Heart Failure with Normal Natriuretic Peptide Levels and Preserved Ejection Fraction: A Prospective Clinical and Cardiac MRI Study.

Purpose To describe the clinical presentation, comprehensive cardiac MRI characteristics, and prognosis of individuals with predisposed heart failure with preserved ejection fraction (HFpEF). Materials and Methods This prospective cohort study (part of MISSION-HFpEF [Multimodality Imaging in the Screening, Diagnosis, and Risk Stratification of HFpEF]; NCT04603404) was conducted from January 1, 2019, to September 30, 2021, and included individuals with suspected HFpEF who underwent cardiac MRI. Participants who had primary cardiomyopathy and primary valvular heart disease were excluded. Participants were split into a predisposed HFpEF group, defined as HFpEF with normal natriuretic peptide levels based on an HFA-PEFF (Heart Failure Association Pretest Assessment, Echocardiography and Natriuretic Peptide, Functional Testing, and Final Etiology) score of 4 from the latest European Society of Cardiology guidelines, and an HFpEF group (HFA-PEFF score of ≥ 5). An asymptomatic control group without heart failure was also included. Clinical and cardiac MRI-based characteristics and outcomes were compared between groups. The primary end points were death, heart failure hospitalization, or stroke. Results A total of 213 participants with HFpEF, 151 participants with predisposed HFpEF, and 100 participants in the control group were analyzed. Compared with the control group, participants with predisposed HFpEF had worse left ventricular remodeling and function and higher systemic inflammation. Compared with participants with HFpEF, those with predisposed HFpEF, whether obese or not, were younger and had higher plasma volume, lower prevalence of atrial fibrillation, lower left atrial volume index, and less impaired left ventricular global longitudinal strain (-12.2% ± 2.8 vs -13.9% ± 3.1; P < .001) and early-diastolic global longitudinal strain rate (eGLSR, 0.52/sec ± 0.20 vs 0.57/sec ± 0.15; P = .03) but similar prognosis. Atrial fibrillation occurrence (hazard ratio [HR] = 3.90; P = .009), hemoglobin level (HR = 0.94; P = .001), and eGLSR (per 0.2-per-second increase, HR = 0.28; P = .002) were independently associated with occurrence of primary end points in participants with predisposed HFpEF. Conclusion Participants with predisposed HFpEF showed relatively unique clinical and cardiac MRI features, warranting greater clinical attention. eGLSR should be considered as a prognostic factor in participants with predisposed HFpEF. Keywords: Heart Failure with Preserved Ejection Fraction, Normal Natriuretic Peptide Levels, Cardiovascular Magnetic Resonance, Myocardial Strain, Prognosis Clinical trial registration no. NCT04603404 Supplemental material is available for this article. © RSNA, 2024.

Association of lipids and inflammatory markers with left ventricular wall thickness in patients with bipolar disorder.

BACKGROUND: Individuals with bipolar disorder (BD) face a high risk of heart failure and left ventricular (LV) dysfunction. Despite strong evidence that high LV relative wall thickness (RWT) is a risk marker for heart failure, few studies have evaluated LV RWT and aggravating factors in individuals with BD. METHODS: We recruited 104 participants (52 patients with BD and 52 age- and sex-matched mentally healthy controls) to undergo echocardiographic imaging and biochemistry, high-sensitivity C-reactive protein (hs-CRP), and blood cell count measurements. LV RWT was estimated using the following equation: (2 × LV posterior wall end-diastolic thickness)/LV end-diastolic diameter. Clinical data were obtained through interviews and chart reviews. RESULTS: The BD group exhibited a significantly greater LV RWT (Cohen's d = 0.53, p = 0.003) and a less favorable mitral valve E/A ratio (Cohen's d = 0.54, p = 0.023) and LV global longitudinal strain (Cohen's d = 0.57, p = 0.047) than did the control group. Multiple linear regression revealed that in the BD group, serum triglyceride levels (ß = 0.466, p = 0.001), platelet-to-lymphocyte ratios (ß = 0.324, p = 0.022), and hs-CRP levels (ß = 0.289, p = 0.043) were all significantly and positively associated with LV RWT. LIMITATIONS: This study applied a cross-sectional design, meaning that the direction of causation could not be inferred. CONCLUSIONS: Patients with BD are at a risk of heart failure, as indicated by their relatively high LV RWT. Lipid levels and systemic inflammation may explain this unfavorable association.

Evaluation of thyroid congestion in patients with heart failure using shear wave elastography: An observational study.

Shear wave elastography (SWE) is a noninvasive method for measuring organ stiffness. Liver stiffness measured using SWE reflects hepatic congestion in patients with heart failure (HF). However, little is known about the use of SWE to assess other organ congestions. This study aimed to evaluate the utility of SWE for assessing not only the liver but also thyroid congestion in patients with HF. This prospective study included 21 patients with HF who have normal thyroid lobes (age: 77.0 ±â€…11.0, men: 14). Thyroid and liver stiffness were measured by SWE using the ARIETTA 850 ultrasonography system (Fujifilm Ltd., Tokyo, Japan). SWE of the thyroid was performed on B-mode ultrasonography; a target region was identified within a region of interest. SWE was performed in each lobe of the thyroid gland. Five measurements were taken at the same location and the averages were recorded for comparison. We investigated the relationship between SWE for evaluating thyroid stiffness and the clinical characteristics of patients with HF. SWE of the thyroid was significantly correlated with SWE of the liver (R = 0.768, P < .001), thyroid stimulation hormone (R = 0.570, P = .011), free thyroxine (R = 0.493, P = .032), estimated right atrial pressure (RAP; R = 0.468, P = .033), and composite congestion score (R = 0.441, P = .045). SWE may be useful for evaluating thyroid stiffness and assessing the degree of thyroid congestion. Thyroid congestion may reflect the elevation of RAP and cause thyroid dysfunction through organ congestion.

Diaphragm thickness and mobility elicited by two different modalities of inspiratory muscle loading in heart failure participants: A randomized crossover study.

OBJECTIVES: To analyze diaphragmatic thickness, at end-inspiration and end-expiration, diaphragmatic thickening index and mobility via US under two different modalities of inspiratory muscle loading, in two different modalities of inspiratory muscle loading and different load intensities at full-vital capacity maneuvers and the relationship between diaphragmatic thickness with pulmonary function tests in participants with HF. METHODS: This randomized crossover trial, enrolled with 17 HF subjects, evaluated diaphragm thickness (Tdi, mm), fractional thickness (TFdi, %), and mobility (mm) US during low and high intensities (30% and 60% of maximal inspiratory pressure-MIP) with two modalities of inspiratory muscle loading mechanical threshold loading (MTL) and tapered flow-resistive loading (TFRL). RESULTS: Both MTL and TFRL produced a increase in Tdi, but only with high intensity loading compared to baseline-2.21 (0.26) vs. 2.68 (0.33) and 2.73 (0.44) mm; p = .01. TFdi was greater than baseline under all conditions, except during low intensity of TFRL. Diaphragm mobility was greater than baseline under all conditions, and high intensity of TFRL elicited greater mobility compared to all other conditions. Additionally, baseline Tdi was moderately correlated with pulmonary function tests. CONCLUSIONS: MTL and TFRL modalities elicit similar increases in diaphragm thickness at loads, but only during high intensity loading it was greater than baseline. Diaphragm mobility was significantly greater than baseline under both loads and devices, and at high intensity compared to low intensity, although TFRL produced greater mobility compared to modalities of inspiratory muscle loading. There is an association between diaphragm thickness and pulmonary function tests.

A novel multi-task machine learning classifier for rare disease patterning using cardiac strain imaging data.

To provide accurate predictions, current machine learning-based solutions require large, manually labeled training datasets. We implement persistent homology (PH), a topological tool for studying the pattern of data, to analyze echocardiography-based strain data and differentiate between rare diseases like constrictive pericarditis (CP) and restrictive cardiomyopathy (RCM). Patient population (retrospectively registered) included those presenting with heart failure due to CP (n = 51), RCM (n = 47), and patients without heart failure symptoms (n = 53). Longitudinal, radial, and circumferential strains/strain rates for left ventricular segments were processed into topological feature vectors using Machine learning PH workflow. In differentiating CP and RCM, the PH workflow model had a ROC AUC of 0.94 (Sensitivity = 92%, Specificity = 81%), compared with the GLS model AUC of 0.69 (Sensitivity = 65%, Specificity = 66%). In differentiating between all three conditions, the PH workflow model had an AUC of 0.83 (Sensitivity = 68%, Specificity = 84%), compared with the GLS model AUC of 0.68 (Sensitivity = 52% and Specificity = 76%). By employing persistent homology to differentiate the "pattern" of cardiac deformations, our machine-learning approach provides reasonable accuracy when evaluating small datasets and aids in understanding and visualizing patterns of cardiac imaging data in clinically challenging disease states.

Study on the construction of nomogram prediction model for prognostic assessment of heart failure patients based on serological markers and echocardiography.

OBJECTIVE: We aimed to construct a nomogram prediction model for prognostic assessment of patients with heart failure (HF) based on serological markers and echocardiography. PATIENTS AND METHODS: A total of 200 HF patients admitted to the Second Affiliated Hospital of Nanchang University from January 2018 to January 2020 were selected as the research objects. According to the New York Heart Association (NYHA) cardiac function classification, they were divided into 3 groups, including 65 cases of grade II, 97 cases of grade III, and 38 cases of grade IV. Three groups of echocardiographic parameters were compared [including left ventricular ejection fraction (LVEF), left ventricular end-diastolic diameter (LVEDD), left ventricular end-systolic diameter (LVESD), left ventricular end-systolic volume (LVESV)], differences in serum markers brain natriuretic peptide (BNP), soluble growth-stimulating expression gene 2 (sST2) and the Modified Early Warning Score (MEWS). The patients were divided into two groups according to their clinical outcomes during the follow-up period, including 52 cases in the death group and 148 cases in the survival group. The clinical data of the two groups were compared, and multi-factor logistic regression analysis was performed to screen out the independent risk factors affecting the patient's death. A nomogram model of the patient's mortality risk was constructed based on the independent risk factors. Receiver operating characteristic (ROC) curves and calibration curves were used to evaluate the discrimination and accuracy of the nomogram model. RESULTS: As the cardiac function class of elderly chronic heart failure (CHF) patients increases, LVEDD, LVESD, sST2, and MEWS increase and LVEF decreases (p<0.05). Multifactor analysis results showed that LVEF, LVEDD, sST2, and MEWS were independent factors affecting the clinical outcome of patients. The AUCs predicted using LVEF, LVEDD, sST2, and MEWS alone were 0.738, 0.775, 0.717, 0.831, and 0.768, respectively. There is a certain degree of discrimination, and the model has extremely high accuracy. CONCLUSIONS: MEWS, LVEDD, and sST2 increase as the NYHA cardiac function grade of HF patients increases and LVEF decreases, which can reflect the severity of the disease to a certain extent. Additionally, the nomogram model established based on this has a high predictive value for the long-term prognosis of patients and can formulate effective intervention measures for quantitative values.

Role of NT-proBNP and lung ultrasound in diagnosing and classifying heart failure in a hospitalized oldest-old population: a cross-sectional study.

AIM: Diagnosing and classifying heart failure (HF) in the oldest-old patients has technical and interpretation issues, especially in the acute setting. We assessed the usefulness of both N-terminal pro-brain natriuretic peptide (NT-proBNP) and lung ultrasound (LUS) for confirming HF diagnosis and predicting, among hospitalized HF patients, those with reduced ejection fraction (HFrEF). METHODS: We performed a cross-sectional study on 148 consecutive patients aged ≥ 80 years admitted to our Internal Medicine and Geriatrics ward with at least one symptom/sign compatible with HF and NT-proBNP ≥ 125 pg/mL. We measured serum NT-proBNP levels and performed LUS and transthoracic echocardiography (TTE) on admission before diuretic therapy. We divided our cohort into three subgroups according to the left ventricular ejection fraction (LVEF): reduced (LVEF ≤ 40%), mildly-reduced (LVEF = 41-49%) and preserved (LVEF ≥ 50%). RESULTS: The mean age was 88±5 years. Male prevalence was 42%. Patients with HFrEF were 19%. Clinical features and laboratory parameters did not differ between the three subgroups, except for higher NT-proBNP in HFrEF patients, which also had a higher number of total B-lines and intercostal spaces of pleural effusion at LUS. Overall, NT-proBNP showed an inverse correlation with LVEF (r = -0.22, p = 0.007) and a direct correlation with age, total pulmonary B-lines, and intercostal spaces of pleural effusion. According to the ROCs, NT-proBNP levels, pulmonary B-lines and pleural effusion extension were poorly predictive for HFrEF. The best-performing cut-offs were 9531 pg/mL for NT-proBNP (SP 0.70, SE 0.50), 13 for total B-lines (SP 0.69, SE 0.85) and one intercostal space for pleural effusion (SP 0.55, SE 0.89). Patients with admission NT-proBNP ≥ 9531 pg/mL had a 2-fold higher risk for HFrEF (OR 2.5, 95% CI 1.3-4.9), while we did not find any association for total B-lines ≥ 13 or pleural effusion ≥ 1 intercostal space with HFrEF. A significant association with HFrEF emerged for the combination of NT-proBNP ≥ 9531 pg/mL, total B-lines ≥ 13 and intercostal spaces of pleural effusion ≥ 1 (adjusted OR 4.3, 95% CI 1.5-12.9). CONCLUSIONS: Although NT-proBNP and LUS help diagnose HF, their accuracy in discriminating HFrEF from non-HFrEF was poor in our real-life clinical study on oldest-old hospitalized patients, making the use of TTE still necessary to distinguish HF phenotypes in this peculiar setting. These data require confirmation in more extensive and longer prospective studies.

Diagnostic value of LGE and T1 mapping in multiple myeloma patients'heart.

BACKGROUND: Unidentified heart failure occurs in patients with multiple myeloma when their heart was involved. CMR with late gadolinium enhancement (LGE) and T1 mapping can identify myocardial amyloid infiltrations. PURPOSE: To explore the role of CMR with late gadolinium enhancement (LGE) and T1 mapping for detection of multiple myeloma patients'heart. MATERIAL AND METHODS: A total of 16 MM patients with above underwent CMR (3.0-T) with T1 mapping (pre-contrast and post-contrast) and LGE imaging. In addition, 26 patients with non-obstructive hypertrophic cardiomyopathy and 26 healthy volunteers were compared to age- and sex-matched healthy controls without a history of cardiac disease, diabetes mellitus, or normal in CMR. All statistical analyses were performed using the statistical software GraphPad Prism. The measurement data were represented by median (X) and single sample T test was adopted. Enumeration data were represented by examples and Chi-tested was adopted. All tests were two-sided, and P values < 0.05 were considered statistically significant. RESULTS: In MM group, LVEF was lower than healthy controls and higher than that of non-obstructive hypertrophic cardiomyopathy group, but without statistically significant difference (%: 49.1 ± 17.5 vs. 55.6 ± 10.3, 40.4 ± 15.6, all P > 0.05). Pre-contrast T1 values of MM group were obviously higher than those of healthy controls and non-obstructive hypertrophic cardiomyopathy group (ms:1462.0 ± 71.3vs. 1269.3 ± 42.3, 1324.0 ± 45.1, all P < 0.05). 16 cases (100%) in MM group all had LGE. CONCLUSION: LGE joint T1 mapping wider clinical use techniques and follow-up the patients'disease severity.

Glycemic control and clinical outcomes in diabetic patients with heart failure and reduced ejection fraction: insight from ventricular remodeling using cardiac MRI.

BACKGROUND: Glycemic control, as measured by glycosylated hemoglobin (HbA1c), is an important biomarker to evaluate diabetes severity and is believed to be associated with heart failure development. Type 2 diabetes mellitus (T2DM) and heart failure with reduced ejection fraction (HFrEF) commonly coexist, and the combination of these two diseases indicates a considerably poorer outcome than either disease alone. Therefore, glycemic control should be carefully managed. The present study aimed to explore the association between glycemic control and clinical outcomes, and to determine the optimal glycemic target in this specific population. METHODS: A total of 262 patients who underwent cardiac MRI were included and were split by HbA1c levels [HbA1c < 6.5% (intensive control), HbA1c 6.5-7.5% (modest control), and HbA1c > 7.5% (poor control)]. The biventricular volume and function, as well as left ventricular (LV) systolic strains in patients in different HbA1c categories, were measured and compared. The primary and secondary outcomes were recorded. The association of different HbA1c levels with adverse outcomes was assessed. RESULTS: Despite similar biventricular ejection fractions, both patients with intensive and poor glycemic control exhibited prominent deterioration of LV systolic strain in the longitudinal component (P = 0.004). After a median follow-up of 35.0 months, 55 patients (21.0%) experienced at least one confirmed endpoint event. Cox multivariable analysis indicated that both patients in the lowest and highest HbA1c categories exhibited a more than 2-fold increase in the risk for primary outcomes [HbA1c < 6.5%: hazard ratio (HR) = 2.42, 95% confidence interval (CI) = 1.07-5.45; P = 0.033; HbA1c > 7.5%: HR = 2.24, 95% CI = 1.01-4.99; P = 0.038] and secondary outcomes (HbA1c < 6.5%: HR = 2.84, 95% CI = 1.16-6.96; P = 0.022; HbA1c > 7.5%: HR = 2.65, 95% CI = 1.08-6.50; P = 0.038) compared with those in the middle HbA1c category. CONCLUSIONS: We showed a U-shaped association of glycemic control with clinical outcomes in patients with T2DM and HFrEF, with the lowest risk of adverse outcomes among patients with modest glycemic control. HbA1c between 6.5% and 7.5% may be served as the optimal hypoglycemic target in this specific population.

Diagnostic performance of a clinical ultrasound-based algorithm for acute heart failure in patients presenting to the emergency department with dyspnea. / Rendimiento diagnóstico de un algoritmo basado en ecografía clínica para el diagnóstico de insuficiencia cardiaca aguda en pacientes que consultan en urgencias por disnea.

OBJECTIVES: To study the diagnostic performance of an ultrasound-based algorithm that includes the deceleration time (DT) of early mitral filling to establish a diagnosis of acute heart failure (AHF) in patients who come to an emergency department because of dyspnea. MATERIAL AND METHODS: Prospective analysis in a convenience sample of patients who came to a hospital emergency department with acute dyspnea. The algorithm included ultrasound findings and 4 echocardiographic findings as follows: mitral annular plane systolic excursion, Doppler mitral flow velocity, tissue Doppler imaging measure of the lateral annulus, and the DT of early mitral filling. The definitive diagnosis was made by 2 physicians blinded to each other's diagnosis and the ultrasound findings. RESULTS: A total of 166 adult patients with a mean (SD) age of 76 (13) years were included; 79 (48%) were women. AHF was the definitive diagnosis in 62 patients (37%). Diagnostic agreement was good between the 2 physicians (κ = 0.71). The algorithm classified all the patients, and there were no undetermined diagnoses. Diagnostic performance indicators for the ultrasound-based algorithm integrating early DT findings were as follows: area under the receiver operating characteristic curve, 0.91 (95% CI, 0.86-0.96); sensitivity, 87% (95% CI, 76%-94%); specificity, 95% (95% CI, 89%-98%); positive likelihood ratio, 18.1 (95% CI, 7.7-42.8); and negative likelihood ratio, 0.14 (95% CI, 0.07-0.26). CONCLUSION: The ultrasound-based algorithm integrating the DT of early mitral filling performs well for diagnosing AHF in emergency patients with dyspnea. The inclusion of early DT allows all patients to be diagnosed.

OBJETIVO: Analizar el rendimiento diagnóstico de un algoritmo ecográfico que incluye el tiempo de desaceleración precoz del flujo mitral (TD) para establecer el diagnóstico de insuficiencia cardiaca aguda (ICA) en pacientes que consultan en un servicio de urgencias hospitalario (SUH) por disnea. METODO: Análisis prospectivo de una muestra de conveniencia de pacientes que consultan por disnea aguda en un SUH. El algoritmo ecográfico incluyó la ecografía pulmonar y cuatro parámetros ecocardiográficos, se midió MAPSE (desplazamiento sistólico del plano del anillo mitral), medidas doppler de flujo mitral, medidas doppler tisular en el anillo mitral lateral y TD. El diagnóstico final fue asignado por 2 médicos ciegos entre sí y a los hallazgos ecográficos. RESULTADOS: Se incluyeron 166 pacientes adultos, la edad media fue de 76 años (DE 13) y 79 eran mujeres (48%). Hubo 62 pacientes (37%) con un diagnóstico final de ICA. La concordancia entre asignadores fue buena para el diagnóstico de ICA (κ = 0,71). El algoritmo clasificó a todos los pacientes, no hubo ningún diagnóstico indeterminado. El rendimiento diagnóstico del algoritmo mostró un área bajo la curva de 0,91 (IC 95%: 0,86-0,96), sensibilidad del 87% (IC 95%: 76%-94%), especificidad del 95% (IC 95%: 89%-98%), razón de verosimilitud positiva del 18,1 (IC 95%: 7,7-42,8), razón de verosimilitud negativa del 0,14 (IC 95%: 0,07-0,26). CONCLUSIONES: Un algoritmo ecográfico que incluye el TD tiene un buen rendimiento para el diagnóstico de ICA en pacientes que acuden a SUH por disnea. Además, el uso de TD permite clasificar a todos los pacientes.

Combined transcatheter aortic valve and tricuspid valve-in-valve implantation in a patient with a mitral mechanical prosthesis.

Despite progressively uncommon in Western countries, rheumatic heart disease still portrays a significant global burden. In elderly or high-surgical risk patients, plurivalvular disease may require a complex percutaneous approach. Transcatheter aortic valve implantation (TAVI) in patients with previous monoleaflet mitral prosthesis is challenging due to interference between the aortic valve and the rigid mitral mechanical prosthesis "ring." Prior cases report the use of CoreValve or Edwards Sapien aortic valves in patients with adequate mitro-aortic distance. Performing a second major procedure, such as tricuspid valve-in-valve (TVIV), sequentially during a single percutaneous intervention, increases treatment complexity. An 83-year-old woman with rheumatic heart disease, with previous implantation of a Bjork-Shiley monoleaflet mitral prosthesis, and Carpentier-Edwards 29 tricuspid bioprosthesis presented with decompensated heart failure due to severe aortic stenosis and tricuspid bioprosthesis stenosis. After HeartTeam discussion, the patient was deemed as inoperable due to a prohibitive surgical risk. As an alternative, a TAVI (Navitor FlexNav) and a transcatheter TVIV replacement (Edwards Sapiens 3 Ultra) were discussed and proposed, with both techniques being performed sequentially in a single procedure. TAVI in a patient with a previous monoleaflet mitral mechanical prosthesis and TVIV may be a feasible approach in inoperable patients with plurivalvular disease.

Dynamic trend of lung fluid movement during exercise in heart failure: From lung imaging to alveolar-capillary membrane function.

BACKGROUND: In chronic heart failure (HF), exercise-induced increase in pulmonary capillary pressure may cause an increase of pulmonary congestion, or the development of pulmonary oedema. We sought to assess in HF patients the exercise-induced intra-thoracic fluid movements, by measuring plasma brain natriuretic peptide (BNP), lung comets and lung diffusion for carbon monoxide (DLCO) and nitric oxide (DLNO), as markers of hemodynamic load changes, interstitial space and alveolar-capillary membrane fluids, respectively. METHODS AND RESULTS: Twenty-four reduced ejection fraction HF patients underwent BNP, lung comets and DLCO/DLNO measurements before, at peak and 1 h after the end of a maximal cardiopulmonary exercise test. BNP significantly increased at peak from 549 (328-841) to 691 (382-1207, p < 0.0001) pg/mL and almost completely returned to baseline value 1 h after exercise. Comets number increased at peak from 9.4 ± 8.2 to 24.3 ± 16.7, returning to baseline (9.7 ± 7.4) after 1 h (p < 0.0001). DLCO did not change significantly at peak (from 18.01 ± 4.72 to 18.22 ± 4.73 mL/min/mmHg), but was significantly reduced at 1 h (16.97 ± 4.26 mL/min/mmHg) compared to both baseline (p = 0.0211) and peak (p = 0.0174). DLNO showed a not significant trend toward lower values 1 h post-exercise. CONCLUSIONS: Moderate/severe HF patients have a 2-step intra-thoracic fluid movement with exercise: the first during active exercise, from the vascular space toward the interstitial space, as confirmed by comets increase, without any effect on diffusion, and the second, during recovery, toward the alveolar-capillary membrane, clearing the interstitial space but worsening gas diffusion.

Predictors of heart failure readmission and all-cause mortality in patients with acute heart failure.

BACKGROUND: Predischarge risk stratification of patients with acute heart failure (AHF) could facilitate tailored treatment and follow-up, however, simple scores to predict short-term risk for HF readmission or death are lacking. METHODS: We sought to develop a congestion-focused risk score using data from a prospective, two-center observational study in adults hospitalized for AHF. Laboratory data were collected on admission. Patients underwent physical examination, 4-zone, and in a subset 8-zone, lung ultrasound (LUS), and echocardiography at baseline. A second LUS was performed before discharge in a subset of patients. The primary endpoint was the composite of HF hospitalization or all-cause death. RESULTS: Among 350 patients (median age 75 years, 43% women), 88 participants (25%) were hospitalized or died within 90 days after discharge. A stepwise Cox regression model selected four significant independent predictors of the composite outcome, and each was assigned points proportional to its regression coefficient: NT-proBNP ≥2000 pg/mL (admission) (3 points), systolic blood pressure < 120 mmHg (baseline) (2 points), left atrial volume index ≥60 mL/m2 (baseline) (1 point) and ≥ 9 B-lines on predischarge 4-zone LUS (3 points). This risk score provided adequate risk discrimination for the composite outcome (HR 1.48 per 1 point increase, 95% confidence interval: 1.32-1.67, p < 0.001, C-statistic: 0.70). In a subset of patients with 8-zone LUS data (n = 176), results were similar (C-statistic: 0.72). CONCLUSIONS: A four-variable risk score integrating clinical, laboratory and ultrasound data may provide a simple approach for risk discrimination for 90-day adverse outcomes in patients with AHF if validated in future investigations.

Right ventricular dysfunction in chronic heart failure: clinical laboratory and echocardiographic characteristics. (the RIVED-CHF registry).

BACKGROUND: Right ventricular dysfunction (RVD) and pulmonary hypertension have been recognized as two important prognostic features in patients with left side heart failure. Current literature does not distinguish between right heart failure (RHF) and RVD, and the two terms are used indiscriminately to describe pulmonary hypertension and RVD as well as clinical sign of RHF. Therefore, the right ventricle (RV) adaptation across the whole spectrum of left ventricular ejection fraction (LVEF) values has been poorly investigated. METHODS: This is a multicenter observational prospective study endorsed by the Italian Society of Cardiology aiming to analyze the concordance between the signs and symptoms of RHF and echocardiographic features of RVD. The protocol will assess patients affected by chronic heart failure in stable condition regardless of the LVEF threshold by clinical, laboratory, and detailed echocardiographic study. During the follow-up period, patients will be observed by direct check-up visit and/or virtual visits every 6 months for a mean period of 3 years. All clinical laboratory and echocardiographic data will be recorded in a web platform system accessible for all centers included in the study. RESULTS: The main study goals are: to investigate the concordance and discordance between clinical signs of RHF and RVD measured by ultrasonographic examination; to evaluate prognostic impact (in terms of cardiovascular mortality and heart failure hospitalization) of RVD and RHF during a mean follow-up period of 3 years; to investigate the prevalence of different right ventricular maladaptation (isolated right ventricular dilatation, isolated pulmonary hypertension, combined pattern) and the related prognostic impact. CONCLUSIONS: With this protocol, we would investigate the three main RVD patterns according to heart failure types and stages; we would clarify different RVD and pulmonary hypertension severity according to the heart failure types. Additionally, by a serial multiparametric analysis of RV, we would provide a better definition of RVD stage and how much is it related with clinical signs of RHF (ClinicalTrials.gov Identifier: NCT06002321).

Impact of Changes in Rectus Femoris Cross-Sectional Area Measured by Ultrasound on the Prognosis of Patients With Acute Heart Failure.

BACKGROUND: Low muscle mass in patients with acute heart failure (AHF) is associated with poor prognosis; however, this is based on a single baseline measurement, with little information on changes in muscle mass during hospitalization and their clinical implications. This study investigated the relationship between changes in rectus femoris cross-sectional area (RFCSA) on ultrasound and the prognosis of patients with AHF.Methods and Results: This is a retrospective evaluation of 284 AHF patients (mean [±SD] age 79.1±11.9 years; 116 female). RFCSA assessments at admission (pre-RFCSA), ∆RFCSA (i.e., the percentage change in RFCSA from admission to 2 weeks), and composite prognosis (all-cause death and heart failure-related readmission) within 1 year were determined. Patients were divided into 4 groups according to their median pre-RFCSA and ∆RFCSA after sex stratification: Group A, higher pre-RFCSA/better ∆RFCSA; Group B, higher pre-RFCSA/worse ∆RFCSA; Group C, lower pre-RFCSA/better ∆RFCSA; Group D, lower pre-RFCSA/worse ∆RFCSA. In the Cox regression analysis, with Group A as the reference, the cumulative event rate of Group C (hazard ratio [HR] 3.39; 95% confidence interval [CI] 0.71-16.09; P=0.124) did not differ significantly; however, the cumulative event rates of Group B (HR 7.93; 95% CI 1.99-31.60; P=0.003) and Group D (HR 9.24; 95% CI 2.57-33.26; P<0.001) were significantly higher. CONCLUSIONS: ∆RFCSA during hospitalization is useful for risk assessment of prognosis in patients with AHF.

Circadian assessment of heart failure using explainable deep learning and novel multi-parameter polar images.

BACKGROUND AND OBJECTIVE: Heart failure (HF) is a multi-faceted and life-threatening syndrome that affects more than 64.3 million people worldwide. Current gold-standard screening technique, echocardiography, neglects cardiovascular information regulated by the circadian rhythm and does not incorporate knowledge from patient profiles. In this study, we propose a novel multi-parameter approach to assess heart failure using heart rate variability (HRV) and patient clinical information. METHODS: In this approach, features from 24-hour HRV and clinical information were combined as a single polar image and fed to a 2D deep learning model to infer the HF condition. The edges of the polar image correspond to the timely variation of different features, each of which carries information on the function of the heart, and internal illustrates color-coded patient clinical information. RESULTS: Under a leave-one-subject-out cross-validation scheme and using 7,575 polar images from a multi-center cohort (American and Greek) of 303 coronary artery disease patients (median age: 58 years [50-65], median body mass index (BMI): 27.28 kg/m2 [24.91-29.41]), the model yielded mean values for the area under the receiver operating characteristics curve (AUC), sensitivity, specificity, normalized Matthews correlation coefficient (NMCC), and accuracy of 0.883, 90.68%, 95.19%, 0.93, and 92.62%, respectively. Moreover, interpretation of the model showed proper attention to key hourly intervals and clinical information for each HF stage. CONCLUSIONS: The proposed approach could be a powerful early HF screening tool and a supplemental circadian enhancement to echocardiography which sets the basis for next-generation personalized healthcare.

Artificial Intelligence Predicts Hospitalization for Acute Heart Failure Exacerbation in Patients Undergoing Myocardial Perfusion Imaging.

Heart failure (HF) is a leading cause of morbidity and mortality in the United States and worldwide, with a high associated economic burden. This study aimed to assess whether artificial intelligence models incorporating clinical, stress test, and imaging parameters could predict hospitalization for acute HF exacerbation in patients undergoing SPECT/CT myocardial perfusion imaging. Methods: The HF risk prediction model was developed using data from 4,766 patients who underwent SPECT/CT at a single center (internal cohort). The algorithm used clinical risk factors, stress variables, SPECT imaging parameters, and fully automated deep learning-generated calcium scores from attenuation CT scans. The model was trained and validated using repeated hold-out (10-fold cross-validation). External validation was conducted on a separate cohort of 2,912 patients. During a median follow-up of 1.9 y, 297 patients (6%) in the internal cohort were admitted for HF exacerbation. Results: The final model demonstrated a higher area under the receiver-operating-characteristic curve (0.87 ± 0.03) for predicting HF admissions than did stress left ventricular ejection fraction (0.73 ± 0.05, P < 0.0001) or a model developed using only clinical parameters (0.81 ± 0.04, P < 0.0001). These findings were confirmed in the external validation cohort (area under the receiver-operating-characteristic curve: 0.80 ± 0.04 for final model, 0.70 ± 0.06 for stress left ventricular ejection fraction, 0.72 ± 0.05 for clinical model; P < 0.001 for all). Conclusion: Integrating SPECT myocardial perfusion imaging into an artificial intelligence-based risk assessment algorithm improves the prediction of HF hospitalization. The proposed method could enable early interventions to prevent HF hospitalizations, leading to improved patient care and better outcomes.