ESC Heart Failure最新文献

Aims: The Tpeak-Tend interval on electrocardiogram may be a predictor of worse outcomes in Takotsubo syndrome (TTS), but the mechanisms have not been fully determined. This study aimed to investigate the relationships between the corrected Tpeak-Tend (cTp-e) interval and coronary microvascular-dysfunction (CMD) assessed by the angiography-derived index of microvascular resistance (Angio-IMR) and the in-hospital prognosis in patients with TTS.

Methods and results: We retrospectively evaluated 111 consecutive patients admitted for TTS who underwent coronary angiography at Kindai University Hospital from October 2009 to July 2023. The Tpeak-Tend interval was defined as the time interval between the peak and the end of the T wave in electrocardiogram lead V5 on admission. Angio-IMR was assessed from aortic pressure, quantitative flow ratio (QFR), vessel length and hyperemic velocity using the formula described in validation studies. QFR, vessel length and hyperemic velocity was derived from coronary angiography and QAngio XA 3D software package. The degree of CMD was assessed by the maximum Angio-IMR value in each of the three coronary arteries. The primary endpoint was the relationship between the grade of a prolonged cTp-e interval on admission and Angio-IMR. The secondary endpoint was the relationship between the grade of a prolonged cTp-e interval on admission and in-hospital adverse cardiovascular events (composite of acute heart failure, cardiogenic shock, life-threatening arrhythmia, thrombotic events, stroke and all-cause death). The median age was 77.5 [71.0-83.0] years, and most patients were women (82.0%). The median cTp-e interval was 114.5 [91.2-147.0] ms. The patients were categorized according to the tertiles of the cTp-e interval (T1: 52.4-96.9 ms; T2: 100.1-129.1 ms; T3: 131.7-309.8 ms). There was a stepwise increment in the values of maximum Angio-IMR in each of the three coronary arteries in tertiles of the cTp-e interval (T1 vs. T2 vs. T3: 16.1 [14.7-19.3] vs. 21.8 [16.0-31.1] vs. 29.0 [27.2-31.9], P < 0.001). In-hospital adverse cardiovascular events occurred in 53 of 111 patients (47.7%). There was a stepwise increment in the incidence of in-hospital adverse cardiovascular events in tertiles of the cTp-e interval (T1 vs. T2 vs. T3: 27.1% vs. 54.1% vs. 62.2%, P = 0.007). The multivariable analysis showed that prolonged cTp-e interval (OR: 1.30; 95% CI: 1.12-1.56; P < 0.001) was independent predictors of in-hospital adverse cardiovascular events.

Conclusions: The Tpeak-Tend interval on admission reflected CMD and predicts in-hospital adverse cardiovascular events in patients with TTS.

Aims: This study aimed to identify factors associated with frailty in heart failure (HF) patients, focusing on demographic, biochemical and health-related variables. It also explored the correlation between frailty and comorbidities such as malnutrition, cognitive impairment and depression, assessing how these factors interact to influence frailty risk.

Methods: A total of 250 HF patients (mean age 73.5 ± 7.2 years; 45.6% female) hospitalized for acute decompensated HF were included. Frailty was assessed using Fried phenotype criteria. Cognitive function, depression and nutritional status were evaluated using validated instruments [Mini-Mental State Examination (MMSE), Patient Health Questionnaire-9 (PHQ-9) and Mini Nutritional Assessment (MNA)]. Biochemical markers included C-reactive protein (CRP), N-terminal prohormone of brain natriuretic peptide (NT-proBNP), haemoglobin, estimated glomerular filtration rate (eGFR) and systolic blood pressure (SBP). Statistical analyses, including logistic regression, were performed to assess associations and odds ratios (ORs) for frailty, adjusted for inflammation and HF type.

Results: Frailty was present in 60.4% of patients. Frail individuals exhibited significantly higher CRP (median 4.60 vs. 2.54 mg/L, P < 0.001) and NT-proBNP (median 2558.8 vs. 1102.6 pg/mL, P = 0.001) and lower haemoglobin (13.7 vs. 14.3 g/dL, P = 0.012), eGFR (62 vs. 71 mL/min/1.73 m², P = 0.025) and SBP (130 vs. 134 mmHg, P = 0.026). Each 10% increase in CRP was associated with a 5.5% increase in frailty odds (P < 0.001). Frailty was linked to cognitive impairment (OR 2.1, P = 0.018), malnutrition (OR 3.0, P < 0.001) and depression (OR 3.1, P < 0.001), while high adherence to treatment reduced frailty risk by 78.9% (P = 0.027). Interactions were observed between cognitive impairment and body mass index (BMI) (P = 0.020), where higher BMI mitigated the frailty odds difference between cognitively impaired and unimpaired patients. Depression's association with frailty odds varied by adherence levels (P = 0.034) and central obesity (P = 0.047), with the absence of depression offering protection against frailty in patients with central obesity. These interactions remained significant after adjustment for HF type and left ventricular ejection fraction (LVEF) and were consistent across stratifications by these factors.

Conclusions: Frailty in HF is influenced by inflammatory markers, cognitive impairment and psychosocial factors. Elevated CRP and NT-proBNP were strong predictors of frailty. Cognitive impairment and depression were key modifiable factors, interacting with BMI, adherence and obesity. Targeting these factors with early interventions could mitigate frailty risk, improving outcomes and quality of life in HF patients.

Aims: Risk prediction indices used in worsening heart failure (HF) vary in complexity, performance, and the type of datasets in which they were validated. We compared the performance of seven risk prediction indices in a contemporary cohort of patients hospitalized for HF.

Methods and results: We assessed the performance of the Length of stay and number of Emergency department visits in the prior 6 months (LE), Length of stay, number of Emergency department visits in the prior 6 months, and admission N-Terminal prohormone of brain natriuretic peptide (NT-proBNP (LENT), Length of stay, Acuity, Charlson co-morbidity index, and number of Emergency department visits in the prior 6 months (LACE), Get With The Guidelines Heart Failure (GWTG), Readmission Risk Score (RRS), Enhanced Feedback for Effective Cardiac Treatment model (EFFECT), and Acute Decompensated Heart Failure National Registry (ADHERE) risk indices among consecutive patients hospitalized for HF and discharged alive from January 2017 to December 2019 in a network of hospitals in England. The primary composite outcome was 30-day all-cause mortality or readmission. We assessed model discrimination and overall accuracy using the C-statistic (higher values, better) and Brier score (lower values, better), respectively. Among 1206 patients in the cohort, 45.0% were female, mean (SD) age was 76.6 (11.7) years, and mean (SD) left ventricular ejection fraction was 43.0% (11.6). At 30 days, 236 (19.6%) patients were readmitted and 28 (2.3%) patients died, with 264 (21.9%) patients experiencing either readmission or death. The LENT index offered the combination of greatest risk discrimination and accuracy for the primary composite outcome (C-statistic: 0.97; 95% CI 0.96, 0.98; 0.29; Brier score: 0.05). The LE (C-statistic: 0.95; 95% CI 0.93, 0.96; Brier score: 0.06) and LACE (C-statistic: 0.90; 95% CI 0.88, 0.92; Brier score 0.09) indices had high discrimination and accuracy. Discrimination and accuracy were modest with the RRS (C-statistic: 0.65; 95% CI 0.61, 0.69; Brier score: 0.16) and EFFECT (C-statistic: 0.64; 95% CI 0.60, 0.67; Brier score: 0.16) score; and poor with the GWTG-HF (C-statistic: 0.62; 95% CI 0.58, 0.66; Brier score: 0.17) and ADHERE (C-statistic: 0.54; 95% CI 0.50, 0.57; Brier score: 0.17) scores.

Conclusions: In a study that compared the performance of seven risk prediction indices in a contemporary cohort of patients hospitalized for HF, the simple LENT index offered the greatest combination of discrimination and accuracy for the primary composite outcome of 30-day all-cause mortality or readmission. This three-variable index -using length of hospital stay, preceding emergency department visits and admission NT-proBNP level- is a practical and reliable way to assess prognosis following hospitalization for HF.

Aims: Right ventricular (RV) failure (RVF) after left ventricular assist device (LVAD) implant is an important cause of morbidity and mortality. Modern, data-driven approaches for defining and predicting RVF have been under-utilized.

Methods: Two hundred thirty-two patients were identified with a mean age of 55 years; 40 (17%) were women, 132 were (59%) Caucasian and 74 (32%) were Black. Patients were split between Interagency Registry for Mechanically Assisted Circulatory Support (INTERMACS) Classes 1, 2 and 3 (25%, 38% and 34%, respectively). Within this group, 'provisional RVF' patients were identified, along with 'no RVF' patients. 'No RVF' patients were defined as patients who never demonstrated more than moderate RV dysfunction on a post-LVAD transthoracic echocardiogram (TTE) (ordinal RV function <3), never required an RV assist device (RVAD), were not discharged on sildenafil and were not on a pulmonary vasodilator or inotropic medication at 3 months after LVAD implant. In total, n = 67 patients were defined as 'no RVF'. The remaining patients represented the 'provisional RVF' population (n = 165). Extensive electronic health records queries yielded >1200 data points per patient. Using <1 and >1 month post-LVAD time windows motivated by established, expert-consensus definitions of 'early' and 'late' post-implant RVF, unbiased clustering analysis was performed to identify hidden patient 'phenogroups' within these two established RVF populations. Clusters were compared on post-implant clinical metrics and 1 year outcomes. Lastly, pre-implant metrics were used to generate models for predicting post-implant RVF phenogroup.

Results: Within the 'early RVF' time window, distinct 'well' and 'sick' patient phenogroup clusters were identified. These clusters had similar RV function and pulmonary vasodilator usage during the first month after LVAD but differed significantly in heart failure therapy tolerance, renal (P < 0.001) and hepatic (P = 0.013) function, RVAD usage (P = 0.001) and 1 year mortality (P = 0.047). Distinct 'well' and 'sick' phenogroups were also identified in the 'late RVF' time window. These clusters had similar RV function (P = 0.111) and RVAD proportions (P = 0.757) but differed significantly in heart failure medication tolerance, pulmonary vasodilator usage (P = 0.001) and 1 year mortality (P < 0.001). Prediction of phenogroup clusters from the 'early RVF' population achieved an area under the receiver operating characteristic curve (AUROC) of 0.84, with top predictors including renal function, liver function, heart rate and pre-LVAD RV function.

Conclusions: Distinct, potentially predictable phenogroups of patients who have significantly different long-term outcomes exist within consensus-defined post-LVAD RVF populations.

Aims: Ischaemic mitral regurgitation (MR) is a dynamic condition influenced by global and regional left ventricular remodelling as well as mitral valvular deformation. Exercise testing plays a substantial role in assessing the haemodynamic relevance of MR and is recommended by current guidelines. We aimed to assess the prevalence, haemodynamic consequences, and prognostic impact of dynamic MR using isometric handgrip exercise.

Methods and results: Heart failure patients with ischaemic cardiomyopathy and at least mild MR who underwent handgrip echocardiography at the University Hospital Duesseldorf between January 2018 and September 2021 were enrolled. Patients were followed-up for 1 year to assess a combined endpoint including all-cause mortality, heart failure hospitalization, mitral valve surgery/interventions, ventricular assist device implantation and heart transplantation. One hundred thirty-three patients with ischaemic cardiomyopathy were included (age 75 ± 10 years; 21% female; LVEF 35 ± 9%). At rest, 70 patients (53%) presented with mild MR, 54 patients had moderate MR (41%), and 9 patients (7%) showed severe MR. Twenty-five patients (20%) with non-severe MR at rest, developed severe MR during handgrip exercise. Patients with dynamic MR had larger left atrial dimensions, increased wall motion score index and larger tenting area at rest. Multivariate analysis identified MR severity during exercise [HR 1.998 (1.367-2.938)] and exercise TAPSE [HR 0.913 (0.853-0.973)] as predictors of the combined endpoint.

Conclusions: The haemodynamic changes provoked by isometric exercise unmasked dynamic severe MR in a significant number of patients with non-severe MR at rest. These data may have implications for therapeutic decision-making in symptomatic patients with non-severe MR at rest.

Aims: Despite receiving guideline-directed medical heart failure (HF) therapy, patients with pulmonary hypertension associated with left heart disease (PH-LHD) experience higher mortality and hospitalization rates than the general HF population. AZD3427 is a functionally selective, long-acting mimetic of relaxin, a hormone that has the potential to induce vasodilation and prevent fibrosis. In a phase 1b study conducted in patients with HF, AZD3427 demonstrated a favourable safety and pharmacokinetic profile. To address the unmet medical need in patients with PH-LHD in the context of HF, AZD3427 is currently under development as a potential treatment option.

Methods and results: The Re-PHIRE study is a phase 2b, randomized, double-blind, placebo-controlled, multicentre, dose-ranging study to evaluate the effect of AZD3427 on a broad range of PH-LHD phenotypes. In total, 220 patients will be randomized to four treatment groups to receive a subcutaneous injection of AZD3427 or placebo every 2 weeks for 24 weeks. The primary endpoint of the study is the change in pulmonary vascular resistance in patients treated with AZD3427 versus placebo after 24 weeks of treatment. Key secondary endpoints include changes in mean pulmonary arterial pressure, pulmonary artery wedge pressure, systemic vascular resistance, 6-min walking distance, N-terminal pro B-type natriuretic peptide levels, echocardiographic parameters, and health-related quality of life (assessed by the Kansas City Cardiomyopathy Questionnaire).

Conclusions: Re-PHIRE is the first study of a relaxin mimetic in patients with PH-LHD. The insights gained from the Re-PHIRE study are expected to inform the further development of AZD3427 in the PH-LHD population, including identifying the most suitable pulmonary hypertension and HF phenotypes for treatment.

Aims: Sodium-glucose cotransporter 2 (SGLT2) inhibitors (SGLT2i) have demonstrated effectiveness in reducing cardiovascular death and heart failure hospitalization (HFH). However, the efficacy and safety of SGLT2 inhibitors in elderly patients with poor general status, such as very low bodyweight or low nutritional status, who are not included in randomized controlled trials, has not yet been examined. In a real-world setting, the introduction of SGLT2 inhibitors to such elderly patients is a very difficult decision to make. We therefore examined the efficacy and safety of these drugs in elderly heart failure patients in a real-world setting.

Methods and results: In Kokura Memorial Hospital, a retrospective study was conducted on 1559 patients over 80 years old hospitalized for HF between 2018 and 2023. Among them, 1326 were included in the non-SGLT2i group and 233 in the SGLT2i group. A multivariate Cox regression model was used to compare the risk of primary composite outcome (all-cause death and HFH) and secondary safety composite outcome (ischaemic stroke, urinary tract infection and dehydration) at 1 year post-discharge between the two groups. The cumulative 1 year incidence of the composite outcome was significantly higher in the non-SGLT2i group (47.3% vs. 31.6%, P < 0.01). SGLT2 inhibitors independently reduced the risk of all-cause death [adjusted hazard ratio (HR): 0.58, 95% confidence interval (CI): 0.39-0.87, P < 0.01] and HFH (adjusted HR: 0.69, 95% CI: 0.52-0.91, P < 0.01), whereas the risk of safety composite events was not increased (adjusted HR: 0.80, 95% CI: 0.49-1.29, P = 0.36). Subgroup analysis showed no significant interactions between age, diabetes, body mass index, left ventricular ejection fraction, clinical frailty scale, geriatric nutritional risk index and SGLT2 inhibitors consistently reduced composite outcomes across all strata. Similarly, SGLT2 inhibitors did not increase safety composite outcomes at any strata.

Conclusions: SGLT2 inhibitors reduce the risk of all-cause death and HFH without increasing adverse events, even in patients over 80 years old. It may be that SGLT2 inhibitors are effective and safe in patients who are basically hesitant to be introduced to SGLT2 inhibitors, such as those with high frailty, low nutritional status or very low bodyweight.

Aims: Heart failure (HF) patients may lack improvement of left ventricular (LV) ejection fraction (LVEF) despite optimal HF medication comprising an angiotensin receptor-neprilysin inhibitor (ARNI). Therefore, we aimed to identify key predictors for LV functional enhancement and prognostic reverse cardiac remodelling in HF patients on ARNI treatment.

Methods: We retrospectively analysed 294 consecutive patients with HF with reduced (HFrEF) or mildly reduced (HFmrEF) ejection fraction in our 'EnTruth' patient registry. LVEF was determined by echocardiography at initiation of ARNI and at 12 months of follow-up. We assessed the predictive value of clinically relevant patient-, HF- and treatment-related parameters in regard to changes in LVEF and all-cause mortality using medoid clustering and the XGBoost machine learning algorithm.

Results: Cluster analysis integrating clinically relevant patient characteristics unveiled four characteristic sub-phenotypes of patients with HFrEF and HFmrEF, respectively. Distinct clusters exhibit a strong (P < 0.05) therapeutic response to ARNI treatment and enhanced LV function. Key patient criteria, such as duration and aetiology of HF, renal function and de novo ARNI treatment, were significantly (P < 0.05) associated with change of LVEF and independently predicted cardiac remodelling. By training various machine learning models on relevant clinical parameters, stratification of LVEF improvement by XGBoost resulted in a high prediction accuracy. The stratification of patients with HFrEF [area under the receiver operating characteristic curve (AUC) = 0.77] and HFmrEF (AUC = 0.70) led to an increased diagnostic accuracy of LVEF improvement in the validation cohort. Using machine learning, the likelihood of cardiac remodelling following ARNI treatment, as indicated by our newly established EnTruth score, was directly associated with absolute LVEF improvement in both HFrEF (r = 0.51, P < 0.0001) and HFmrEF (r = 0.42, P = 0.001). Ultimately, patients with HFrEF and a high EnTruth score have a lower risk of all-cause mortality (P < 0.05 in survival analysis).

Conclusions: Recognition of essential clinical factors by integrating machine learning and cluster analyses may help to identify HF patients benefiting from improvement of LVEF following ARNI treatment. Early identification of those patients with a high response to ARNI treatment may allow a more refined selection of patients benefiting from an early escalation of HF treatment or interventional therapy.