Non-fatal Heart Failure Events Research Articles

Usefulness of telemedicine-based heart failure monitoring according to “eHealth literacy” domains: insights from the iCOR randomised controlled trial

Abstract Background/Introduction The potential positive effect of electronic health (eHealth)-based heart failure (HF) monitoring remains uncertain, largely due to the heterogeneity of the studies published to date. A subgroup of patients in which its key role is particularly uncertain is in the “low literacy” or “computer or digital illiterate” patients mainly due to telemedicine (TM)-based strategies have been often discouraged on the basis of a foreseeable limited benefit in them. Purpose The aim of this study was to determine the effectiveness of a TM-based managed care solution across literacy levels and information and communications technology (ICT) skills. Methods We performed a sub-analysis on the basis of two literacy domains (traditional and computer literacy) encompassed in the definition of “eHealth literacy” to the HF-patients included in the “insuficiència Cardíaca Optimitzaciό Remota” (iCOR) randomised study comparing TM vs. usual care (UC) in HF-patients. The primary study endpoint was the incidence of a non-fatal HF event after 6 months of inclusion. The event rates of primary (the occurrence of non-fatal HF event) and secondary (all-cause hospitalization, all cause death and the composite endpoint combining of allcause death or non-fatal HF events) study endpoints were calculated for each literacy domains and its combination. Cox proportional-hazards regression models were used to evaluate the effect of “eHealth literacy” dimensions, treatment group and the interaction term “eHealth literacy” domains by treatment group on study endpoints, and p-value was used to compare the different curves. Results 178 patients were analysed (81 TM vs 90 UC). As far as the “traditional literacy” analyses, 65% of patients had only elementary education and the 6% had no literacy qualifications, defining the low-educated subgroup as “lower literacy” (126 patients, 71%). All the other patients were classified in the “middle or higher literacy” (52 patients, 29%) subgroup. Moreover, concerning new technological management, 128 patients (72%) referred presenting moderate to high difficulties in its handling, constituting the “lower ICT skills” subgroup. The remaining 28% (50 patients) were allocated into the “middle or higher ICT skills” subgroup due to their minor handicap in their ICT use. The beneficial effect of TM compared to UC strategy was consistent across all literacy domains (pvalue for interaction 0.207 and 0.117 respectively). The risk of experiencing a primary event was significantly lower in patients that underwent allocation to the TM arm compared to UC in both clustered in the “lower literacy” (p-value=0.001) (Picture 1) and those allocated to the “lower ICT skills” (p-value=0.001) (Picture 2) subgroup. Conclusions Non-invasive eHealth-based HF monitoring tools are effective compared to UC in preventing HF events in the early post-discharge period, regardless of two “eHealth literacy” domains (“traditional and computer literacy”). Funding Acknowledgement Type of funding sources: None.

Improving predictive performance in incident heart failure using machine learning and multi-center data.

To mitigate the burden associated with heart failure (HF), primary prevention is of the utmost importance. To improve early risk stratification, advanced computational methods such as machine learning (ML) capturing complex individual patterns in large data might be necessary. Therefore, we compared the predictive performance of incident HF risk models in terms of (a) flexible ML models and linear models and (b) models trained on a single cohort (single-center) and on multiple heterogeneous cohorts (multi-center). In our analysis, we used the meta-data consisting of 30,354 individuals from 6 cohorts. During a median follow-up of 5.40 years, 1,068 individuals experienced a non-fatal HF event. We evaluated the predictive performance of survival gradient boosting (SGB), CoxNet, the PCP-HF risk score, and a stacking method. Predictions were obtained iteratively, in each iteration one cohort serving as an external test set and either one or all remaining cohorts as a training set (single- or multi-center, respectively). Overall, multi-center models systematically outperformed single-center models. Further, c-index in the pooled population was higher in SGB (0.735) than in CoxNet (0.694). In the precision-recall (PR) analysis for predicting 10-year HF risk, the stacking method, combining the SGB, CoxNet, Gaussian mixture and PCP-HF models, outperformed other models with PR/AUC 0.804, while PCP-HF achieved only 0.551. With a greater number and variety of training cohorts, the model learns a wider range of specific individual health characteristics. Flexible ML algorithms can be used to capture these diverse distributions and produce more precise prediction models.

Usefulness of telemedicine-based heart failure monitoring according to “eHealth literacy” domains: insights from the iCOR randomised controlled trial

Abstract Background/Introduction The potential positive effect of electronic health (eHealth)-based heart failure (HF) monitoring remains uncertain, largely due to the heterogeneity of the studies published to date. A subgroup of patients in which its key role is particularly uncertain is in the “low literacy” or “computer or digital illiterate” patients mainly due to telemedicine (TM)-based strategies have been often discouraged on the basis of a foreseeable limited benefit in them. Purpose The aim of this study was to determine the effectiveness of a TM-based managed care solution across literacy levels and information and communications technology (ICT) skills. Methods We performed a sub-analysis on the basis of two literacy domains (traditional and computer literacy) encompassed in the definition of “eHealth literacy” to the HF-patients included in the “insuficiència Cardíaca Optimitzaciό Remota” (iCOR) randomised study comparing TM vs. usual care (UC) in HF-patients. The primary study endpoint was the incidence of a non-fatal HF event after 6 months of inclusion. The event rates of primary (the occurrence of non-fatal HF event) and secondary (all-cause hospitalization, all cause death and the composite endpoint combining of allcause death or non-fatal HF events) study endpoints were calculated for each literacy domains and its combination. Cox proportional-hazards regression models were used to evaluate the effect of “eHealth literacy” dimensions, treatment group and the interaction term “eHealth literacy” domains by treatment group on study endpoints, and p-value was used to compare the different curves. Results 178 patients were analysed (81 TM vs 90 UC). As far as the “traditional literacy” analyses, 65% of patients had only elementary education and the 6% had no literacy qualifications, defining the low-educated subgroup as “lower literacy” (126 patients, 71%). All the other patients were classified in the “middle or higher literacy” (52 patients, 29%) subgroup. Moreover, concerning new technological management, 128 patients (72%) referred presenting moderate to high difficulties in its handling, constituting the “lower ICT skills” subgroup. The remaining 28% (50 patients) were allocated into the “middle or higher ICT skills” subgroup due to their minor handicap in their ICT use. The beneficial effect of TM compared to UC strategy was consistent across all literacy domains (pvalue for interaction 0.207 and 0.117 respectively). The risk of experiencing a primary event was significantly lower in patients that underwent allocation to the TM arm compared to UC in both clustered in the “lower literacy” (p-value=0.001) (Picture 1) and those allocated to the “lower ICT skills” (p-value=0.001) (Picture 2) subgroup. Conclusions Non-invasive eHealth-based HF monitoring tools are effective compared to UC in preventing HF events in the early post-discharge period, regardless of two “eHealth literacy” domains (“traditional and computer literacy”). Funding Acknowledgement Type of funding sources: None.

Strategic management to optimize response to cardiac resynchronization therapy registry

Abstract Background Cardiac resynchronization therapy (CRT) is guideline-recommended for the treatment of symptomatic heart failure (HF) in patients (pts) with reduced LVEF and prolonged QRS. Clinical trials report Clinical Composite Score (CCS) response rates from 60 to 75%. However, patients with common comorbidities, such as atrial fibrillation, are often under-represented in clinical trials. The Strategic MAnagement to optimize response to cardiac Resynchronization Therapy (SMART) Registry (NCT03075215) was designed to examine outcomes in CRT patients in the real world. Methods The SMART Registry was a global, multicenter, prospective, clinical registry that enrolled subjects undergoing a de novo CRT-D implant or upgrade from pacemaker to CRT-D using a quadripolar LV lead. CCS was assessed at 12 months post-implant. Results For study design and CCS outcomes see Figure 1. CCS at 12 months showed that 58.8% of pts improved and 20.1% stabilized. Of the 21.1% of pts that worsened, 8.4% were due to death, 7.8% non-fatal heart failure event, and 5% worsening of NYHA or patient global assessment. Notably, this registry had a high prevalence of pts with NYHA I/II (51%), Non-LBBB (50%), AF (37%), diabetes (35%), and bradycardia (31%) at baseline. Age (>65), diabetes, ischemia, non-LBBB, atrial fibrillation (AF) and renal dysfunction correlated with worsened CCS outcomes. NYHA III/IV patients had significantly higher HF hospitalization (HFH) rates than NYHA I/II (P-value <0.001) (Figure 2a) and patients with AF had higher HFH rates than those without (P-value <0.001) (Figure 2b). Similar effects of NYHA score and AF were seen on mortality. The use of ACE/ARB, or ARNI, and MRA correlated with better outcomes, whereas diuretics and anticoagulants correlated with poorer outcomes. Conclusions In this large registry, clinical outcomes across important sub-populations are in line with expectations, with older age, ischemia, renal dysfunction, AF, non-LBBB, and diabetes associated with a lower likelihood of response to CRT. By including these patients, this study provides a clearer picture of the effectiveness of CRT in the real world. Future studies should examine optimization approaches to facilitate CRT effectiveness in these under studied patient populations. Funding Acknowledgement Type of funding sources: Private company. Main funding source(s): This registry was funded by Boston Scientific (BSC)

PREDICTIVE PERFORMANCE OF MACHINE LEARNING MODELS FOR DETECTION OF INCIDENT HEART FAILURE USING MULTI-CENTRE DATA

Objective: To mitigate the health and economic burden associated with heart failure (HF), primary prevention is of utmost importance. To effectively address the diverse range of individual health profiles, prediction models must be trained and validated on a wide range of population-based cohorts. We evaluated the predictive performance of Survival Gradient Boosting (SGB) and Coxnet (CN) for the detection of incident HF. In addition, we compared the models’ performance trained only on a single-centre cohort with those trained on diverse multi-centre cohorts. Design and method: We utilized 6 cohorts from the Heart ‘omics’ in AGEing (HOMAGE) project to evaluate two computational approaches. The dataset consists of 31,382 individuals (mean age 66 ± 10 years old), free of HF at the baseline. During a median follow-up of 5.36 years, 1,130 non-fatal HF events occurred. SGB is a non-linear machine learning method based on training regression trees with the objective of optimizing Cox partial likelihood. Coxnet is a standard linear Cox proportional hazard model, regularized by both L1 and L2 norms. To estimate the predictive accuracy of a single-centre model on a specific test cohort, we averaged the performance of single models trained on remaining cohorts one at a time. To develop models in multi-centre settings, we used 5 cohorts in every iteration as a training set and the remaining 1 cohort as a test set. We used 33 features, including clinical, ECG, and biochemical data. Results: Overall, multi-centre models achieved a higher c-index than those trained on single cohorts (Figure). For example, in the FLEMENGHO cohort, multi-centre SGB achieved 0.819, while only 0.664 in a single-centre setting. Additionally, non-linear SGB achieved a considerably higher c-index than linear CN in all but one cohort, especially in multi-centre settings, for example in the HVC cohort (SGB 0.689, CN 0.614). Conclusions: With a greater number and variety of training cohorts, the model learns a wider range of specific individual health characteristics. Flexible machine learning algorithms such as gradient boosting can be used to capture these diverse distributions and produce more precise, personalized models for the prediction of adverse events.

Usefulness of telemedicine-based heart failure monitoring according to ‘eHealth literacy’ domains: Insights from the iCOR randomized controlled trial

BackgroundThe potential positive effect of electronic health (eHealth)-based heart failure (HF) monitoring remains uncertain mainly in the ‘low literacy’ or ‘computer or digital illiterate’ patients. The aim of this study was to determine the effectiveness of a telemedicine (TM)-based managed care solution across literacy levels and information and communications technology (ICT) skills. MethodsWe performed a sub-analysis on the basis of two literacy domains encompassed in the definition of ‘eHealth literacy’ to the HF-patients included in the ‘insuficiència Cardíaca Optimització Remota’ (iCOR) randomized study comparing TM vs. usual care (UC) in HF-patients. The primary study endpoint was the incidence of a non-fatal HF event after 6 months of inclusion. The event rates of primary and secondary study endpoints were calculated for each literacy domains and its combination. Cox proportional-hazards regression models were used to evaluate the effect of ‘eHealth literacy’ dimensions, treatment group and the interaction term ‘eHealth literacy’ domains by treatment group on study endpoints. ResultsThe beneficial effect of TM compared to UC strategy was consistent across all literacy domains (p-value for interaction 0.207 and 0.117 respectively). The risk of experiencing a primary event was significantly lower in patients that underwent allocation to the TM arm compared to UC in both clustered in the ‘lower literacy’ (p-value=0.001) and those allocated to the ‘lower ICT skills’ (p-value=0.001) subgroup. ConclusionsNon-invasive eHealth-based HF monitoring tools are effective compared to UC in preventing HF events in the early post-discharge period, regardless of two ‘eHealth literacy’ domains (‘traditional and computer literacy’).

Effectiveness of telemedicine in patients with heart failure according to frailty phenotypes: Insights from the iCOR randomised controlled trial

BackgroundThe potential impact of telemedicine (TM) in the monitoring of patients with heart failure (HF) is still uncertain particularly in the frailest patients. The aim of this study was to define the efficacy of a TM-based managed care solution across different HF patient frailty phenotypes. MethodsWe performed a clustering analysis on the basis of 8 frailty-related dimensions to the HF-patients included in the ‘insuficiència Cardíaca Optimització Remota’ (iCOR) randomised study comparing TM vs. usual care (UC) in HF patients. The primary study endpoint was the incidence of a non-fatal HF event after 6 months of inclusion. The healthcare-related costs in each study group and cluster were also evaluated. The event rates of primary and secondary study endpoints were calculated for each cluster. Cox proportional-hazards regression models were used to evaluate the effect of cluster, treatment group and the interaction term cluster by treatment group on study endpoints. Results5 different frailty phenotypes were identified. The positive effect of TM compared to UC strategy was consistent across all frailty phenotypes (p-value for interaction 0.711). The risk of experiencing a primary event was significantly lower in patients that underwent allocation to the TM arm compared to UC (p-value = 0.016). Ultimately, the healthcare costs were significantly reduced in patients allocated to the TM compared to UC in all 5 frailty phenotypes (all p-value < 0.05). ConclusionsNon-invasive TM-based follow-up tools are effective compared to UC follow-up in preventing HF events in the early post-discharge period, regardless of the 5 frailty phenotypes.

Frailty phenotypes in patients with heart failure in the early post-discharge period: insights from the iCOR randomised controlled trial and a machine learning-based clustering analysis

Abstract Background/Introduction Several variables such as clinical, socioeconomic, functional or cognitive, among others can have an impact on the prognosis of heart failure (HF) patients despite the optimisation of follow-up strategies (e.g. telemedicine [TM] solutions). The clustering of HF patients may to identify different patient frailty phenotypes. Purpose The aim of this study was to perform a machine learning-based clustering analysis to identify different patient frailty phenotypes in a cohort of HF patients recruited in a randomized clinical trial (The Insuficiència Cardíaca Optimitzaciό Remota [iCOR] study). Methods We performed the clustering analysis on the basis of 8 frailty-related dimensions. To define the number of clusters, dissimilarity matrix was calculated with Gower's distance. Then, hierarchical divisive clustering was performed. Using then Elbow and Silhouette to analyse how the within sum of squares changes for the different number of clusters, the final number of clusters were chosen. The incidence proportion of the each of the study endpoints (non-fatal HF events as primary endpoint and all-cause hospitalization, all-cause death and the composite endpoint combining of all-cause death or non-fatal HF events as secondary endpoints) was calculated for cluster. Results 5 different frailty phenotypes were identified. Cluster 1 (29 patients, 16%) comprised patients with the best reported self-perceived health status (QoL), fair emotional-affective status, but low levels of self-care. Cluster 2 (41 patients, 23%) included the youngest patients with the highest level of education and a better level of cognition. Cluster 3 (68, 38%) encompassed the patients who had the best level of self-care behaviour (18.9±9.8), greater physical and instrumental functioning for activities of daily living (ADL) and a lower rate of comorbidities. Patients in the Cluster 4 (30 patients, 17%) tended to be elderly females with poor health-related QoL, and a higher level of functional dependence. Finally, Cluster 5 was the smallest group (10 patients, 6%), encompassing the oldest patients with low level of education, a worse affective-emotional state, a significant cognitive decline and a higher proportion of comorbidities compared to the other clusters. Cluster 4 had the highest incidence rate of the primary endpoint (57 per 100 patient-years at risk, 95% CI [37.4–74–5]) and a higher incidence of all-cause hospitalization and of the combined variable of all-cause of death or non-fatal HF events. Conclusion(s) Using the cluster analysis, we were able to stratify HF patients according to the stage of their impairment and vulnerability in each of the different frailty domains. This will allow clinicians to incorporate holistic multi-domain assessments in HF programmes to identify patients' needs and provide each patient with personalised and structured follow-up programme according to patient's needs (personalised and precision medicine). Funding Acknowledgement Type of funding sources: None. Radar chart to compare frailty clustersClinical endpoints according clusters

Effectiveness of telemedicine in patients with heart failure according to frailty phenotypes: insights from the iCOR randomised controlled trial

Abstract Background/Introduction The potential impact of telemedicine (TM) in the monitoring of heart failure (HF) patients is still uncertain, largely due to the heterogeneity of the studies published to date. A subgroup of patients in which its key role is particularly uncertain is that of the frailest patients mainly due to TM-based strategies have been often discouraged on the basis of a foreseeable limited benefit in them. Purpose The aim of this study was to define the efficacy of a TM-based managed care solution across different HF patient frailty phenotypes in a cohort of HF patients recruited in a randomized clinical trial (The Insuficiència Cardíaca Optimitzaciό Remota [iCOR] study) evaluating the efficacy of a TM-based management compared to usual care (UC) in the early post-discharge period. Methods Five previously described frailty clusters were analysed. Cox proportional-hazards regression models were used to evaluate the effect of each cluster and group of treatment (and its interaction) on a series of endpoints (the incidence of non-fatal HF events as primary endpoint and all-cause hospitalization, all-cause death and the composite endpoint combining of all-cause death or non-fatal HF events as secondary endpoints). The incidence proportion of the first occurrence of each of the study endpoints was calculated for each study arm and for cluster, and these compared using χ2 tests. Additionally, a survival analysis was conducted using Cox regression to describe the event-free survival experience of the combination of the clusters with each of the 2 treatment groups for the study endpoints evaluated, and p-value was used to compare the different curves. Results The positive effect of TM compared to UC strategy was consistent across all frailty phenotypes (p-value for interaction 0.711). The risk of experiencing a primary event was significantly lower in patients that underwent allocation to the TM arm compared to UC (p-value=0.016). As shown for the primary endpoint, the positive effect of TM compared to UC strategy was consistent across all frailty phenotypes also for the secondary endpoints (all p-value for interaction &amp;gt;0.05). Likewise, the risk of all-cause hospitalization or the composite end-point of all-cause death or non-fatal HF event was significantly lower in patients that underwent allocation to the TM arm compared to UC (p-value=0.030 and 0.016 respectively). However, the risk of all-cause death did not differ across subgroup strata (p-value&amp;gt;0.05). Conclusion(s) This study showed that non-invasive TM-based follow-up tools are effective compared to UC in preventing fatal and non-fatal adverse events in the early post-discharge period, regardless of the 5 different frailty phenotypes. Importantly, when comparing TM-based follow-up with UC management in patients belonging to equal frailty cluster, those who were followed-up by eHealth had a considerably lower risk of non-fatal HF events, hospitalization or death. Funding Acknowledgement Type of funding sources: None. Cox regression non-fatal HF eventsCox regression all-cause hospitalization

Influence of receptor selectivity on benefits from SGLT2 inhibitors in patients with heart failure: a systematic review and head-to-head comparative efficacy network meta-analysis

BackgroundReceptor selectivity of sodium-glucose cotransporter-2 inhibitors (SGLT2i) varies greatly between agents. The overall improvement of cardiovascular (CV) outcomes in heart failure (HF) patients varies between trials. We, therefore, evaluated the comparative efficacy of individual SGLT2i and the influence of their respective receptor selectivity thereon.MethodsWe identified randomized controlled trials investigating the use of SGLT2i in patients with HF—either as the target cohort or as a subgroup of it. Comparators included placebo or any other active treatment. The primary endpoint was the composite of hospitalization for HF or CV death. Secondary outcomes included all-cause mortality, CV mortality, hospitalization for HF, worsening renal function (RF), and the composite of worsening RF or CV death. Evidence was synthesized using network meta-analysis. In addition, the impact of receptor selectivity on outcomes was analysed using meta-regression.ResultsWe identified 18,265 patients included in 22 trials. Compared to placebo, selective and non-selective SGLT2i improved fatal and non-fatal HF events. Head-to-head comparisons suggest superior efficacy with sotagliflozin as compared to dapagliflozin, empagliflozin or ertugliflozin. No significant difference was found between canagliflozin and sotagliflozin. Meta-regression analyses show a decreasing benefit on HF events with increasing receptor selectivity of SGLT2i. In contrast, receptor selectivity did not affect mortality and renal endpoints and no significant difference between individual SGLT2i was noted.ConclusionOur data point towards a class-effect of SGLT2i on mortality and renal outcomes. However, non-selective SGLT2i such as sotagliflozin may be superior to highly selective SGLT2i in terms of HF outcomes.

Heart Failure Hospitalization in Adults Receiving Hemodialysis and the Effect of Intravenous Iron Therapy

ObjectivesThis study sought to examine the effect of intravenous iron on heart failure events in hemodialysis patients. BackgroundHeart failure is a common and deadly complication in patients receiving hemodialysis and is difficult to diagnose and treat. MethodsThe study analyzed heart failure events in the PIVOTAL (Proactive IV Iron Therapy in Hemodialysis Patients) trial, which compared intravenous iron administered proactively in a high-dose regimen with a low-dose regimen administered reactively. Heart failure hospitalization was an adjudicated outcome, a component of the primary composite outcome, and a prespecified secondary endpoint in the trial. ResultsOverall, 2,141 participants were followed for a median of 2.1 years. A first fatal or nonfatal heart failure event occurred in 51 (4.7%) of 1,093 patients in the high-dose iron group and in 70 (6.7%) of 1,048 patients in the low-dose group (HR: 0.66; 95% CI: 0.46–0.94; P = 0.023). There was a total of 63 heart failure events (including first and recurrent events) in the high-dose iron group and 98 in the low-dose group, giving a rate ratio of 0.59 (95% CI: 0.40–0.87; P = 0.0084). Most patients presented with pulmonary edema and were mainly treated by mechanical removal of fluid. History of heart failure and diabetes were independent predictors of a heart failure event. ConclusionsCompared with a lower-dose regimen, high-dose intravenous iron decreased the occurrence of first and recurrent heart failure events in patients undergoing hemodialysis, with large relative and absolute risk reductions. (UK Multicentre Open-label Randomised Controlled Trial Of IV Iron Therapy In Incident Haemodialysis Patients; 2013-002267-25).

Study design of Heart failure Events reduction with Remote Monitoring and eHealth Support (HERMeS).

AimsThe role of non‐invasive telemedicine (TM) combining telemonitoring and teleintervention by videoconference (VC) in patients recently admitted due to heart failure (HF) (‘vulnerable phase’ HF patients) is not well established. The aim of the Heart failure Events reduction with Remote Monitoring and eHealth Support (HERMeS) trial is to assess the impact on clinical outcomes of implementing a TM service based on mobile health (mHealth), which includes remote daily monitoring of biometric data and symptom reporting (telemonitoring) combined with VC structured, nurse‐based follow‐up (teleintervention). The results will be compared with those of the comprehensive HF usual care (UC) strategy based on face‐to‐face on‐site visits at the vulnerable post‐discharge phase.Methods and resultsWe designed a 24 week nationwide, multicentre, randomized, controlled, open‐label, blinded endpoint adjudication trial to assess the effect on cardiovascular (CV) mortality and non‐fatal HF events of a TM‐based comprehensive management programme, based on mHealth, for patients with chronic HF. Approximately 508 patients with a recent hospital admission due to HF decompensation will be randomized (1:1) to either structured follow‐up based on face‐to‐face appointments (UC group) or the delivery of health care using TM. The primary outcome will be a composite of death from CV causes or non‐fatal HF events (first and recurrent) at the end of a 6 month follow‐up period. Key secondary endpoints will include components of the primary event analysis, recurrent event analysis, and patient‐reported outcomes.ConclusionsThe HERMeS trial will assess the efficacy of a TM‐based follow‐up strategy for real‐world ‘vulnerable phase’ HF patients combining telemonitoring and teleintervention.

SGLT2 inhibitors in patients with heart failure with reduced ejection fraction: a meta-analysis of the EMPEROR-Reduced and DAPA-HF trials

Both DAPA-HF (assessing dapagliflozin) and EMPEROR-Reduced (assessing empagliflozin) trials showed that sodium-glucose co-transporter-2 (SGLT2) inhibition reduced the combined risk of cardiovascular death or hospitalisation for heart failure in patients with heart failure with reduced ejection fraction (HFrEF) with or without diabetes. However, neither trial was powered to assess effects on cardiovascular death or all-cause death or to characterise effects in clinically important subgroups. Using study-level published data from DAPA-HF and patient-level data from EMPEROR-Reduced, we aimed to estimate the effect of SGLT2 inhibition on fatal and non-fatal heart failure events and renal outcomes in all randomly assigned patients with HFrEF and in relevant subgroups from DAPA-HF and EMPEROR-Reduced trials. We did a prespecified meta-analysis of the two single large-scale trials assessing the effects of SGLT2 inhibitors on cardiovascular outcomes in patients with HFrEF with or without diabetes: DAPA-HF (assessing dapagliflozin) and EMPEROR-Reduced (assessing empagliflozin). The primary endpoint was time to all-cause death. Additionally, we assessed the effects of treatment in prespecified subgroups on the combined risk of cardiovascular death or hospitalisation for heart failure. These subgroups were based on type 2 diabetes status, age, sex, angiotensin receptor neprilysin inhibitor (ARNI) treatment, New York Heart Association (NYHA) functional class, race, history of hospitalisation for heart failure, estimated glomerular filtration rate (eGFR), body-mass index, and region (post-hoc). We used hazard ratios (HRs) derived from Cox proportional hazard models for time-to-first event endpoints and Cochran's Q test for treatment interactions; the analysis of recurrent events was based on rate ratios derived from the Lin-Wei-Yang-Ying model. Among 8474 patients combined from both trials, the estimated treatment effect was a 13% reduction in all-cause death (pooled HR 0·87, 95% CI 0·77-0·98; p=0·018) and 14% reduction in cardiovascular death (0·86, 0·76-0·98; p=0·027). SGLT2 inhibition was accompanied by a 26% relative reduction in the combined risk of cardiovascular death or first hospitalisation for heart failure (0·74, 0·68-0·82; p<0·0001), and by a 25% decrease in the composite of recurrent hospitalisations for heart failure or cardiovascular death (0·75, 0·68-0·84; p<0·0001). The risk of the composite renal endpoint was also reduced (0·62, 0·43-0·90; p=0·013). All tests for heterogeneity of effect size between trials were not significant. The pooled treatment effects showed consistent benefits for subgroups based on age, sex, diabetes, treatment with an ARNI and baseline eGFR, but suggested treatment-by-subgroup interactions for subgroups based on NYHA functional class and race. The effects of empagliflozin and dapagliflozin on hospitalisations for heart failure were consistent in the two independent trials and suggest that these agents also improve renal outcomes and reduce all-cause and cardiovascular death in patients with HFrEF. Boehringer Ingelheim.

Impact of telemedicine on the clinical outcomes and healthcare costs of patients with chronic heart failure and mid-range or preserved ejection fraction managed in a multidisciplinary chronic heart failure programme: A sub-analysis of the iCOR randomized trial

Background The efficacy of telemedicine in the management of patients with chronic heart failure and left ventricular ejection fraction ≥40% is poorly understood. The aim of our analysis was to evaluate the efficacy of a telemedicine-based intervention specifically in these patients, as compared to standard of care alone. Methods The Insuficiència Cardiaca Optimització Remota (iCOR) study was a single centre, randomised, controlled trial, designed to evaluate a telemedicine intervention added to an existing hospital/primary care multidisciplinary, integrated programme for chronic heart failure patients. 178 participants were randomised to telemedicine or usual care, and were followed for six months. For the present sub-analysis, only iCOR participants (n = 116) with left ventricular ejection fraction ≥40% were included. The primary study endpoint was the incidence of an acute non-fatal heart failure event, defined as a new episode of worsening of symptoms and signs consistent with acute heart failure requiring intravenous diuretic therapy. The healthcare-related costs in each study group were also evaluated. Results The incidence of the first occurrence of the primary endpoint was significantly lower in the telemedicine arm (22% vs 56%, p<0.001), with a hazard ratio of 0.33 comparing to the usual care arm (95% confidence interval 0.17–0.64). Telemedicine was also associated with lower mean overall chronic heart failure care-related costs compared to usual care (8163€ vs 4993€, p=0.001). The results were consistent in both left ventricular ejection fraction of 40–49% and left ventricular ejection fraction ≥50% patients. Conclusions Our results suggest that telemedicine is a promising strategy for the management of chronic heart failure patients with left ventricular ejection fraction ≥40%. These findings should be replicated in larger cohorts.

Impact of a Pharmacist-led Cardiology Pharmacotherapy Clinic on Chronic Heart Failure Management

Introduction There are limited data on the impact of pharmacist-led heart failure (HF) clinics on care processes and outcomes. We compared the impact of pharmacist interventions in a cardiology pharmacotherapy clinic (CPC) versus standard care in general cardiology and HF subspecialty clinics on medication titration and non-fatal HF events in patients with HF with reduced ejection fraction (HFrEF) at the Veterans Affairs Ann Arbor Healthcare System (VAAAHS). Hypothesis Patients referred to CPC will be more likely to achieve target doses of guideline-recommended therapies and have fewer non-fatal HF events when compared to general cardiology. Methods This was a single-center retrospective chart review conducted at the VAAAHS in HFrEF patients (New York Heart Association Class II-IV) enrolled in general cardiology, HF subspecialty clinic, or CPC from July 1, 2009 to September 7, 2016. Exclusion criteria included terminal illness, dementia, investigational drug use, nursing home resident, and hospitalization in last month. The primary outcome was the proportion of patients on goal dose guideline-recommended therapies after 1 year of follow-up. Other outcomes included non-fatal HF events, defined as ER visits and hospital admissions for HF. Between-group differences were evaluated by t-testing or chi-square, and pre-post differences by McNemar's test. Results A total of 240 patients were evaluated and followed for 1 year. Patients in the CPC had an intermediate risk profile between general cardiology and HF subspecialty clinics. Patients referred to CPC were similarly likely to be on goal doses of ACEI/valsartan (ACE/ARB), evidence-based beta blockers (carvedilol/metoprolol succinate/bisoprolol; BB), and mineralocorticoid antagonists (MRA) as general cardiology, and less likely to be on target dose at baseline when compared to the HF subspecialty clinic. Between referral and 1 year of follow-up, the proportion of patients on goal-dose ACE/ARB (p = 0.02) and BB (p Table ). There were slightly more ER visits in CPC patients, but no between-clinic differences in hospital admissions. Conclusions Patients with HFrEF referred to a pharmacist-led clinic had more effective titration of evidence-based medications than through usual care in general cardiology.

Effects of Sodium-Glucose Cotransporter 2 Inhibitors for the Treatment of Patients With Heart Failure

ImportanceOnly 1 class of glucose-lowering agents—sodium-glucose cotransporter 2 (SGLT2) inhibitors—has been reported to decrease the risk of cardiovascular events primarily by reducing the risk of the development or progression of heart failure. In a landmark trial called Empagliflozin, Cardiovascular Outcomes, and Mortality in Type 2 Diabetes [EMPA-REG Outcomes], long-term treatment with empagliflozin prevented fatal and nonfatal heart failure events but did not reduce the risk of myocardial infarction or stroke in diabetic patients.ObservationsThe beneficial effect of SGLT2 inhibitors on heart failure cannot be explained by their actions on glycemic control or as osmotic diuretics. Instead, in the kidneys, SGLT2 functionally interacts with the sodium-hydrogen exchanger, which is responsible for the majority of sodium tubular reuptake following filtration. The activity of sodium-hydrogen exchanger is markedly increased in patients with heart failure and may be responsible for both resistance to diuretics and to endogenous natriuretic peptides. In addition, in the heart, empagliflozin appears to inhibit sodium-hydrogen exchange, which may in turn lead to a reduction in cardiac injury, hypertrophy, fibrosis, remodeling, and systolic dysfunction. Furthermore, the major pathophysiological derangements of heart failure and a preserved ejection fraction may be mitigated by the actions of SGLT2 inhibitors to reduce blood pressure, body weight, and fluid retention as well as to improve renal function. The benefits of spironolactone in patients with heart failure with either a reduced or a preserved ejection fraction may also be attributable to the actions of the drug to inhibit the sodium-hydrogen exchange mechanism.Conclusions and RelevanceThe benefits of SGLT2 inhibitors in heart failure may be mediated by the inhibition of sodium-hydrogen exchange rather than the effect on glucose reabsorption. This hypothesis has important implications for the design and analysis of large-scale outcomes trials involving diabetic or nondiabetic patients with chronic heart failure.

Multiple Comorbidities and Response to Cardiac Resynchronization Therapy: MADIT-CRT Long-Term Follow-Up

BackgroundData regarding cardiac resynchronization therapy (CRT) in patients with multiple comorbidities are limited. ObjectivesThis study evaluated the association of multiple comorbidities with the benefits of CRT over implantable cardioverter-defibrillator (ICD) alone. MethodsWe examined 1,214 MADIT-CRT (Multicenter Automatic Defibrillator Implantation Trial with Cardiac Resynchronization Therapy) study patients with left bundle branch block (LBBB) and 0, 1, 2, or ≥3 comorbidities, including renal dysfunction, hypertension (HTN), diabetes, coronary artery disease, history of atrial arrhythmias, history of ventricular arrhythmias, current smoking, and cerebrovascular accident. In an adjusted analysis, we analyzed risk of heart failure (HF) events or death by comorbidity group in all patients and in patients with CRT with defibrillator (CRT-D) versus ICD. Then we examined percent change in left ventricular (LV) end-diastolic volume, LV end-systolic volume, LV ejection fraction, left atrial volume, and LV dyssynchrony at 1-year in CRT-D patients by comorbidity group. ResultsThere was an inverse relationship between comorbidity burden and improvements in LV end-systolic volume, LV end-diastolic volume, left ventricular ejection fraction, left atrial volume, and LV dyssynchrony. In an adjusted model, there was an increasing risk of death or nonfatal HF events with increasing comorbidity burden regardless of treatment group (p < 0.001). During a mean follow-up of 4.65 years, there was no interaction with respect to comorbidity burden and the benefit of CRT-D versus ICD only for death or nonfatal HF events (interaction p = 0.943). In the groups with greatest comorbidity burden (2 and ≥3), the absolute risk reduction associated with CRT-D over ICD alone appeared greater than that seen for groups with less comorbidity burden (0 and 1). ConclusionsDuring long-term follow-up of MADIT-CRT study patients with LBBB randomized to CRT-D, there were differences in HF or death risk and in the degree of reverse remodeling among comorbidity groups. However, the burden of comorbidity does not appear to compromise the clinical benefits of CRT-D compared with ICD alone.

Cardiorespiratory fitness and nonfatalcardiovascular events: A population-based follow-up study

To examine the prognostic value of cardiorespiratory fitness (CRF) with risk of first major nonfatal myocardial infarction (MI), stroke, and heart failure (HF) events. Cardiorespiratory fitness, as measured by maximal oxygen uptake, was assessed at baseline in a prospective cohort of 2,089 men aged 42 to 61years. During a mean (SD) follow-up of 19.1(8.4) years, 522 nonfatal acute MI events, 198 acute all-cause nonfatal stroke events, and 221 nonfatal HF events were recorded. The hazard ratio per 1-metabolic-equivalent increase in CRF was 0.93 (95% CI 0.88-0.97) for nonfatal MI, 0.94 (95% CI0.87-1.01) for nonfatal stroke, and 0.84 (95% CI 0.78-0.91) for nonfatal HF events after adjustment for cardiovascular risk factors (age, systolic blood pressure, body mass index, history of cardiovascular disease, diabetes, smoking, alcohol use, serum creatinine, low-density lipoprotein levels, physical activity, and socioeconomic status). Further adjustment for left ventricular hypertrophy and resting heart rate did not attenuate these associations. Addition of CRF to conventional cardiovascular disease risk factors significantly improved both discrimination (C index) and category free net reclassification index (cf-NRI) for nonfatal MI (change in C index, 0.015 [95% CI 0.010-0.020] and change in cf-NRI 0.27, P<.01) and HF (change in C index 0.040 [95% CI 0.010-0.060] and change in cf-NRI 0.88, P<.01). In this Finnish population, there is a strong, inverse, and independent association between CRF and acute nonfatal MI and HF risk.

Abstract 17210: Cardiorespiratory Fitness and Non Fatal Cardiovascular Events

Introduction: To examine the relationship between cardiorespiratory fitness (CRF) and risk of non-fatal cardiovascular events. Methods: Cardiorespiratory fitness, as measured by maximal oxygen uptake (VO2max), was assessed at baseline in a prospective cohort of 2,089 men aged 42-61 years from the Kuopio Ischaemic Heart Disease Study (KIHD). Results: During a mean follow-up of 19.1 years (SD 8.4), 522 non-fatal acute myocardial infarction (MI) events, 198 acute all cause non-fatal stroke events and 221 non-fatal incident heart failure (HF) events were recorded. The hazard ratio (HR) per 1 MET increase in CRF was 0.93(95% CI: 0.88-0.97) for non-fatal MI, 0.94(95% CI: 0.87-1.01) for non-fatal stroke and 0.84(95% CI: 0.78-0.91) for non-fatal HF events after adjustment for established cardiovascular risk factors (age, systolic blood pressure, body mass index, history of cardiovascular disease, diabetes, smoking, alcohol use, serum creatinine, low density lipoprotein levels, physical activity and socioeconomic status). Further adjustment for additional risk factors did not substantially attenuate these associations. In a comparison of extreme quartiles of CRF levels, the corresponding adjusted HRs were 0.74 (95% CI: 0.55-0.99) for non-fatal MI, 0.91(95% CI: 0.58-1.44) non-fatal stroke and 0.49(95% CI: 0.30-0.80) for non-fatal HF respectively, Figures 1&amp; 2. Conclusions: In this Finnish population, there is a strong, inverse, and independent association between CRF and non-fatal MI and HF risk, but not for acute non-fatal stroke events. The protective effect of CRF on non-fatal cardiovascular events needs further investigation in larger studies.

Impact on clinical events and healthcare costs of adding telemedicine to multidisciplinary disease management programmes for heart failure: Results of a randomized controlled trial

Background The role of telemedicine in the management of patients with chronic heart failure (HF) has not been fully elucidated. We hypothesized that multidisciplinary comprehensive HF care could achieve better results when it is delivered using telemedicine. Methods and results In this study, 178 eligible patients with HF were randomized to either structured follow-up on the basis of face-to-face encounters (control group, 97 patients) or delivering health care using telemedicine (81 patients). Telemedicine included daily signs and symptoms based on telemonitoring and structured follow-up by means of video or audio-conference. The primary end-point was non-fatal HF events after six months of follow-up. The median age of the patients was 77 years, 41% were female, and 25% were frail patients. The hazard ratio for the primary end-point was 0.35 (95% confidence interval (CI), 0.20–0.59; p-value < 0.001) in favour of telemedicine. HF readmission (hazard ratio 0.39 (0.19–0.77); p-value=0.007) and cardiovascular readmission (hazard ratio 0.43 (0.23–0.80); p-value=0.008) were also reduced in the telemedicine group. Mortality was similar in both groups (telemedicine: 6.2% vs control: 12.4%, p-value > 0.05). The telemedicine group experienced a significant mean net reduction in direct hospital costs of €3546 per patient per six months of follow-up. Conclusions Among patients managed in the setting of a comprehensive HF programme, the addition of telemedicine may result in better outcomes and reduction of costs.