Vericiguat is a soluble guanylate cyclase stimulator and improves survival in patients with heart failure (HF) with reduced ejection fraction (HFrEF) and an increased risk of decompensation. As real-world data on how many patients could be eligible for vericiguat therapy derive from outdated registries, we aimed to assess eligibility in a prospective cohort of patients with HF. Data from consecutive HF patients undergoing an elective ambulatory visit at five university hospitals from 3 July to 28 July 2023 were collected. Independent investigators assessed which patients (i) met the eligibility criteria of the VICTORIA trial, (ii) complied with HF guideline recommendations, (iii) met regulatory agency criteria, or (iv) met criteria for refundability according to the Italian regulatory agency. Patients (n=346, 72% men, median age 69years) had HFrEF in 57% of cases, left ventricular ejection fraction<45% in 68%, and New York Heart Association class II-IV symptoms in 76%. Patients meeting the eligibility criteria of the VICTORIA trial or European and American HF Guideline recommendations were 9% and 13%, respectively. Patients meeting Food and Drug Administration (FDA) or European Medicines Agency (EMA) label criteria were 19% and 17%, respectively. Drug costs would be covered by the Italian National Health System in 10% of patients [if a sodium-glucose cotransporter-2 inhibitor (SGLT2i) is not mandatory] or in 8% (if an SGLT2i is requested). In a real-world study, 9% of patients met the eligibility criteria of the VICTORIA trial, but up to 13% complied with guideline recommendations and up to 19% met FDA or EMA criteria. In Italy, drug costs would be covered by up to 10% of patients.

Traditional approaches to designing clinical trials for heart failure (HF) have historically relied on expertise and past practices. However, the evolving landscape of healthcare, marked by the advent of novel data science applications and increased data availability, offers a compelling opportunity to transition towards a data-driven paradigm in trial design. This research aims to evaluate the scope and determinants of disparities between clinical trials and registries by leveraging natural language processing for the analysis of trial eligibility criteria. The findings contribute to the establishment of a robust design framework for guiding future HF trials. Interventional phase III trials registered for HF on ClinicalTrials.gov as of the end of 2021 were identified. Natural language processing was used to extract and structure the eligibility criteria for quantitative analysis. The most common criteria for HF with reduced ejection fraction (HFrEF) were applied to estimate patient eligibility as a proportion of registry patients in the ASIAN-HF (N=4868) and BIOSTAT-CHF registries (N=2545). Of the 375 phase III trials for HF, 163 HFrEF trials were identified. In these trials, the most frequently encountered inclusion criteria were New York Heart Association (NYHA) functional class (69%), worsening HF (23%), and natriuretic peptides (18%), whereas the most frequent comorbidity-based exclusion criteria were acute coronary syndrome (64%), renal disease (55%), and valvular heart disease (47%). On average, 20% of registry patients were eligible for HFrEF trials. Eligibility distributions did not differ (P=0.18) between Asian [median eligibility 0.20, interquartile range (IQR) 0.08-0.43] and European registry populations (median 0.17, IQR 0.06-0.39). With time, HFrEF trials became more restrictive, where patient eligibility declined from 0.40 in 1985-2005 to 0.19 in 2016-2022 (P=0.03). When frequency among trials is taken into consideration, the eligibility criteria that were most restrictive were prior myocardial infarction, NYHA class, age, and prior HF hospitalization. Based on 14 trial criteria, only one-fifth of registry patients were eligible for phase III HFrEF trials. Overall eligibility rates did not differ between the Asian and European patient cohorts.

Improvement in left ventricular ejection fraction (impEF) often presents in contemporary acute myocardial infarction (AMI) patients. New-onset atrial fibrillation (NOAF) during AMI is an important predictor of subsequential heart failure (HF), while its impact on the trajectory of post-MI left ventricular ejection fraction (LVEF) and prognostic implication in patients with and without impEF remains undetermined. We aimed to investigate the prognostic impacts of NOAF in AMI patients with and without impEF. Consecutive AMI patients without a prior history of AF between February 2014 and March 2018 with baseline LVEF≤40% and had ≥1 LVEF measurement after baseline were included. ImpEF was defined as a baseline LVEF≤40% and a re-evaluation showed both LVEF>40% and an absolute increase of LVEF≥10%. Persistently reduced EF (prEF) was defined as the second measurement of LVEF either ≤40% or an absolute increase of LVEF<10%. The primary endpoint was a major adverse cardiac event (MACE) that was composed of cardiovascular death and HF hospitalization. Cox regression analysis and competing risk analysis were performed to assess the association of post-MI NOAF with MACE. Among 293 patients (mean age: 66.6±11.3years, 79.2% of males), 145 (49.5%) had impEF and 67 (22.9%) developed NOAF. Higher heart rate (odds ratio [OR]: 0.84, 95% confidence interval [CI]: 0.73-0.97; P=0.015), prior MI (OR: 0.25, 95% CI: 0.09-0.69; P=0.008), and STEMI (OR: 0.40, 95% CI: 0.21-0.77; P=0.006) were independent predictors of post-MI impEF. Within up to 5years of follow-up, there were 22 (15.2%) and 53 (35.8%) MACE in patients with impEF and prEF, respectively. NOAF was an independent predictor of MACE in patients with impEF (hazard ratio [HR]: 7.34, 95% CI: 2.49-21.59; P<0.001) but not in those with prEF (HR: 0.78, 95% CI: 0.39-1.55; P=0.483) after multivariable adjustment. Similar results were obtained when accounting for the competing risk of all-cause death (subdistribution HR and 95% CIs in impEF and prEF were 6.47 [2.32-18.09] and 0.79 [0.39-1.61], respectively). The NOAF was associated with an increased risk of cardiovascular outcomes in AMI patients with impEF.

In heart failure (HF), inflammation is linked to malnutrition and impaired physical function. In this study, we aimed to assess how novel nutritional-inflammatory markers and lymphocyte-to-C-reactive protein ratio (LCR) and score (LCS) are associated with the nutritional status, physical function, and prognosis of patients with HF. This study was a secondary analysis of the FRAGILE-HF study, a prospective observational study conducted across 15 hospitals in Japan. We included 1212 patients (mean age, 80.2±7.8years; 513 women) hospitalized with HF, who were classified into three groups according to their LCS score: 0 (n=498), 1 (n=533), and 2 (n=181). Baseline data on physical examination, echocardiography, blood test results (including lymphocyte counts and CRP levels), and oral medication usage were collected in a clinically compensated state before discharge. Nutritional status and physical function were evaluated using several indices and tests. The primary outcome of this study was all-cause death within 2years. Univariate and multivariate linear regression analyses were performed to evaluate the associations among the nutritional status, physical function, and LCR/LCS. Patients with an LCS score of 2 were older and had a lower body mass index than those in the other two groups. Multivariate linear regression analysis revealed that lower LCR and higher LCS were independently associated with worse nutritional status, lower handgrip strength, shorter physical performance battery score, and shorter 6-min walk distance. At 2years, all-cause death occurred in 254 patients: 86 (17.6%), 113 (21.5%), and 55 (30.9%) with LCS scores of 0, 1, and 2, respectively (P=0.001). Cox proportional hazards analysis revealed that LCR and LCS were significantly associated with 2-year mortality even after adjusting for the conventional risk model (LCS score, 0 vs. 2: hazard ratio, 1.64; 95% confidence interval [CI]; 1.14-2.35; P=0.007; log-transformed LCR: hazard ratio, 0.88; 95% CI, 0.81-0.95; P=0.002). LCR yielded additional prognostic predictability compared with the conventional risk model (continuous net reclassification improvement, 0.153; 95% CI, 0.007-0.299; P=0.041). LCR and LCS emerge as potential predictors of nutritional status, physical function, and prognosis in older patients with HF.

One third of patients do not improve after cardiac resynchronization therapy (CRT). Septal flash (SF) and apical rocking (ApRock) are deformation patterns observed on echocardiography in most patients eligible for CRT. These markers of mechanical dyssynchrony have been associated to improved outcome after CRT in observational studies and may be useful to better select patients. The aim of this trial is to investigate whether the current guideline criteria for selecting patients for CRT should be modified and include SF and ApRock to improve therapy success rate, reduce excessive costs and prevent exposure to device-related complications in patients who would not benefit from CRT. The AMEND-CRT trial is a multicentre, randomized, parallel-group, double-blind, sham-controlled trial with a non-inferiority design. The trial will include 578 patients scheduled for CRT according to the 2021 ESC guidelines who satisfy all inclusion criteria. The randomization is performed 1:1 to an active control arm ('guideline arm') or an experimental arm ('echo arm'). All participants receive a device, but in the echo arm, CRT is activated only when SF or ApRock or both are present. The outcome of both arms will be compared after 1year. The primary outcome measures are the average change in left ventricular end-systolic volume and patient outcome assessed using a modified Packer Clinical Composite Score. The findings of this trial will redefine the role of echocardiography in CRT and potentially determine which patients with heart failure and a prolonged QRS duration should receive CRT, especially in patients who currently have a class IIa or class IIb recommendation.

Currently, there is limited data on prognostic indicators after insertion of percutaneous ventricular assist device (PVAD) in the treatment of cardiogenic shock (CS). This study evaluated the prognostic role of cardiac power output (CPO) ratio, defined as CPO at 24h divided by early CPO (30min to 2h), in CS patients after PVAD. Consecutive CS patients from the QEH-PVAD Registry were followed up for survival at 90days after PVAD. Among 121 consecutive patients, 98 underwent right heart catheterization after PVAD, with CPO ratio available in 68 patients. The CPO ratio and 24-h CPO, but not the early CPO post PVAD, were significantly associated with 90-day survival, with corresponding area under curve in ROC analysis of 0.816, 0.740, and 0.469, respectively. In multivariate analysis, only the CPO ratio and lactate level at 24h remained as independent survival predictors. The CPO ratio was not associated with age, sex, and body size. Patients with lower CPO ratio had significantly lower coronary perfusion pressure, worse right heart indices, and higher pulmonary vascular resistance. A lower CPO ratio was also significantly associated with mechanical ventilation and higher creatine kinase levels in myocardial infarction patients. In post-PVAD patients, the CPO ratio outperformed the absolute CPO values and other haemodynamic metrics in predicting survival at 90days. Such a proportional change of CPO over time, likely reflecting native heart function recovery, may help to guide management of CS patients post-PVAD.

Veno-arterial extracorporeal membrane oxygenation (VA-ECMO) is a life-saving procedure for supporting patients with cardiogenic shock after cardiac surgery. This work aimed to analyse the impact of changes in blood lactate levels on the survival of patients on post-cardiotomy ECMO (PC-ECMO) and whether lactate clearance (LC) performs better than absolute lactate levels. We retrospectively analysed the data of adult patients who received PC-ECMO at our centre between 2016 and 2022. The primary outcome was the in-hospital mortality rate. Arterial lactate levels were measured at ECMO initiation, peak and 12 and 24h after VA-ECMO support. LC was calculated at 12 and 24h. Out of 2368 patients who received cardiac surgeries, 152 (median age, 48years; 57.9% of them were men) received PC-ECMO. Of them, 48 (31.6%) survived and were discharged, while 104 (68.4%) died during the index hospitalization. Non-survivors had higher frequencies of atrial fibrillation (41.35% vs. 12.5%, P<0.001), chronic kidney disease (26.9% vs. 6.3%, P=0.004), prolonged cardiopulmonary bypass (237 vs. 192min, P=0.016) and aortic cross-clamping times (160 vs. 124min, P=0.04) than survivors. Non-survivors had a significantly higher median Sequential Organ Failure Assessment (SOFA) score at ECMO initiation (13.5 vs. 9, P<0.001) and a lower median Survival After Veno-arterial ECMO (SAVE) score (-3 vs. 3, P<0.001) with higher SAVE classes (P<0.001) than survivors. After 12h of VA-ECMO support, the blood lactate level was negatively correlated with LC in survivors (r=-0.755, P<0.001) and non-survivors (r=-0.601, P<0.001). After 24h, the same negative correlation was identified between survivors (r=-0.764, P<0.001) and non-survivors (r=-0.847, P<0.001). Blood lactate levels measured at 12h to determine hospital mortality [>8.2mmol/L, area under the receiver operating characteristic curve (AUROC): 0.868] and 24h (>2.6mmol/L, AUROC: 0.896) had the best performance, followed by LC-T12 (<21.94%, AUROC: 0.807), LC-T24 (<40.3%, AUROC: 0.839) and peak blood lactate (>14.35mmol/L, AUROC: 0.828). The initial pre-ECMO blood lactate (>6.25mmol/L, AUROC: 0.731) had an acceptable ability to discriminate mortality but was less than the following measurements and clearance. Kaplan-Meier curves demonstrated that LC of <21.94% at T12h and <40.3% at T24h was associated with decreased survival (log-rank P<0.001). Cox proportional hazards regression analysis for mortality revealed that LC of <21.94% at T12h had an adjusted hazard ratio (HR) of 2.73 [95% confidence interval (CI): 1.64-5.762, P<0.001] and LC of <40.3% at T24h had an adjusted HR of 1.98 (95% CI: 1.46-4.173, P<0.001). The predictors of hospital mortality after PC-ECMO were the lactate level at 12h [odds ratio (OR): 1.67, 95% CI: 1.121-2.181, P=0.001], initial SOFA score (OR: 1.593, 95% CI: 1.15-2.73, P<0.001), initial blood lactate (OR: 1.21, 95% CI: 1.016-1.721, P=0.032) and atrial fibrillation (OR: 6.17, 95% CI: 2.37-57.214, P=0.003). Bivariate models using lactate levels and clearance at the same points revealed that blood lactate levels performed better than the clearance percentage. Serial measurements of arterial blood lactate and LC help in obtaining early prognostic guidance in adult patients supported by VA-ECMO after cardiac surgery. Absolute lactate levels, compared with LC at the same time points, demonstrated better performance in differentiating mortality.

Assessing the risk for HF rehospitalization is important for managing and treating patients with HF. To address this need, various risk prediction models have been developed. However, none of them used deep learning methods with real-world data. This study aimed to develop a deep learning-based prediction model for HF rehospitalization within 30, 90, and 365days after acute HF (AHF) discharge. We analysed the data of patients admitted due to AHF between January 2014 and January 2019 in a tertiary hospital. In performing deep learning-based predictive algorithms for HF rehospitalization, we use hyperbolic tangent activation layers followed by recurrent layers with gated recurrent units. To assess the readmission prediction, we used the AUC, precision, recall, specificity, and F1 measure. We applied the Shapley value to identify which features contributed to HF readmission. Twenty-two prognostic features exhibiting statistically significant associations with HF rehospitalization were identified, consisting of 6 time-independent and 16 time-dependent features. The AUC value shows moderate discrimination for predicting readmission within 30, 90, and 365days of follow-up (FU) (AUC:0.63, 0.74, and 0.76, respectively). The features during the FU have a relatively higher contribution to HF rehospitalization than features from other time points. Our deep learning-based model using real-world data could provide valid predictions of HF rehospitalization in 1year follow-up. It can be easily utilized to guide appropriate interventions or care strategies for patients with HF. The closed monitoring and blood test in daily clinics are important for assessing the risk of HF rehospitalization.

The frailty index based on laboratory tests (FI-lab) can identify individuals at increased risk for adverse health outcomes. The association between the FI-lab and all-cause mortality in patients with heart failure (HF) in the intensive care unit (ICU) remains unknown. This study aimed to determine the correlation between FI-lab and all-cause mortality to evaluate the impact of FI-lab on the prognosis of critically ill patients with HF. This retrospective observational study utilized data extracted from the Medical Information Mart for Intensive Care IV database. The FI-lab, which consists of 33 laboratory tests, was constructed. Patients were then grouped into quartiles (Q1-Q4) based on their FI-lab scores. Kaplan-Meier analysis was used to compare all-cause mortality among the four groups. A Cox proportional hazard analysis was conducted to examine the association between the FI-lab score and all-cause mortality. The incremental predictive value of adding FI-lab to classical disease severity scores was assessed using Harrell's C statistic, integrated discrimination improvement (IDI) and net reclassification improvement (NRI). Among 3021 patients, 838 (27.74%) died within 28days, and 1400 (46.34%) died within a 360day follow-up period. Kaplan-Meier analysis indicated that patients with higher FI-lab scores had significantly higher risks of all-cause mortality (log-rank P<0.001). Multivariable Cox regression suggested that FI-lab, evaluated as a continuous variable (for each 0.01 increase), was associated with increased 28day mortality [hazard ratio (HR) 1.02, 95% confidence interval (CI) (1.01-1.03), P<0.001] and 360day mortality [HR 1.02, 95% CI (1.01-1.02), P<0.001]. When assessed in quartiles, the 28day mortality risk [HR 1.66, 95% CI (1.28-2.15), P<0.001] and 360day mortality risk [HR 1.48, 95% CI (1.23-1.8), P<0.001] were significantly higher for FI-lab Q4 compared with FI-lab Q1. FI-lab significantly improved the predictive capability of classical disease severity scores for 28 and 360day mortality. In ICU patients diagnosed with HF, the FI-lab is a potent predictor of short-term and long-term mortality in critically ill patients with HF. The active use of FI-lab to identify high-risk groups among critically ill HF patients and initiate timely interventions may have significant value in improving the prognosis of critically ill patients with HF.