitoring the operation of a lead according to the present invention is configured to detect this type of failure.

[0065] For this purpose, the device 4 for monitoring the operation of a read according to the present invention further comprises a processing unit 2.

[0066] The processing unit 2 may be implemented within the implantable cardiac device 1, or it may be implemented within an external device such as a computer.

[0067] The implantable cardiac device 1 and the processing unit 2 are configured to communicate with each other, for example, by telemetry 6.

[0068] The processing unit 2 is configured to determine a value representing at least one of several parameters that characterize the embedded lead 7, based on at least two different time scales, particularly three time scales. The analysis of the variation in parameter values ​​at different time scales will be further explained with reference to Figures 2 and 3.

[0069] The processing unit 2 is further configured to compare a so-called analytical value of at least one of several parameters that characterize the embedded lead 7 with a value that represents that parameter.

[0070] According to the present invention, the analysis of each parameter characterizing the embedded lead 7 can be performed according to several factors, such as a maximum or minimum threshold, an absolute upward or downward fluctuation referred to as "short-term" (e.g., over a day), an absolute or relative upward or downward fluctuation referred to as "medium-term" (e.g., over a week), and a relative upward or downward fluctuation referred to as "long-term" (e.g., over a month). The examination of parameter fluctuations will be described with reference to Figures 2, 3, and 4.

[0071] Secondly, a combination of all these analyses related to the parameters characterizing the embedded lead is performed to trigger an alarm, as described with reference to Figures 5 and 6.

[0072] Furthermore, when determining representative values, the processing unit 2 is configured not to consider one value among the multiple parameters characterizing the read that exceeds a predefined limit. Such a value exceeding the predefined limit is identified as an "unused point," that is, a point where the value is outside the usable range or cannot be used. On the other hand, if a value exceeds the maximum or minimum threshold, the value exceeding the predefined limit is identified as an "outlier point." All other values ​​that do not exceed the predefined limit are considered "normal values" and can be used for variation analysis.

[0073] By analyzing the variation between the maximum and minimum points on the same day, we analyze the variation on a first time scale called the "short term." As an example, processing unit 2 considers four impedance measurements in one day. In a variation, processing unit 2 also considers other parameters, such as the pacing threshold or the detection amplitude. The measurement unit can measure a parameter five or more times, or three or fewer times, in a single day.

[0074] The processing unit 2 further includes an alarm unit (not shown in Figure 1). The alarm unit is configured to sound an alarm when the analyzed value exceeds the limit value of at least one representative value among a plurality of parameters and / or the threshold limit of at least one parameter in an increasing or decreasing manner. The term “threshold limit” of a parameter includes two aspects: the limit value (e.g., the parameter exceeds the limit value) and the limit variation (e.g., the parameter is varying beyond this limit variation).

[0075] The processing unit 2 further includes a memory unit (not shown in Figure 1) capable of storing data.

[0076] Figure 2 shows the variability analysis using a second time scale called the "medium term."

[0077] The second time scale according to the present invention differs from the first time scale in that it represents a variation analysis that extends beyond one day, and in particular over a week.

[0078] The second, so-called "medium-term" timescale analysis (relative or absolute) is performed between the analysis point Pa and a baseline Lm, which is called the medium-term baseline.

[0079] The analysis point Pa corresponds to a point that represents the average for the day.

[0080] The baseline Lm corresponds to the number of final points n, each representing the average for the day. The baseline Lm includes only points that were classified as "normal". Points A1, A2, and A3 in Figure 2 are excluded from this baseline Lm because they each have values ​​exceeding the maximum threshold (the dotted line extending horizontally in Figure 2). Points exceeding the minimum threshold can similarly be excluded from the baseline Lm.

[0081] Since the baseline Lm is the "medium-term" (i.e., weekly) baseline Lm, the medium-term baseline Lm corresponds to the last 7 points Pm1 through Pm7 that were deemed normal for the baseline Lm. As explained above, each of the 7 points Pm1 through Pm7 corresponds to the daily average.

[0082] In the example in Figure 2, Pm1 represents the most recent point on the medium-term baseline Lm relative to the analysis point Pa. On the other hand, Pm7 represents the oldest point on the medium-term baseline Lm relative to the analysis point Pa.

[0083] To avoid comparing the analysis point Pa with events considered too old, a first time interval Δm1 can be defined between the analysis point Pa and the most recent point Pm1 of the medium-term baseline Lm. This first time interval Δm1 may correspond to 7 days. Otherwise, the variation analysis can be suspended.

[0084] Furthermore, a second time interval Δm2 may be defined between the most recent point Pm1 of the medium-term baseline Lm and a baseline Lm point Pm that corresponds to the oldest point of the medium-term baseline Lm. This second time interval Δm2 may correspond to 14 days. Otherwise, the variation analysis can be suspended.

[0085] Figure 3 shows an analysis of value fluctuations on a third time scale, referred to as the "long term."

[0086] The processing unit 2 of the device 4 for monitoring the operation of a read according to the present invention examines the signal S obtained by the parameter determination device of the monitoring device 4. This signal S may be a raw signal or a signal processed by a known filtering means.

[0087] The processing unit 2 is configured to calculate a rolling average (particularly over 7 points) for the signal S. The curve Cm in Figure 3 represents the averaged curve obtained in this way. By averaging, it is possible to avoid changes caused by so-called "short-term" fluctuations, such as daily fluctuations.

[0088] The curve Cm in Figure 3 corresponds to the curve considered for variability analysis on a third time scale, known as the long term.

[0089] Because averaging causes a shift, the focus of curve Cm can be readjusted over a three-day period.

[0090] The curve Cm shown in the example in Figure 3 is a downward curve. In one embodiment, the curve Cm can be an upward curve.

[0091] For the variation analysis on the second time scale, as explained with reference to Figure 2, points considered abnormal were excluded before the averaging operation. Points considered normal correspond to the weekly average.

[0092] As shown in Figure 3, a predetermined time interval Δl1 may include the last seven points Pl1 through Pl7 that are considered normal. The first point Pl1 corresponds to the analysis point Pa, and point Pl7 corresponds to the oldest point relative to the analysis point Pa.

[0093] As shown in Figure 3, a first time interval Δl1 is defined between the analysis point Pa and the most recent point Pl7 of the long-term baseline Ll, in order to avoid comparing the analysis point Pa with events that are considered too old. This first time interval Δl1 may correspond to 7 days. Otherwise, the variation analysis may be suspended.

[0094] In this way, by limiting the predetermined time interval Δl1 to the last 7 points that are most recent with respect to the analysis point Pa, it is impossible for more than 7 points to exist between the analysis point Pa and the last point Pl7, thus avoiding the need to compare the maximum or minimum values ​​of a week for events that are considered too old.

[0095] Points Pl1 through Pl7 within a given time interval Δl1 are compared to a so-called long-term baseline Ll.

[0096] In the example in Figure 3, the so-called long-term baseline Ll corresponds to the last 28 points on the curve Cm that are considered normal, prior to point Pl7. Therefore, the so-called long-term baseline Ll in the example in Figure 3 is located between point Pl7 and point Pl35.

[0097] In one modified version of the present invention, the so-called long-term baseline Ll may consist of more than 28 points, or less than 28 points, which is at least more points than the so-called medium-term baseline Lm.

[0098] In one variation, the so-called long-term baseline Ll is never composed of more than 56 points in order to avoid considering events that are considered too old.

[0099] Variation analysis on a third time scale, referred to as "long-term," is performed between the maximum, minimum, or mean value of points considered normal in a given time interval Δl1 and the maximum, minimum, or mean value of points considered normal in the long-term baseline Ll or the given time interval Δl3. Points on the curve Cm included in the given time interval Δl1 are compared with points on the curve Cm included in the given time interval Δl2 or Δl3.

[0100] The given time interval Δl2 includes the points between Pl7 and Pln, where Pln corresponds to the oldest point relative to Pa. In Figure 3, Δl2 represents the interval containing 56 points between Pl7 and Pln.

[0101] A given time interval Δl3 includes the seven oldest points considered normal on the curve Cm, which starts at point Pl35, the oldest point of the long-term baseline. In the example in Figure 3, the given time interval Δl3 thus includes points Pl28 through Pl35.

[0102] As shown in the example in Figure 3, when the curve Cm is descending, the minimum value from point Pl1 to Pl7 in a predetermined time interval Δl1 can be compared with the maximum value from point Pl28 to Pl35 in a predetermined time interval Δl3.

[0103] In one modified example, the average value of points Pl1 to Pl7 in a predetermined time interval Δl1 may be compared with the average value of points Pl28 to Pl35 in a predetermined time interval Δl3.

[0104] Figures 4a and 4b show flowchart 100 illustrating the analysis of variations and thresholds at three different time scales according to the present invention. Flowchart 100 is shown in two figures, 4a and 4b, solely for the purpose of making the diagrams easier to understand. Figure 4b shows a continuation of the steps shown in Figure 4a. Following step 114 in Figure 4a, step 116 shown in Figure 4b is performed.

[0105] Flowchart 100 includes steps performed by the processing unit 2 of the device 4 that monitors the operation of the lead of the implanted active cardiac device 1 described above. Therefore, it includes a variation analysis of the value of one parameter that characterizes the implanted lead 7. As a result, a detailed explanation of the elements with the same reference numerals already used for the explanation of Figures 1 to 3 will not be repeated, so please refer to the explanation above.

[0106] In the first step 102 of the variation analysis, the analysis point Pa is examined by the processing unit 2.

[0107] In step 104, it is determined whether the value of analysis point Pa corresponds to an usable value. If the value of analysis point Pa exceeds a predefined limit, it is designated as an "unusable point," meaning the value is outside the usable range or the value cannot be used. In this case, the analysis is interrupted in step 105. Subsequently, in step 130, the following points are considered as analysis point Pa.

[0108] If the value of analysis point Pa is deemed usable, the analysis will continue.

[0109] In step 106, it is determined whether the value of analysis point Pa corresponds to a value that can be considered a "normal value". For this purpose, the value of the analysis point is compared to a predefined limit, maximum, or minimum threshold. If the value of analysis point Pa exceeds the predefined maximum or minimum threshold, the value of analysis point Pa is considered abnormal. In this case, a notification indicating that the threshold has been exceeded is issued in step 107, and thereafter, the next point is considered as analysis point Pa.

[0110] If the value at analysis point Pa is deemed normal, proceed to step 130 to continue the analysis.

[0111] In step 108, it is determined whether the variation on the first time scale exceeds a predetermined threshold limit, essentially a variation limit. The first time scale may refer to one day. The variation on the first time scale corresponds to the variation between the maximum and minimum points on the same day.

[0112] If a predetermined threshold is actually exceeded for the first time scale, a notification indicating that the fluctuation has been exceeded is issued in step 109.

[0113] Regardless of whether a predetermined threshold was exceeded for the first time scale in step 108, step 110 establishes a baseline for the second time scale. This second time scale is different from the first time scale. The second time scale may also be a week.

[0114] In step 112, it is determined whether the number of days between the analysis point Pa and the most recent point Pm1 of the baseline Lm of the second so-called "medium-term" scale (see Figure 2) falls within a predefined time interval Δm1. Preferably, Δm1 is equal to 7 days.

[0115] If not included, the analysis is terminated in step 113. Subsequently, in step 130, the following points are considered as analysis point Pa.

[0116] Otherwise, continue the analysis.

[0117] In step 114, it is determined whether the number of days between the most recent point Pm1 and the oldest point Pm of the baseline Lm of the second so-called "medium-term" scale (see Figure 2) falls within a predefined time interval Δm2. Preferably, Δm2 is equal to 14 days.

[0118] If not included, the analysis is terminated in step 115. Subsequently, in step 130, the following points are considered as analysis point Pa.

[0119] Otherwise, continue the analysis.

[0120] In step 116, it is determined whether the variation on the second time scale exceeds a predetermined threshold limit, essentially a variation limit.

[0121] If a predetermined threshold is actually exceeded for the second time scale, a notification indicating that the variability has been exceeded is issued in step 117.

[0122] Regardless of whether a predetermined threshold was exceeded for the second time scale in step 116, step 118 establishes a baseline for the third time scale. This third time scale is different from the first and second time scales. The third time scale may also be one month, and is considered "long term."

[0123] In step 120, the mean of the seven oldest points of the so-called long-term baseline Ll (the mean of the seven points starting from the oldest point of the so-called long-term baseline Ll (see Figure 3)) is determined. In one modified example, in step 120, the maximum or minimum point of the seven oldest points of the so-called long-term baseline Ll may be determined.

[0124] In step 122, it is determined whether the number of days between the analysis point Pa corresponding to the most recent point Pl1 and the oldest point Pl7 considered for analysis on the third time scale (see Figure 3) falls within a predefined time interval Δl1. Preferably, Δl1 is equal to 7 days.

[0125] If not included, the analysis is terminated in step 123. Subsequently, in step 130, the following points are considered as analysis point Pa.

[0126] Otherwise, continue the analysis.

[0127] In step 124, it is determined whether the number of days between the most recent point PI7 and the oldest point Pl35 of the baseline Ll of the so-called "long-term" third scale (see Figure 3) falls within a predefined time interval Δl2. Preferably, Δl2 is equal to 56 days.

[0128] If not included, the analysis is terminated in step 125. Next, in step 130, the following point is considered as the analysis point Pa.

[0129] Otherwise, continue the analysis.

[0130] In step 126, it is determined whether the variation on the third time scale exceeds a predetermined threshold limit, essentially a variation limit.

[0131] If a predetermined threshold is actually exceeded for the third time scale, a notification indicating that the fluctuation has been exceeded is issued in step 127.

[0132] Otherwise, no notification will be given in step 128.

[0133] In either case, regardless of whether the predetermined threshold is exceeded, step 130 continues the analysis by considering the following points as analysis points Pa.

[0134] Therefore, the variation analysis shown in flowchart 100 includes a continuous variation analysis across different time scales, from the shortest time scale to the longest time scale.

[0135] Figure 5 shows flowchart 300 related to the activation of alarms in response to notifications issued in steps 107, 109, 117, and 127 of flowchart 100.

[0136] Flowchart 300 includes steps performed by the processing unit 2 of the device 4 that monitors the operation of the leads of the implanted active cardiac device 1 described above. As a result, a detailed explanation of the elements with the same reference numerals already used for the explanation of Figures 1 to 4 will not be repeated, so please refer to the explanation above.

[0137] Flowchart 300 shows how the various notifications previously issued in steps 107, 109, 117, and 127 of Flowchart 100 are combined to optimize the sensitivity and specificity of the alarms sent to physicians. In other words, the goal is to trigger only legitimate alarms.

[0138] According to the present invention, a notification is different from an alarm. An alarm is communicated to a physician from the outset, for example, by a visual or auditory message, to indicate a possible lead failure. A notification is not necessarily communicated to a physician. However, as described below, an alarm can be triggered by the simultaneous occurrence of notifications.

[0139] Thus, while an immediate alarm can be triggered by analyzing values ​​that exceed or fall below a certain threshold limit (for example, in the case of impedance or conductivity), analysis of fluctuations in the same parameter requires a notification step.

[0140] The processing unit 2 of the monitoring device 4 of the present invention can consider two types of notifications: namely, notifications of fluctuations (step 301) and notifications of thresholds (step 302).

[0141] As explained with reference to step 107 in Figure 4a, the threshold notification corresponds to the value of analysis point Pa exceeding the threshold limit.

[0142] As explained with reference to step 109 in Figure 4a and steps 117 and 127 in Figure 4b, the notification of variation corresponds to exceeding the threshold limit due to a time-scale variation in the value of the parameter characterizing the embedded read 7.

[0143] For each parameter characterizing the embedded lead 7, at least one threshold limit is determined.

[0144] Multiple threshold limits can be determined for the same parameter. Thus, the parameter has a first threshold limit that triggers a notification when exceeded, and a second threshold limit that triggers an alarm when exceeded.

[0145] According to the present invention, the threshold limits of the parameters characterizing the reads can be classified into two groups.

[0146] The first group comprises threshold limits for which the alarm unit of the monitoring device 4 is configured to issue an alarm when the threshold limit of one parameter is exceeded. For example, thresholds for lead impedance, lead conductivity, and the total number of premature contractions belong to the first group.

[0147] The second group comprises threshold limits for which the alarm unit of the monitoring device 4 is configured to issue an alarm if at least two different parameters are exceeded in parallel. For example, threshold limits for the amplitude of the detected signal, the detection rate, the pacing threshold, the number of isolated premature contractions, the number of treated ventricular fibrillation episodes, the number of persistent but untreated ventricular fibrillation episodes, and the number of non-persistent ventricular fibrillation episodes belong to the second group.

[0148] Furthermore, if the threshold limit of a parameter assigned to the second group is exceeded a predetermined number of times consecutively, this threshold limit can be transferred to the first group.

[0149] Furthermore, it should be noted that the threshold limit for issuing an alarm can change. For example, in the case of left ventricular lead impedance, a lower threshold limit may be required for unipolar vectors than for bipolar vectors.

[0150] As shown in Figure 5, if it is detected in step 302 of flowchart 300 that a threshold notification has been issued (step 107 of flowchart 100), then in step 304, it is determined whether the issued threshold notification relates to a parameter value classified into the first group.

[0151] If this is the case, this condition is sufficient for the alarm unit of the monitoring device 4 to issue an alarm in step 306. As explained earlier regarding the threshold limits of the first group, an alarm can be immediately issued by analyzing values ​​that exceed the threshold limits (for example, in the case of impedance or conductivity). Thus, a value of a certain parameter that is very high or very low (for example, the impedance of the lead exceeds 2000 ohms) is a characteristic that indicates a problem with the lead (for example, a break). Therefore, this factor alone is sufficient to trigger an alarm indicating a possible lead failure.

[0152] Otherwise, in step 308, it is checked whether the issued threshold notification pertains to a parameter that includes a second threshold limit, and if that threshold limit is exceeded, an alarm may be triggered. In fact, as described above, some parameters (e.g., total premature contractions) have a first threshold limit that, if exceeded, triggers a notification, and a second threshold limit that, if exceeded, triggers an alarm. In this case, in step 310, it is checked whether the value of the analysis point exceeds the second threshold limit. If it does, an alarm is triggered in step 306.

[0153] The following describes cases in which an alarm can be issued independently, other than the notifications mentioned above.

[0154] As shown in flowchart 300, in step 301, notification of a change in one parameter is not sufficient on its own to trigger an alarm.

[0155] Therefore, this parameter must have at least a second parameter in parallel in order to trigger the alarm.

[0156] Thus, in step 312, it is determined whether a notification regarding the second parameter has been detected in parallel with the notification in step 301. This second parameter may also be insufficient if it reflects the same problem (for example, detection rate and detection amplitude). In that case, the first and second parameters are considered to be "linked".

[0157] Therefore, in step 314, it is determined whether or not the first parameter and the second parameter are linked.

[0158] If they are not linked to each other, the alarm is triggered in step 306 by the parallel occurrence of a notification for the first parameter and a notification for the second parameter (the second parameter is not linked to the first parameter).

[0159] Therefore, at least one unlinked second parameter is needed to trigger an alarm, such as the number of ventricular fibrillation episodes per day or the pacing threshold.

[0160] In Figure 6, the sets of parameters that characterize a lead and are therefore insufficient to trigger an alarm are shown by shaded boxes, and will be explained further below.

[0161] Thus, three sets of "linked" parameters are defined. The first set corresponds to the number of detections per day and the amplitude of the wave. The second set corresponds to persistent episodes and untreated episodes. Furthermore, the third set corresponds to isolated premature contractions and total premature contractions.

[0162] If it is determined in step 314 of flowchart 300 that the two parameters are linked, or if a notification for the second parameter was not detected concurrently in step 312, then in step 316, it is determined whether or not the notification for the first parameter (as in step 301) is triggered daily.

[0163] Therefore, the notification regarding the first parameter is stored in the memory section of the processing unit 2.

[0164] Note that the analysis of different parameters is performed simultaneously. When one parameter issues a notification, that notification is valid for a predetermined period, for example, 7 days.

[0165] If notifications are issued for several consecutive days, they remain in effect for seven days from the end of each period.

[0166] If multiple notifications for different parameters are enabled simultaneously (i.e., concurrently), this may trigger an alarm.

[0167] This parallel alarm system makes it possible to detect faults that may occur at different times and in different ways.

[0168] Step 318 determines whether the notification was activated more than 7 days ago. If it was more than 7 days ago, step 320 invalidates (deactivates) the notification. Otherwise, step 322 continues the analysis and considers the following points.

[0169] Figure 6 shows a table that weights the degree of satisfaction of each notification.

[0170] In particular, in step 314 of flowchart 300, a weighting scheme for each pair is implemented in order to calculate the degree of satisfaction of the notifications with one another.

[0171] All notifications regarding parameters that characterize leads displayed per day are categorized alphabetically.

[0172] The hatched boxes in Figure 6 represent one notification, not two notifications originating from the same parameter, such as variations of the same parameter at two different scales.

[0173] The "weights" assigned to each group in the table are added together. If the result of this addition is greater than 3 and different from 3, an alarm is issued in step 306 of flowchart 300 (see Figure 5).

[0174] Furthermore, you need to proceed to the row for the first parameter and add the weights of each of the formed sets to the respective weights of the first parameter (shown in hatched boxes). An example is given below.

[0175] In the first example, the first parameter corresponds to impedance and the second parameter corresponds to the pacing threshold. In the first example, we first need to go to the impedance row and add the weight of each impedance (2 (see hatched box)) and the weight of the pair formed by the pacing threshold (4). Since the result of the addition, 6, is greater than 3, an alarm is triggered.

[0176] In the second example, the first parameter corresponds to the signal amplitude, and the second parameter corresponds to the daily rate of detected signals, i.e., the daily rate of spontaneous rhythm signals. Therefore, in the second example, we need to go to the wave amplitude row and add the weight of each wave amplitude (2 (see hatched box)) and the weight of the set formed by the detections per day (1). Since the result of the addition is equal to 3, no alarm is triggered.

[0177] In one embodiment of the present invention, a device that monitors the behavior of a read considers at least two different parameters that characterize the read.

[0178] In another embodiment of the present invention, the device for monitoring the behavior of a read considers at least three different parameters that characterize the read. Thus, a third example of considering three different parameters is described below.

[0179] In the third example, the first parameter corresponds to the wave amplitude, the second parameter to the number of detections per day, and the third parameter to the conductivity. Therefore, in the third example, we need to go to the row for wave amplitude and add the weights for each wave amplitude (2 (see hatched box)), the weight of the pair formed by the number of detections per day (1), and the weight of the pair formed by the conductivity (4). The result of the addition is equal to 7, which is greater than 3, so an alarm is triggered.

[0180] Thus, in this invention, in order to better predict the failure of the embedded lead, several (electrical and rhythmic) parameters characteristic of the embedded lead can be examined on different time scales. [Brief explanation of the drawing]

[0181] [Figure 1] The device for monitoring operation according to the present invention is shown. [Figure 2] This section presents an analysis of parameter variations on a second time scale, referred to as the "medium term." [Figure 3] This section presents an analysis of parameter fluctuations on a third time scale, referred to as the "long term." [Figure 4a] The first part of a flowchart relating to the analysis of parameter value fluctuations at three different time scales according to the present invention and notifications is shown. [Figure 4b] The second part of the flowchart shown in Figure 4a is shown here. [Figure 5] This is a flowchart relating to the activation of an alarm as a notification function according to the present invention. [Figure 6] A table is shown to weight the degree of satisfaction of each notification.

Claims

1. A device for monitoring the operation of leads of an implantable active cardiac device, particularly an implantable automatic defibrillator or cardiac resynchronization defibrillator, A parameter determination device that determines the values ​​of multiple parameters that characterize the read, A processing unit configured to determine a representative value of at least one of the plurality of parameters that characterize the read based on at least two different time scales, Equipped with, The processing unit is further configured to compare a so-called analytical value of at least one of the plurality of parameters characterizing the read with a representative value of the parameter. Device.

2. A device for monitoring the operation of a lead in an implantable active cardiac device according to claim 1, wherein the first representative value is the average value of a first predetermined number of representative values ​​determined prior to the analysis value, and the average value is compared by the processing unit.

3. The device for monitoring the operation of a lead in an implantable active cardiac device according to claim 2, wherein the second representative value is the average value of a second predetermined number of representative values ​​determined prior to the analysis value, the average value is compared by the processing unit, and the second predetermined number is greater than the first predetermined number.

4. A device for monitoring the operation of a lead of an implantable active cardiac device according to any one of claims 1 to 3, wherein the third representative value is a rolling average value based on the average value of a third predetermined number of representative values ​​determined prior to the analysis value, the average value is compared by the processing unit, and the average value of the third predetermined number of values ​​corresponds to one of the plurality of parameters.

5. The device for monitoring the operation of a lead of an implantable active cardiac device according to any one of claims 1 to 4, wherein the processing unit is configured not to consider one value among the values ​​of the plurality of parameters that characterize the lead that exceeds a predetermined limit value when determining the representative value.

6. The processing unit is configured to compare the analytical value of at least one of the plurality of parameters characterizing the lead with a value representative of the at least one parameter, and the most recent value of the analytical value considered in determining the representative value falls within a first predetermined time interval, as described in any one of claims 1 to 5, for monitoring the operation of a lead in an implantable active cardiac device.

7. The processing unit is configured to compare the analytical value of at least one of the plurality of parameters characterizing the lead with a value representative of the at least one parameter, and the most recent value of the analytical value considered in determining the representative value falls within a second predetermined time interval, as described in any one of claims 1 to 6, for monitoring the operation of a lead in an implantable active cardiac device.

8. A device for monitoring the operation of a lead in an implantable active cardiac device according to claims 1 to 7, wherein the parameter is one of the following parameters: amplitude of the detection signal, conductivity of the lead, detection rate per day, number of non-sustained ventricular fibrillation episodes, number of untreated ventricular fibrillation episodes, number of treated ventricular fibrillation episodes, number of isolated premature contractions, total number of premature contractions, impedance of the lead, and pacing threshold.

9. A device for monitoring the operation of a lead in an implantable active cardiac device according to any one of claims 1 to 8, wherein the plurality of parameters characterizing the lead include at least two different parameters, in particular at least three different parameters.

10. A device for monitoring the operation of a lead of an implantable active cardiac device according to any one of claims 1 to 9, further comprising an alarm unit that issues an alarm when the analyzed value exceeds a limit value of at least one representative value among the plurality of parameters and / or a threshold limit of at least one parameter in such a way that it increases or decreases the limit.

11. Each of the aforementioned multiple parameters has one threshold limit. The threshold limits are grouped into a first group of threshold limits, in which the alarm unit is configured to issue an alarm when the threshold limit of one parameter is exceeded, or a second group of threshold limits, in which the alarm unit is configured to issue an alarm when the threshold limits of at least two different parameters are exceeded in parallel. A device for monitoring the operation of the leads of an implantable active cardiac device according to claim 10.

12. A device for monitoring the operation of a lead of an implantable active cardiac device according to claim 11, wherein if the threshold limit of a parameter assigned to the second group is exceeded for a predetermined number of consecutive times, the threshold limit is moved to the first group.

13. The impedance of the lead, the conductivity of the lead, and the threshold limits related to the total number of premature contractions are part of the first group. The threshold limits related to the amplitude of the detected signal, the detection rate, the pacing threshold, the number of isolated premature contractions, the number of treated ventricular fibrillation episodes, the number of persistent but untreated ventricular fibrillation episodes, and the number of non-persistent ventricular fibrillation episodes are part of the second group. A device for monitoring the operation of the leads of an implantable active cardiac device according to claim 11 or 12.

14. Weight values ​​are assigned to each parameter of the second group described above. The alarm unit is configured to activate an alarm when the sum of the weighting values ​​of at least two of the aforementioned parameters exceeds a predetermined number. A device for monitoring the operation of a lead in an implantable active cardiac device according to any one of claims 11 to 13.

15. The alarm unit comprises a memory unit configured to store the fact that a threshold limit has been exceeded for a specified period and delete it after the expiration of the specified period, wherein the device monitors the operation of a lead in an implantable active cardiac device according to any one of claims 11 to 14.

16. One of the aforementioned multiple parameters includes a first threshold limit and a second threshold limit. The aforementioned first threshold limit is part of the aforementioned first group, The aforementioned second threshold limit is part of the aforementioned second group. A device for monitoring the operation of a lead in an implantable active cardiac device according to any one of claims 11 to 15.

17. A device for monitoring the operation of leads of an implantable active cardiac device according to any one of claims 11 to 16, wherein some of the threshold limits of the second group are linked to each other, and other threshold limits are not linked to each other, and the alarm unit is configured to activate an alarm when the threshold limits of the second group that are not linked to each other are exceeded at least twice.

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