BACKGROUND: Dynamic arterial elastance (Eadyn) has been investigated for its ability to predict hypotension during the weaning of vasopressors. Our study focused on assessing Eadyn\'s performance in the context of critically ill adult patients admitted to the intensive care unit, regardless of diagnosis.
METHODS: Our study was conducted in accordance with the Preferred Reported Items for Systematic Reviews and Meta-Analysis checklist. The protocol was registered in PROSPERO (CRD42023421462) on May 26, 2023. We included prospective observational studies from the MEDLINE and Embase databases through May 2023. Five studies involving 183 patients were included in the quantitative analysis. We extracted data related to patient clinical characteristics, and information about Eadyn measurement methods, results, and norepinephrine dose. Most patients (76%) were diagnosed with septic shock, while the remaining patients required norepinephrine for other reasons. The average pressure responsiveness rate was 36.20%. The synthesized results yielded an area under the curve of 0.85, with a sensitivity of 0.87 (95% CI 0.74-0.93), specificity of 0.76 (95% CI 0.68-0.83), and diagnostic odds ratio of 19.07 (95% CI 8.47-42.92). Subgroup analyses indicated no variations in the Eadyn based on norepinephrine dosage, the Eadyn measurement device, or the Eadyn diagnostic cutoff to predict cessation of vasopressor support.
CONCLUSIONS: Eadyn, evaluated through subgroup analyses, demonstrated good predictive ability for the discontinuation of vasopressor support in critically ill patients.

BACKGROUND: The precise mechanisms leading to the development of heart failure with preserved ejection fraction (HFpEF) remain incompletely defined. In this study, an integrative approach utilizing untargeted proteomics and metabolomics was employed to delineate the altered proteomic and metabolomic profiles in patients with HFpEF compared to healthy controls.
METHODS: Data were collected from a prospective cohort consisting of 30 HFpEF participants and 30 healthy controls, matched by gender and age. plasma samples were analyzed by multi-omics platforms. The quantification of plasma proteins and metabolites was performed using data-independent acquisition-based liquid chromatography-tandem mass spectrometry (LC-MS/MS) and ultrahigh-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS), respectively. Additionally, Proteomic and metabolomic results were analyzed separately and integrated using correlation and pathway analysis. This was followed by the execution of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment studies to elucidate the biological relevance of the observed results.
RESULTS: A total of 46 significantly differentially expressed proteins (DEPs) and 102 differentially expressed metabolites (DEMs) were identified. Then, GO and KEGG pathway enrichment analyses were performed by DEPs and DEMs. Integrated analysis of proteomics and metabolomics has revealed Tuberculosis and African trypanosomiasis pathways that are significantly enriched and the DEPs and DEMs enriched within them, are associated with inflammation and immune response.
CONCLUSIONS: Integrated proteomic and metabolomic analyses revealed distinct inflammatory and immune response pathways in HFpEF, highlighting novel therapeutic avenues.

OBJECTIVE: To evaluate the predictive value of global longitudinal strain (GLS) measured by cardiac magnetic resonance (CMR) feature-tracking technique for left ventricular remodeling (LVR) after percutaneous coronary intervention (PCI) in patients with acute ST-segment elevation myocardial infarction (STEMI).
METHODS: A total of 403 patients undergoing PCI for acute STEMI were prospectively recruited from multiple centers in China.CMR examinations were performed one week (7±2 days) and 6 months after myocardial infarction to obtain GLS, global radial strain (GRS), global circumferential strain (GCS), ejection fraction (LVEF) and infarct size (IS).The primary endpoint was LVR, defined as an increase of left ventricle end-diastolic volume by ≥20% or an increase of left ventricle end-systolic volume by ≥15% from the baseline determined by CMR at 6 months.Logistic regression analysis was performed to evaluate the predictive value of CMR parameters for LVR.
RESULTS: LVR occurred in 101 of the patients at 6 months after myocardial infarction.Compared with those without LVR (n=302), the patients in LVR group exhibited significantly higher GLS and GCS (P < 0.001) and lower GRS and LVEF (P < 0.001).Logistic regression analysis indicated that both GLS (OR=1.387, 95%CI: 1.223-1.573;P < 0.001) and LVEF (OR=0.951, 95%CI: 0.914-0.990;P=0.015) were independent predictors of LVR.ROC curve analysis showed that at the optimal cutoff value of-10.6%, GLS had a sensitivity of 74.3% and a specificity of 71.9% for predicting LVR.The AUC of GLS was similar to that of LVEF for predicting LVR (P=0.146), but was significantly greater than those of other parameters such as GCS, GRS and IS (P < 0.05);the AUC of LVEF did not differ significantly from those of the other parameters (P>0.05).
CONCLUSIONS: In patients receiving PCI for STEMI, GLS measured by CMR is a significant predictor of LVR occurrence with better performance than GRS, GCS, IS and LVEF.

Low blood pressure (BP) is associated with poor outcomes in patients with heart failure (HF). We investigated the influence of initial BP on the prognosis of HF patients at admission, and prescribing patterns of HF medications, such as angiotensin-converting enzyme inhibitors (ACEi), angiotensin receptor blockers (ARB), and beta-blockers (BB). Data were sourced from a multicentre cohort of patients admitted for acute HF. Patients were grouped into heart failure reduced ejection fraction (HFrEF) and HF mildly reduced/preserved ejection fraction (HFmrEF/HFpEF) groups. Initial systolic and diastolic BPs were categorized into specific ranges. Among 2778 patients, those with HFrEF were prescribed ACEi, ARB, or BB at discharge, regardless of their initial BP. However, medication use in HFmrEF/HFpEF patients tended to decrease as BP decreased. Lower initial BP in HFrEF patients correlated with an increased incidence of all-cause death and composite clinical events, including HF readmission or all-cause death. However, no significant differences in clinical outcomes were observed in HFmrEF/HFpEF patients according to BP. Initial systolic (< 120 mmHg) and diastolic (< 80 mmHg) BPs were independently associated with a 1.81-fold (odds ratio [OR] 1.81, 95% confidence interval [CI] 1.349-2.417, p < 0.001) and 2.24-fold (OR 2.24, 95% CI 1.645-3.053, p < 0.001) increased risk of long-term mortality in HFrEF patients, respectively. In conclusion, low initial BP in HFrEF patients correlated with adverse clinical outcomes, and BP < 120/80 mmHg independently increased mortality. However, this relationship was not observed in HFmrEF/HFpEF patients.

BACKGROUND: There is no clear evidence on the comparative effectiveness of bone-marrow mononuclear cell (BMMNC) vs. mesenchymal stromal cell (MSC) stem cell therapy in patients with chronic heart failure (HF).
METHODS: Using a systematic approach, eligible randomized controlled trials (RCTs) of stem cell therapy (BMMNCs or MSCs) in patients with HF were retrieved to perform a meta-analysis on clinical outcomes (major adverse cardiovascular events (MACE), hospitalization for HF, and mortality) and echocardiographic indices (including left ventricular ejection fraction (LVEF)) were performed using the random-effects model. A risk ratio (RR) or mean difference (MD) with corresponding 95% confidence interval (CI) were pooled based on the type of the outcome and subgroup analysis was performed to evaluate the potential differences between the types of cells.
RESULTS: The analysis included a total of 36 RCTs (1549 HF patients receiving stem cells and 1252 patients in the control group). Transplantation of both types of cells in patients with HF resulted in a significant improvement in LVEF (BMMNCs: MD (95% CI) = 3.05 (1.11; 4.99) and MSCs: MD (95% CI) = 2.82 (1.19; 4.45), between-subgroup p = 0.86). Stem cell therapy did not lead to a significant change in the risk of MACE (MD (95% CI) = 0.83 (0.67; 1.06), BMMNCs: RR (95% CI) = 0.59 (0.31; 1.13) and MSCs: RR (95% CI) = 0.91 (0.70; 1.19), between-subgroup p = 0.12). There was a marginally decreased risk of all-cause death (MD (95% CI) = 0.82 (0.68; 0.99)) and rehospitalization (MD (95% CI) = 0.77 (0.61; 0.98)) with no difference among the cell types (p > 0.05).
CONCLUSIONS: Both types of stem cells are effective in improving LVEF in patients with heart failure without any noticeable difference between the cells. Transplantation of the stem cells could not decrease the risk of major adverse cardiovascular events compared with controls. Future trials should primarily focus on the impact of stem cell transplantation on clinical outcomes of HF patients to verify or refute the findings of this study.

BACKGROUND: Heart failure (HF) with preserved or mildly reduced ejection fraction includes a heterogenous group of patients. Reclassification into distinct phenogroups to enable targeted interventions is a priority. This study aimed to identify distinct phenogroups, and compare phenogroup characteristics and outcomes, from electronic health record data.
METHODS: 2,187 patients admitted to five UK hospitals with a diagnosis of HF and a left ventricular ejection fraction ≥ 40% were identified from the NIHR Health Informatics Collaborative database. Partition-based, model-based, and density-based machine learning clustering techniques were applied. Cox Proportional Hazards and Fine-Gray competing risks models were used to compare outcomes (all-cause mortality and hospitalisation for HF) across phenogroups.
RESULTS: Three phenogroups were identified: (1) Younger, predominantly female patients with high prevalence of cardiometabolic and coronary disease; (2) More frail patients, with higher rates of lung disease and atrial fibrillation; (3) Patients characterised by systemic inflammation and high rates of diabetes and renal dysfunction. Survival profiles were distinct, with an increasing risk of all-cause mortality from phenogroups 1 to 3 (p < 0.001). Phenogroup membership significantly improved survival prediction compared to conventional factors. Phenogroups were not predictive of hospitalisation for HF.
CONCLUSIONS: Applying unsupervised machine learning to routinely collected electronic health record data identified phenogroups with distinct clinical characteristics and unique survival profiles.

We sought to validate the ability of a novel handheld ultrasound device with an artificial intelligence program (AI-POCUS) that automatically assesses left ventricular ejection fraction (LVEF). AI-POCUS was used to prospectively scan 200 patients in two Japanese hospitals. Automatic LVEF by AI-POCUS was compared to the standard biplane disk method using high-end ultrasound machines. After excluding 18 patients due to infeasible images for AI-POCUS, 182 patients (63 ± 15 years old, 21% female) were analyzed. The intraclass correlation coefficient (ICC) between the LVEF by AI-POCUS and the standard methods was good (0.81, p < 0.001) without clinically meaningful systematic bias (mean bias -1.5%, p = 0.008, limits of agreement ± 15.0%). Reduced LVEF < 50% was detected with a sensitivity of 85% (95% confidence interval 76%-91%) and specificity of 81% (71%-89%). Although the correlations between LV volumes by standard-echo and those by AI-POCUS were good (ICC > 0.80), AI-POCUS tended to underestimate LV volumes for larger LV (overall bias 42.1 mL for end-diastolic volume). These trends were mitigated with a newer version of the software tuned using increased data involving larger LVs, showing similar correlations (ICC > 0.85). In this real-world multicenter study, AI-POCUS showed accurate LVEF assessment, but careful attention might be necessary for volume assessment. The newer version, trained with larger and more heterogeneous data, demonstrated improved performance, underscoring the importance of big data accumulation in the field.

BACKGROUND: Sodium-glucose cotransporter 2 inhibitors (SGLT-2i) are glucose-lowering agents used for the treatment of type 2 diabetes mellitus, which also improve heart failure and decrease the risk of cardiovascular complications. Epicardial adipose tissue (EAT) dysfunction was suggested to contribute to the development of heart failure. We aimed to elucidate a possible role of changes in EAT metabolic and inflammatory profile in the beneficial cardioprotective effects of SGLT-2i in subjects with severe heart failure.
METHODS: 26 subjects with severe heart failure, with reduced ejection fraction, treated with SGLT-2i versus 26 subjects without treatment, matched for age (54.0 ± 2.1 vs. 55.3 ± 2.1 years, n.s.), body mass index (27.8 ± 0.9 vs. 28.8 ± 1.0 kg/m2, n.s.) and left ventricular ejection fraction (20.7 ± 0.5 vs. 23.2 ± 1.7%, n.s.), who were scheduled for heart transplantation or mechanical support implantation, were included in the study. A complex metabolomic and gene expression analysis of EAT obtained during surgery was performed.
RESULTS: SGLT-2i ameliorated inflammation, as evidenced by the improved gene expression profile of pro-inflammatory genes in adipose tissue and decreased infiltration of immune cells into EAT. Enrichment of ether lipids with oleic acid noted on metabolomic analysis suggests a reduced disposition to ferroptosis, potentially further contributing to decreased oxidative stress in EAT of SGLT-2i treated subjects.
CONCLUSIONS: Our results show decreased inflammation in EAT of patients with severe heart failure treated by SGLT-2i, as compared to patients with heart failure without this therapy. Modulation of EAT inflammatory and metabolic status could represent a novel mechanism behind SGLT-2i-associated cardioprotective effects in patients with heart failure.

BACKGROUND: Pulmonary transit time (PTT) can be measured automatically from arterial input function (AIF) images of dual sequence first-pass perfusion imaging. PTT has been validated against invasive cardiac catheterisation correlating with both cardiac output and left ventricular filling pressure (both important prognostic markers in heart failure). We hypothesized that prolonged PTT is associated with clinical outcomes in patients with heart failure.
METHODS: We recruited outpatients with a recent diagnosis of non-ischaemic heart failure with left ventricular ejection fraction (LVEF) < 50% on referral echocardiogram. Patients were followed up by a review of medical records for major adverse cardiovascular events (MACE) defined as all-cause mortality, heart failure hospitalization, ventricular arrhythmia, stroke or myocardial infarction. PTT was measured automatically from low-resolution AIF dynamic series of both the LV and RV during rest perfusion imaging, and the PTT was measured as the time (in seconds) between the centroid of the left (LV) and right ventricle (RV) indicator dilution curves.
RESULTS: Patients (N = 294) were followed-up for median 2.0 years during which 37 patients (12.6%) had at least one MACE event. On univariate Cox regression analysis there was a significant association between PTT and MACE (Hazard ratio (HR) 1.16, 95% confidence interval (CI) 1.08-1.25, P = 0.0001). There was also significant association between PTT and heart failure hospitalisation (HR 1.15, 95% CI 1.02-1.29, P = 0.02) and moderate correlation between PTT and N-terminal pro B-type natriuretic peptide (NT-proBNP, r = 0.51, P < 0.001). PTT remained predictive of MACE after adjustment for clinical and imaging factors but was no longer significant once adjusted for NT-proBNP.
CONCLUSIONS: PTT measured automatically during CMR perfusion imaging in patients with recent onset non-ischaemic heart failure is predictive of MACE and in particular heart failure hospitalisation. PTT derived in this way may be a non-invasive marker of haemodynamic congestion in heart failure and future studies are required to establish if prolonged PTT identifies those who may warrant closer follow-up or medicine optimisation to reduce the risk of future adverse events.

The hemodynamic response during the transition from the supine to standing position in idiopathic atrial fibrillation (AF) patients is not completely understood. This study aimed to analyze the hemodynamic changes that occur during the head-up tilt test in idiopathic AF patients. We investigated the hemodynamic changes during the head-up tilt test with impedance cardiography in 40 AF patients (12 with AF rhythm-AFr and 28 with sinus rhythm-AFsr) and 38 non-AF controls. Patients with AFr had attenuated SVI decrease after standing when compared to AFsr and non-AF [ΔSVI in mL/m2: -1.3 (-3.4 to 1.7) vs. -6.4 (-17.3 to -0.1) vs. -11.8 (-18.7 to -8.0), respectively; p < 0.001]. PVRI decreased in AFr but increased in AFsr and non-AF [ΔPVRI in dyne.seg.m2/cm5: -477 (-1148 to 82.5) vs. 131 (-525 to 887) vs. 357 (-29 to 681), respectively; p < 0.01]. Similarly, compared with non-AF patients, AFr patients also had a greater HR and greater CI increase after standing. The haemodynamic response to orthostatic challenge suggests differential adaptations between patients with AF rhythm and those reverted to sinus rhythm or healthy controls. Characterizing the hemodynamic phenotype may be relevant for the individualized treatment of AF patients.