Performance of a multisensor implantable defibrillator algorithm for HF monitoring in presence of comorbidities

Background

Cardiovascular and non-cardiovascular comorbidities are common in heart failure (HF) patients and impact disease severity and prognosis. Select modern implantable defibrillators (ICDs) are equipped with multisensor algorithms for HF monitoring. The HeartLogic index combines multiple ICD-based sensor data (heart rate, heart sounds, thoracic impedance, respiration, activity), and the associated alert has proved to be a sensitive and timely predictor of impending HF decompensation in cardiac resynchronization therapy (CRT-D) patients The algorithm was developed using data from CRT-D patients; the performance in non-CRT ICD patients and the impact of selected comorbidities on performance requires further study.

Methods

The HeartLogic feature was activated in 568 ICD patients (410 with CRT) from 26 centers. The median follow-up was 25 months [25th–75th percentile: 15–35].

Results

During follow-up, 97 hospitalizations were reported (53 cardiovascular) and 55 patients died. We recorded 1200 HeartLogic alerts (0.71 alerts/patient-year) in 370 patients. Overall, the time IN the alert state was 13% of the total observation period. The rate of cardiovascular hospitalizations or death was 0.48/patient-year (95% CI: 0.37–0.60) with the HeartLogic IN alert state and 0.04/patient-year (95% CI: 0.03–0.05) OUT of alert state, with an incidence rate ratio of 13.35 (95% CI: 8.83–20.51, p<0.001). Among patient characteristics, atrial fibrillation (AF) at implantation (HR: 1.62, 95% CI: 1.27–2.07, p<0.001) and chronic kidney disease (CKD) (HR: 1.53, 95% CI: 1.21–1.93, p<0.001) independently predicted alerts. HeartLogic alerts were not associated with CRT vs. non-CRT device implantation (HR: 1.03, 95% CI: 0.82–1.30, p=0.775). The comparisons of the clinical event rates in the IN alert state with those in the OUT of alert state yielded incidence rate ratios ranging from 9.72 to 14.54 (all p<0.001) in all groups of patients stratified by: CRT/non-CRT, AF/non-AF, CKD/non-CKD. Indeed, after multivariate correction for CKD and AF at implantation, the time IN the HeartLogic alert state >13% was associated with the occurrence of the combined endpoint of cardiovascular hospitalization or death (HR: 2.54, 95% CI: 1.61–4.01, p<0.001).

Conclusions

The burden of HeartLogic alerts appears similar between CRT and non-CRT patients, while patients with AF and CKD seem more exposed to alerts. Nonetheless, the ability of the HeartLogic algorithm to identify patients during periods of significantly increased risk of clinical events is confirmed regardless of the type of device, the presence of AF, or CKD.

Funding Acknowledgement

Type of funding sources: None.

Ventricular tachycardia channels ablation incorporating automated high-density mapping guidance: data from the CHARISMA registry

Funding Acknowledgements

Type of funding sources: None.

Background

Ventricular tachycardia (VT) ablation targeting conducting channels (CC)s based on timing of late potentials (LPs) during sinus rhythm (dechanneling) may facilitate a scar homogenization strategy without the need for extensive ablation and possibly lead to higher successful rate.

Purpose

We evaluated the feasibility and safety of a CC identification and ablation approach by means of an ultra-high density mapping system with a novel automated algorithm in ischemic VT procedures.

Methods

Consecutive patients indicated for ischemic VT ablation were prospectively included. A complete map of the left ventricle was performed prior and after ablation through the Rhythmia mapping system. Channels were defined as any signal activity bounded by anatomic and functional barriers and characterized through the Lumipoint (LM) tool and continuous activation was used on the whole ventricular substrate. Procedural end point was the elimination of all identified CCs by ablation at the CC entrance and exit followed by abolition of any residual LPs inside the CC. The ablation endpoint was noninducibility. Data are reported as mean±SD.

Results

A total of 36 channels were identified through LM from 28 patients (1.2±0.5 per patient): 21 (75%) patients had 1 CC, 6 (21.4%) had 2 CCs and 1 (3.6%) had 3 CCs. LPs were identified inside CCs in 19 cases (67.9%). In 8 cases (28.6%) LPs were present both inside and outside and in 1 (3.6%) case LPs were present only outside the CC. LPs inside channels covered an area of 7.6±5 mm2 with a ratio between LPs area and CCs’ area of 67.4±31.8%. In 12 (43%) cases LPs area covered more than 90% of the CCs’ area. At voltage map analysis a total of 34 CC were identified: 1 CC was present in 75% of the cases, 2 CCs in 17.9% and 3 CCs in 3.6%. LPs were identified only inside CCs in 46.4% of the cases, both inside and outside in 42.9% and only outside in 10.7%. Healthy tissue (voltage level≥0.5mV) was prevalent (68.2±17%), followed by intermediate voltage areas (0.5-0.05 mV; 31.1±17%) and very low voltage areas (<0.05mV; 0.7±1%). LPs were found mostly at intermediate voltage areas (57.0±34% of the covered area; 39.1±33% at healthy tissue and 3.4±13% at very low voltage areas). LM was more accurate than traditional voltage mapping in identifying CCs: in 6 (21.4%) cases voltage map overestimated LPs areas, in 2 (7.1%) cases failed to fully identify LPs and only in 19 out 28 (67.8%) LM and voltage map had a complete agreement. All CCs’ entrance and exit were successfully ablated and abolition of any residual LPs inside the CC was achieved in all patients. No complication occurred. Noninducibility was achieved in all (100%) the cases.

Conclusions

In this experience, a channel identification approach through the advanced Lumipoint tool was more accurate than traditional voltage mapping and seems to be safe, feasible, and effective at least in the acute setting of ischemic VT ablation.

Impact of channels identification and ablation in ventricular tachycardia patients through high-density mapping: preliminary experience from an Italian registry

Funding Acknowledgements

Type of funding sources: None.

Background

Ventricular tachycardia (VT) ablation techniques in ischemic cardiomyopathy have evolved during the recent years. However, the long-term success rate remains disappointing. A technique based on channel identification and ablation through a novel automated algorithm may limit the extent of ablation needed and possibly lead to higher successful rate.

Purpose

To report preliminary data on feasibility and safety of a channel identification approach and to characterize late potentials (LPs) features using an ultra-high density mapping system with a novel analysis tool in ischemic VT procedures.

Methods

Consecutive patients (pts) indicated for ischemic VT ablation were enrolled in the CHARISMA study. A complete map of the left ventricle was performed prior and after ablation through the Rhythmia mapping system. For our purpose channels were defined as any signal activity bounded by anatomic and functional barriers and characterized through a novel map analysis tool (Lumipoint-LM-) that automatically identifies fragmented late potentials (LPs) and continuous activation was used on the whole ventricular substrate. Procedural endpoint was the elimination of all identified conducting channels (CCs) by ablation at the CC entrance and exit followed by abolition of any residual LPs inside the CC. The ablation endpoint was noninducibility.

Results

A total of 18 channels were identified through LM from 14 pts: 71.4% of the pts had 1 CC, 28.6% had 2 CCs. In the majority of the cases LPs where identified only inside CCs (57.1%), whereas in 6 cases (42.9%) LPs were present both inside and outside. The mean conduction time inside CCs was 50.3 ± 30ms, the mean CC length was 32.6 ± 17mm and the conduction velocity was 0.8 ± 0.5 mm/ms. LPs covered a mean area of 7.0 ± 5mm2 (ratio between LPs area and CCs’ area = 52.4 ± 33.7%). At voltage map analysis 1 CC was present in 78.6% of the cases (2 CCs in 21.4%). LPs were identified only inside CCs in 42.9% of the cases, both inside and outside in 50% and only outside in 7.1%. Healthy tissue (voltage level≥0.5mV) was prevalent (61.2 ± 13.8%), followed by intermediate voltage areas (0.5-0.05mV; 37.5 ± 13.7%) and very low voltage areas (<0.05mV; 1.2 ± 2%). LPs were found mostly at intermediate voltage areas (54.1 ± 31.7% of the covered area; 39.1 ± 28.4% at healthy tissue and 6.8 ± 17.8% at very low voltage areas). Agreement in CCs identification between advanced analysis through LM and voltage map was fair (9/14 with complete agreement). In 3 cases voltage map overestimated LPs areas, in 2 cases failed to fully identify LPs. All CCs’ entrance and exit were successfully ablated and abolition of any residual LPs inside the CC was achieved in all pts. No complication occurred. Noninducibility was achieved in all the cases.

Conclusions

In our preliminary experience, a new channel identification approach through the advanced Lumipoint algorithm seems to be safe, feasible and effective at least in the acute setting of ischemic VT ablation.