Use of CIED Generated Heart Failure Risk Score (HFRS) Alerts in an Integrated, Multi-Disciplinary Approach to HF Management-A Prospective Cohort Study.

Aim: To evaluate use of CIED-generated Heart Failure Risk Score (HFRS) alerts in an integrated, multi-disciplinary approach to HF management. Methods: We undertook a prospective, single centre outcome study of patients implanted with an HFRS-enabled Medtronic CIED, generating a "high risk" alert between November 2018 and November 2020. All patients generating a "high risk" HFRS alert were managed within an integrated HF pathway. Alerts were shared with local HF teams, prompting patient contact and appropriate intervention. Outcome data on health care utilisation (HCU) and mortality were collected. A validated questionnaire was completed by the HF teams to obtain feedback. Results: 367 "High risk" alerts were noted in 188 patients. The mean patient age was 70 and 49% had a Charlson Comorbidity Score of >6. Mean number of alerts per patients was 1.95 and 44 (23%) of patients had >3 "high risk" alerts in the follow up period. Overall, 75 (39%) patients were hospitalised in the 4−6-week period of the alert; 53 (28%) were unplanned of which 24 (13%) were for decompensated HF. A total of 33 (18%) patients died in the study period. Having three or more alerts significantly increased the risk of hospitalisation for heart failure (HR 2.5, CI 1.1−5.6 p = 0.03). The feedback on the pathway was positive. Conclusions: Patients with "high risk" alerts are co-morbid and have significant HCU. An integrated approach can facilitate timely risk stratification and intervention. Intervention in these patients is not limited to HF alone and provides the opportunity for holistic management of this complex cohort.

Evaluation of an Integrated Device Diagnostics Algorithm to Risk Stratify Heart Failure Patients　- Results From the SCAN-HF Study.

BACKGROUND: Integrated device diagnostics, Triage-HF, is useful in risk stratifying patients with heart failure (HF), but its performance for Japanese patients remains unknown. This is a prospective study of Japanese patients treated with a cardiac resynchronization therapy defibrillator (CRT-D), with a Medtronic OptiVol 2.0 feature.Methods and Results:A total of 320 CRT-D patients were enrolled from 2013 to 2017. All received HF treatment in the prior 12 months. Following enrollment, they were followed every 6 months for 48 months (mean, 22 months). Triage-HF-stratified patients at low, medium and high risk statuses at every 30-day period, and HF-related hospitalization occurring for the subsequent 30 days, were evaluated and repeated. The primary endpoint was to assess Triage-HF performance in predicting HF-related hospitalization risk. All device data were available for 279 of 320 patients (NYHA class II or III in 93%; mean left ventricular ejection fraction, 31%). During a total of 5,977 patient-month follow-ups, 89 HF-related hospitalization occurred in 72 patients. The unadjusted event numbers for Low, Medium and High statuses were 19 (0.7%), 42 (1.6%) and 28 (4.1%), respectively. Relative risk of Medium to Low status was 2.18 (95% CI 1.23-3.85) and 5.78 (95% CI 3.34-10.01) for High to Low status. Common contributing factors among the diagnostics included low activity, OptiVol threshold crossing, and elevated night heart rate. CONCLUSIONS: Triage-HF effectively stratified Japanese patients at risk of HF-related hospitalization.

Atrial high-rate episodes predict clinical outcome in patients with cardiac resynchronization therapy.

OBJECTIVES: Up to 50% of patients qualified for cardiac resynchronization therapy (CRT) have documented atrial fibrillation (AF) prior to CRT-implantation. This finding is associated with worse prognosis but few studies have evaluated the importance of post-implant device-detected AF. This study aimed to assess the prognostic impact of device-detected atrial high-rate episodes (AHRE), as a surrogate for AF. DESIGN: Data were retrospectively obtained from consecutive patients receiving CRT. Baseline clinical data and data from CRT device-interrogations, performed at a median of 12.2 months after CRT-implantation, were evaluated with regard to prediction of the composite endpoint of death, heart transplant or appropriate shock therapy. Median follow-up time was 51 months post-implant. RESULTS: The study included 377 patients. Preoperative AF was present in 49% and associated with worse outcome. The cumulative burden of AHRE at 12 months post-implant was an independent predictor of the primary endpoint. During the first 12 months after CRT-implantation, AHRE were detected in 25% of the patients with no preoperative diagnosis of AF. This finding was not associated with worse outcome. CONCLUSIONS: In CRT recipients, the cumulative burden of AHRE during the first year of follow-up was associated with worse long-term clinical outcome. Prospective trials are needed to determine if a rhythm control strategy is to be preferred in patients with CRT.

Assessment of intrathoracic impedance algorithm in the pediatric and adult congenital population.

BACKGROUND: Decreased intrathoracic impedance has been used in adults to predict heart failure (HF) exacerbations. A commercial algorithm, OptiVol® (Medtronic Inc., Minneapolis, MN, USA), identifies patients with decreased impedance. We sought to determine the specificity, sensitivity, and positive predictive value (PPV) of OptiVol for predicting HF exacerbation or increased arrhythmia burden in pediatric and adult congenital heart disease (CHD) patients. METHODS: A multicenter retrospective chart review was undertaken. Inclusion criteria were: (1) <19 years or CHD adults, (2) an implanted device with OptiVol capability, (3) implanted between April 9 and September 6, and (4) follow-up of >30 days postimplant. Clinical events were defined as clinical HF exacerbation/hospital admission, initiation/uptitration of medication, or increased arrhythmia burden. RESULTS: Seventy-two patients (19 ± 9 years) were identified with the following indications: 20% dilated cardiomyopathy (DCM), 11% hypertrophic cardiomyopathy (HCM), 43% CHD, 15% channelopathy, and 11% other. Thirty-nine had 122 OptiVol crossings (median 2, range 1-11); 30% were linked to a cause. The remaining 33 had no crossing, though 17 had 89 clinical events. The clinical event rate was 19% greater in patients with crossings, though not statistically significant (P = 0.4). The algorithm had a 59% sensitivity, 52% specificity, and 62% PPV. Clinical HF exacerbation and arrhythmia burden did not significantly correlate with decreased impedance though uptitration or initiation of HF medication did correlate significantly (P = 0.03). CONCLUSION: The algorithm sensitivity for pediatric DCM, HCM, CHD, and adult CHD was equivalent to the general adult population. Further studies are warranted to assess whether inaccuracy in prediction is secondary to the algorithm or to differences in the clinical response of pediatric/CHD patients.

Development and validation of an integrated diagnostic algorithm derived from parameters monitored in implantable devices for identifying patients at risk for heart failure hospitalization in an ambulatory setting.

BACKGROUND: We developed and validated a heart failure (HF) risk score combining daily measurements of multiple device-derived parameters. METHODS: Heart failure patients from clinical studies with implantable devices were used to form two separate data sets. Daily HF scores were estimated by combining changes in intra-thoracic impedance, atrial fibrillation (AF) burden, rapid rate during AF, %CRT pacing, ventricular tachycardia, night heart rate, heart rate variability, and activity using a Bayesian model. Simulated monthly follow-ups consisted of looking back at the maximum daily HF risk score in the preceding 30 days, categorizing the evaluation as high, medium, or low risk, and evaluating the occurrence of HF hospitalizations in the next 30 days. We used an Anderson-Gill model to compare survival free from HF events in the next 30 days based on risk groups. RESULTS: The development data set consisted of 921 patients with 9790 patient-months of data and 91 months with HF hospitalizations. The validation data set consisted of 1310 patients with 10 655 patient-months of data and 163 months with HF hospitalizations. In the validation data set, 10% of monthly evaluations in 34% of the patients were in the high-risk group. Monthly diagnostic evaluations in the high-risk group were 10 times (adjusted HR: 10.0; 95% CI: 6.4-15.7, P < 0.001) more likely to have an HF hospitalization (event rate of 6.8%) in the next 30 days compared with monthly evaluations in the low-risk group (event rate of 0.6%). CONCLUSION: An HF score based on implantable device diagnostics can identify increased risk for HF hospitalization in the next 30 days.

Atrial Fibrillation, thromboembolic risk, and the potential role of the natriuretic peptides, a focus on BNP and NT-proBNP - A narrative review.

Atrial fibrillation (AF) is one of the most commonly encountered arrythmia in clinical practice. AF itself can be driven by genetic predisposition, ectopic electrical activity, and abnormal atrial tissue substrates. Often there is no single etiological mechanism, but rather a combination of factors that feed back to remodel and worsen tissue substrate, "AF begets AF". The clinical consequences of AF can often include emboli, heart failure, and early mortality. The classical AF cardioembolic (CE) concept requires thrombus formation in the left atrial appendage, with subsequent embolization. The temporal dissociation between AF occurrence and CE events has thrown doubt on AF as the driver of this mechanism. Instead, there has been a resurgence of the "atrial cardiomyopathy" (ACM) concept. An ACM is proposed as a potential mechanism of embolic disease through promotion of prothrombotic mechanisms, with AF instead reflecting atrial disease severity. Regardless, AF has been implicated in 25% to 30% of cryptogenic strokes. Natriuretic peptide(NP)s have been shown to be elevated in AF, with higher levels of both NT-proBNP and BNP being predictive of incidental AF. NPs potentially reflect the atrial environment and could be used to identify an underlying ACM. Therefore, this narrative review examines this evidence and mechanisms that may underpin the role of NPs in identifying atrial dysfunction, with focus on both, BNP and NTproBNP. We explore their potential role in the prediction and screening for both, ACM and AF. Moreover, we compare both NPs directly to ascertain a superior biomarker.

Incremental Value of Implantable Cardiac Device Diagnostic Variables Over Clinical Parameters to Predict Mortality in Patients With Mild to Moderate Heart Failure.

Background Heart failure remains a leading cause of morbidity and mortality. Clinical prediction models provide suboptimal estimates of mortality in this population. We sought to determine the incremental value of implantable device diagnostics over clinical prediction models for mortality. Methods and Results RAFT (Resynchronization/Defibrillation for Ambulatory Heart Failure Trial) patients with implanted devices capable of device diagnostic monitoring were included, and demographic and clinical parameters were used to compute Meta-Analysis Global Group in Chronic Heart Failure (MAGGIC) heart failure risk scores. Patients were classified according to MAGGIC score into low (0-16), intermediate (17-24), or high (>24) risk groups. Mortality was evaluated from 6 months postimplant in accordance with the RAFT protocol. In a subset of 1036 patients, multivariable analysis revealed that intermediate and high MAGGIC scores, fluid index, atrial fibrillation, and low activity flags were independent predictors of mortality. A device-integrated diagnostic parameter that included a fluid index flag and either a positive atrial fibrillation flag or a positive activity flag was able to significantly differentiate higher from lower risk for mortality in the intermediate MAGGIC cohort. The effect was more pronounced in the high-risk MAGGIC cohort, in which device-integrated diagnostic-positive patients had a shorter time to death than those who were device-integrated diagnostic negative. Conclusions Device diagnostics using a combination of fluid index trends, atrial fibrillation burden, and patient activity provide significant incremental prognostic value over clinical heart failure prediction scores in higher-risk patients. This suggests that combining clinical and device diagnostic parameters may lead to models with better predictive power. Whether this risk is modifiable with early medical intervention would warrant further studies. Clinical Trial Registration URL : http://www.clinicaltrials.gov . Unique identifier: NCT00251251.

Prospective evaluation of integrated device diagnostics for heart failure management: results of the TRIAGE-HF study.

AIMS: The primary aim of the TRIAGE-HF trial was to correlate cardiac implantable electronic device-generated heart failure risk status (HFRS) with signs, symptoms, and patient behaviours classically associated with worsening heart failure (HF). METHODS AND RESULTS: TRIAGE-HF enrolled 100 subjects with systolic HF implanted with a Medtronic high-performance device and followed up at three Canadian HF centres. Study follow-up was up to 8 months. The HFRS assigned each subject's overall risk of HF hospitalization in the next 30 days and also highlighted abnormal device parameters contributing to a patient's risk status at the time of remote data transmission. Subjects with a high HFRS were contacted by telephone to assess symptoms, and compliance with prescribed therapies, nutrition, and exercise. Clinician-assessed risk and HFRS-calculated risk were correlated at both study baseline and exit. Twenty-four high HFRS occurrences were observed among 100 subjects. Device parameters associated with increased risk of HF hospitalization included OptiVol index (n = 20), followed by low patient activity (n = 18) and elevated night heart rate (n = 12). High HFRS was associated with symptoms of worsening HF in 63% of cases (n = 15) increasing to 83% of cases (n = 20) when non-compliance with pharmacological therapies and lifestyle was considered. CONCLUSIONS: TRIAGE-HF is the first study to provide prospective data on the distribution of abnormal device parameters contributing to high HFRS. High HFRS has good predictive accuracy for patient-reported signs, symptoms, and behaviours associated with worsening HF status. As such, HFRS may be a useful tool for ambulatory HF monitoring to improve both patient-centred and health system level outcomes.

Validation of device algorithm to differentiate pacemaker-mediated tachycardia from tachycardia due to atrial tracking.

BACKGROUND: Current cardiac devices cannot always differentiate between pacemaker-mediated tachycardia (PMT) and tracking of sinus or atrial tachycardia. We previously derived a novel algorithm for distinguishing the 2 mechanisms based on the specific termination response to postventricular atrial refractory period extension, atrial rates, and changes in atrial electrogram morphology. OBJECTIVE: The purpose of this study was to evaluate how this algorithm would have performed in a clinical setting based on previously recorded PMT events. METHODS: We applied our algorithm to a database of 122 de-identified stored electrograms that were classified as PMT by 43 remotely monitored devices. RESULTS: Of the 122 events stored as "PMT," 3 episodes were excluded because the device recording was consistent with atrial fibrillation. Of the remaining 119 episodes, our algorithm was able to correctly reclassify 92 events (77%) as tracking of sinus or atrial tachycardia rather than true PMT. The VAV response following postventricular atrial refractory period extension, which is specific to tracking of atrial or sinus tachycardia, was seen in 72% of these cases. Changes in atrial rate and atrial electrogram morphology were able to reclassify the remainder of episodes. Finally, we observed that 12 of 83 episodes (14%) misclassified as PMT in cardiac resynchronization devices resulted in loss of cardiac biventricular pacing. CONCLUSION: Applying a novel diagnostic algorithm to current cardiac devices improves the proper diagnosis of true PMT rather than tracking of atrial or sinus tachycardia. Enhanced accuracy of diagnosis reduces the likelihood of inappropriate clinical decisions.

Stratifying patients at the risk of heart failure hospitalization using existing device diagnostic thresholds.

BACKGROUND: Heart failure hospitalizations (HFHs) cost the US health care system ∼$20 billion annually. Identifying patients at risk of HFH to enable timely intervention and prevent expensive hospitalization remains a challenge. Implantable cardioverter defibrillators (ICDs) and cardiac resynchronization devices with defibrillation capability (CRT-Ds) collect a host of diagnostic parameters that change with HF status and collectively have the potential to signal an increasing risk of HFH. These device-collected diagnostic parameters include activity, day and night heart rate, atrial tachycardia/atrial fibrillation (AT/AF) burden, mean rate during AT/AF, percent CRT pacing, number of shocks, and intrathoracic impedance. There are thresholds for these parameters that when crossed trigger a notification, referred to as device observation, which gets noted on the device report. We investigated if these existing device observations can stratify patients at varying risk of HFH. METHODS: We analyzed data from 775 patients (age: 69 ± 11 year, 68% male) with CRT-D devices followed for 13 ± 5 months with adjudicated HFHs. HFH rate was computed for increasing number of device observations. Data were analyzed by both excluding and including intrathoracic impedance. HFH risk was assessed at the time of a device interrogation session, and all the data between previous and current follow-up sessions were used to determine the HFH risk for the next 30 days. RESULTS: 2276 follow-up sessions in 775 patients were evaluated with 42 HFHs in 37 patients. Percentage of evaluations that were followed by an HFH within the next 30 days increased with increasing number of device observations. Patients with 3 or more device observations were at 42× HFH risk compared to patients with no device observation. Even after excluding intrathoracic impedance, the remaining device parameters effectively stratified patients at HFH risk. CONCLUSION: Available device observations could provide an effective method to stratify patients at varying risk of heart failure hospitalization.