Diagnostic capabilities of the implantable therapeutic systems

Transcription

1 Cardiac pacing 2012 and beyound Monday August 27, 2012 Diagnostic capabilities of the implantable therapeutic systems Pekka Raatikainen Heart Center Co. Tampere University Hospital and University of Tampere

2 Disclosure Speaker s bureau Boehringer Ingelheim, MSD, Sanofi Consultant Fees/Honoraria Biosense Webster, Boehringer-Ingelheim, Meda Pharma, St Jude Medical, Sanofi Research support Biosense Webster, St Jude Medical 2

3 Modern pacemakers Accurate A & V sensing Physiological pacing On demand pacing Rate response Regulation of the rate Antitachycardia pacing Collection of diagnostic information

4 Goals of pacemaker diagnostics To collect more and better information on Function and activity of the device Patient (arrhythmias, underlying disease) Alleviate the burden of the device clinics (faster follow-up with less face-to-face contact) 4

5 Information on function of the device Background information on the device and the lead(s) programmed settings Automatic up-to-date information on device longevity lead(s) performance (impedance etc.) sensing and pacing activity 5

6 Device longevity estimate Based on battery voltage battery impedance percent pacing with the programmed settings Elective Replacement Indicator warning

7 Chronic lead impedance Automatic lifetime lead impedance trends

8 Lead noise discrimination Specific lead noise discrimination provides the ability to monitor and issue alerts for early signs of lead failure

9 Non-sustained lead noise SecureSense RV Lead Noise Discrimination Algorithm compares the near field electrogram to the far field electrogram If noise is visible on the near field electrogram and not in the far field electrogram therapy is withheld If binned events are equal on both electrograms the rhythm is treated as VT/VF and therapy is delivered 9

10 Non-sustained lead noise Lead Noise True VT/VF RV Tip- RV Ring (near field) RV Coil- Can (far field) Rate Correlation Different rates Rates Correlate Failure Type Tip or ring conductor noise None Decision Inhibit therapy Deliver therapy

11 Chronic P and R wave amplitude

12 Information on sensing and pacing Event counter Atrial / ventricular sensing and pacing Biventricular pacing Ventricular premature beats Rate histograms AV conduction histograms 12

13 Event counter Detected events are classified as paced/sensed and further divided into various rate ranges 13

14 Event percentage 36.8%

15 Event and rate histograms

16 AV conduction histograms Useful for Timing optimization Evaluation of appropriate pacing function Verification that device performance matches programmed settings

17 VS-AS Interval Measures from an intrinsic ventricular event (VS) to the next intrinsic atrial event (AS) A very short VS-AS interval (<80 ms) suggests far field R wave sensing Check VS-AS interval information on the histogram screen if there are sensing problems (real or suspected) there are a lot of mode switch episodes there seems to be a lot of high-rate atrial activity there is atrial oversensing a tracing of atrial activity does not match device annotations

18 Information on cardiac arrhythmias Did that patient experience arrhythmias since the last follow-up? Is the number/duration of arrhythmias for this time period congruent with the patient s history or has something changed? What is the arrhythmia diagnosis?

19 Mode switching Fast switching to a non-p wave tracking mode after detection of high rate atrial activity 4/7 Mode Switching

20 Mode switch data Heart rate peak atrial rate ventricular rate during mode switch Episode details number and duration of episodes AF burden

21 Mode switch summary Useful for verification that mode switch settings and behavior are appropriate for the patient making adjustments (if required) to the settings

22 Stored diagnostic functions Diagnostic Function Clinical Application Limitations/pitfalls Event counters Evaluation of PM function and adjustment of programming Inappropriately sensed events affect the accuracy of the counter Cannot identify individual VT or AT episodes P & R wave amplitude histogram Optimization of A & V sensing Unable to determine if low amplitude is due to AF or true undersensing Rate histogram Optimization of rate response Identification of SN dysfunction Short arrhythmia episodes are not evident Cannot identify the type of the arrhythmia Mode switch Track occurrence of Ats followed by mode switch to a non-p wave tracking mode Undersensing may underestimate the # and duration of ATs Oversensing may trigger MS High A or V rate episodes Track occurrence of ATs and VTs Undersensing may underestimate the # and duration of tachycardias Oversensing may trigger AT/VT 22

23 Noise reaction Heart Center Tampere University Hospital 23

24 Continous arrhythmia monitoring Arrhytmia Log Duration of the arrhythmia and maximum atrial and ventricular, average ventricular, and sensor rates during the episode EGM collection triggered by either A or V high rates

25 Intracardiac ECG EGM with annotation markers

26 Rolling arrhythmia trend Arrhythmia burden

27 Ventricular rate

28 Diagnostic counters vs IEGM A total of 828 EGMs (520 automatically and 308 manually triggered episodes) were recorded in 140 patients Trigger Episodes Confirmed by EGM (%) Atrial tachyarrhythmia (ATR) (47.0%) VT 37 8 (21.6%) NSVT (27.7%) ATR = atrial tachy response (rate >160 bpm, duration 8 cycles); ventricular tachycardia (VT) (rate >160 bpm, duration 8 cycles); nonsustained ventricular tachycardia (NSVT) ( 3 consecutive ventricular extrasystoles) It is important to use IEGM to confirm that the episodes were properly diagnosed by the device 28 Raatikainen et al. unpublished

29 Automatically stored IEGM Automatically triggered IEGM showing an atrial tachycardia/fibrillation. Atrial rate is >150 bpm and ventricular rate varies due to variable atrioventricular nodal conduction block. 29

30 Automatically stored IEGM Automatically trigged EGM showing sustained ventricular tachycardia in an asymptomatic patient. 30

31 Automatically stored IEGM False-positive atrial arrhythmia detection caused by noise and myopotential artifact. 31

32 Patient initiated events Patients enrolled (n=199) Completed the protocol (n=157) Symptoms after implantation (n=55) No symptoms (n=84) No symptoms Unintentional magnet use (n=18) Arrhythmia confirmed (n=13) Applied magnet (n=48) Magnet storage overwritten by ATR (n=1) No EGM stored (n=1) No arrhytmia on EGM (n=33) 32 Raatikainen et al. unpublished

33 Patient initiated IEGM storage Magnet-triggered IEGM in a patient with palpitations. The device stored both the atrial and ventricular activity during the episode, but did not reveal any arrhythmia during the symptoms. 33

34 Patient initiated IEGM storage Magnet-triggered EGM in a patient with palpitations. The device stored both the atrial and ventricular activity during the episode and revealed premature ventricular contractions (PVC). 34

35 Clinical value of AF detection 2012;366:

36 Atrial tachycardias during the F-U Subclinical ATs occurred in 633 pts (24.5%) with no AT during the monitoring period Clinical ATs occured in 41 of the 261 patients with subclinical ATs during the monitoring period (15.7%) 71 of the 2319 patients with no ATs during the monitoring period (3.1%) 36

37 Ischemic stroke/ systemic embolism Hazard ratio 2.46 ( ), P=

38 Risk of stroke The population attributable risk of stroke or systemic embolism associated with subclinical ATs was 13% Episodes > 6 minutes vs. no episodes increased risk of ischemic stroke or systemic embolism (HR 1.76 (0.99 to 3.11); P = 0.05) Episodes > 6 hours vs. no episodes HR 2.00; 95% CI, 1.13 to 3.55; P = 0.02) Episodes > 24 hours vs. no episodes HR 1.98; 95% CI, 1.11 to 3.51; P = 0.02) 38

39 Risk according to CHADS 2 score 39

40 Risk of thromboembolic events P= % 5.0% 58 pts No AF 80 pts No AF 24 pts No AF 4 pts No AF 55 pts AF > 5 min 76 pts AF > 5 min 42 pts AF > 5 min 7 pts AF > 5 min 59 pts AF > 24 hr 113 pts AF > 24 hr 45 pts AF > 24 hr 6 pts AF > 24 hr CHADS 2 score 40 Botto et al. JCE 2009

41 Atrial fibrillation Clinically detected AF Subclinical AF can be detected using pacemaker diagnostics The higher the risk score the shorter episodes of AF have clinical impact 41

42 Information on patient activity and underlying disease Data on activity and exercise Exercicise training Heart rate variability Prediction of VT/VF episodes Congestion (fluid) monitoring Prediction of heart failure worsening ST segment (ischemia) monitoring 42

43 Activity and exercise training

44 Activity 30 day daily trend Based on accelerometer input Calibrated automatically or manual Bar graph represents hours/day active

45 Exercice training Exercise = extended activity 30 Day trend Bar graph broken into 3 zones: Mild exercise Target exercise Heavy exercise

46 Congestion monitoring 46

47 ST segment monitoring ST segment deviations are measured using a dedicated unipolar ventricular electogram EGM configuration: RV electrode tip (+) - Can (-) - cathode + anode 47

48 Baseline A qualified reference of the patient s normal IEGM Patients are their own control Collected every 6 hours in resting heart rate zone The baseline obtained by the device is used as a reference for ST Shift analysis 24 hour later 48

49 ST monitoring data ST deviation trend ST histogram ST log

50 Conclusions Device diagnostics help early detection and treatment Provides a powerful diagnostic tool for detection of subclinical atrial fibrillation and other arrhythmias, worsening of HF, myocardial ischemia... Proper use of the diagnostic capabilities of implantable devices improves patient care Potential to alleviate the burden of device clinics Stored IEGM is critical component in confirmation of the arrhythmia diagnosis 50

51 Enhanced monitoring Atrial and ventricular arrhythmias Heart rate variability Mean heart rate Myocardial ischemia % CRT Activity / 24h Thoracic Fluid (intrathoracic impedance) Hemodynamics (intracardiac impedance)