Renin–angiotensin–aldosterone system blockers effect in chronic kidney disease progression in hypertensive elderly patients without proteinuria: PROERCAN trial / Efecto de los bloqueantes del sistema renina-angiotensina-aldosterona en la progresión de enfermedad renal crónica en pacientes hipertensos añosos sin proteinuria: ensayo clínico Progresión de Enfermedad Renal Crónica en Ancianos

Introduction: Evidence about nefroprotective effect with RAAS blockers in elderly patients with chronic kidney disease (CKD) without proteinuria is lacking. The primary outcome of our study is to evaluate the impact of RAAS blockers in CKD progression in elderly patients without proteinuria. Materials and methods: Multicenter open-label, randomized controlled clinical trial including patients over 65 year-old with hypertension and CKD stages 3–4 without proteinuria. Patients were randomized in a 1:1 ratio to either receive RAAS blockers or other antihypertensive drugs and were followed up for three years. Primary outcome is estimated glomerular filtration rate (eGFR) decline at 3 years. Secondary outcome measures include BP control, renal and cardiovascular events and mortality. Results: 88 patients were included with a mean age of 77.9±6.1 years and a follow up period of 3 years: 40 were randomized to RAAS group and 48 to standard treatment. Ethiology of CKD was: 53 vascular, 16 interstitial and 19 of unknown ethiology. In the RAAS group eGFR slope during follow up was −4.3±1.1ml/min, whereas in the standard treatment group an increase on eGFR was observed after 3 years (+4.6±0.4ml/min), p=0.024. We found no differences in blood pressure control, number of antihypertensive drugs, albuminuria, potassium serum levels, incidence of cardiovascular events nor mortality during the follow up period. Conclusions: In elderly patients without diabetes nor cardiopathy and with non proteinuric CKD the use of RAAS blockers does not show a reduction in CKD progression. The PROERCAN (PROgresión de Enfermedad Renal Crónica en ANcianos) trial (trial registration: NCT03195023). (AU)

Introducción: Actualmente no existe suficiente evidencia sobre el efecto nefroprotector de los bloqueantes del sistema renina-angiotensina-aldosterona (BSRAA) en pacientes añosos con enfermedad renal crónica (ERC) sin proteinuria y sin cardiopatía. El objetivo es evaluar el efecto de los BSRAA en la progresión de la ERC en este grupo poblacional. Métodos: Se trata de un estudio prospectivo, aleatorizado, que compara la eficacia de los BSRAA vs. otros tratamientos antihipertensivos en la progresión renal en personas mayores de 65 años con ERC estadios 3 y 4 e índice albúmina/creatinina<30mg/g. Aleatorización 1:1 BSRAA o tratamiento antihipertensivo estándar. Se recogieron cifras tensionales y parámetros analíticos de un año previo a la aleatorización y durante el seguimiento. Resultados: Se incluyeron 88 pacientes seguidos durante tres años con edad media de 77,9±6,1 años. De estos, se aleatorizaron 40 al grupo BSRAA y 48 al estándar. La etiología de ERC fue: 53 vascular, 16 intersticial y 19 no filiada. En el primer grupo se observó una progresión de la ERC con una caída del filtrado glomerular estimado (FGe) de -4,3±1,1mL/min, mientras que en el grupo estándar un aumento del FGe durante el seguimiento de 4,6±0,4mL/min, p=0,024. No se apreciaron diferencias entre ambos en el control tensional, el número de antihipertensivos, la albuminuria, los niveles de potasio, la incidencia de eventos cardiovasculares ni la mortalidad durante el seguimiento. Conclusiones: En pacientes añosos no diabéticos con ERC no proteinúrica y sin cardiopatía el uso de BSRAA no añade beneficio en la progresión de la ERC. Ensayo clínico Progresión de Enfermedad Renal Crónica en Ancianos (PROERCAN) (NCT03195023). (AU)

4-phenylbutyric acid improves sepsis-induced cardiac dysfunction by modulating amino acid metabolism and lipid metabolism via Comt/Ptgs2/Ppara.

INTRODUCTION: Cardiac dysfunction after sepsis the most common and severe sepsis-related organ failure. The severity of cardiac damage in sepsis patients was positively associated to mortality. It is important to look for drugs targeting sepsis-induced cardiac damage. Our previous studies found that 4-phenylbutyric acid (PBA) was beneficial to septic shock by improving cardiovascular function and survival, while the specific mechanism is unclear. OBJECTIVES: We aimed to explore the specific mechanism and PBA for protecting cardiac function in sepsis. METHODS: The cecal ligation and puncture-induced septic shock models were used to observe the therapeutic effects of PBA on myocardial contractility and the serum levels of cardiac troponin-T. The mechanisms of PBA against sepsis were explored by metabolomics and network pharmacology. RESULTS: The results showed that PBA alleviated the sepsis-induced cardiac damage. The metabolomics results showed that there were 28 metabolites involving in the therapeutic effects of PBA against sepsis. According to network pharmacology, 11 hub genes were found that were involved in lipid metabolism and amino acid transport following PBA treatment. The further integrated analysis focused on 7 key targets, including Comt, Slc6a4, Maoa, Ppara, Pparg, Ptgs2 and Trpv1, as well as their core metabolites and pathways. In an in vitro assay, PBA effectively inhibited sepsis-induced reductions in Comt, Ptgs2 and Ppara after sepsis. CONCLUSIONS: PBA protects sepsis-induced cardiac injury by targeting Comt/Ptgs2/Ppara, which regulates amino acid metabolism and lipid metabolism. The study reveals the complicated mechanisms of PBA against sepsis.

Incidence of chemotherapy-related cardiac dysfunction in cancer patients.

BACKGROUND: Cancer patients are increasingly affected by chemotherapy-related cardiac dysfunction. The reported incidence of this condition vary significantly across different studies. HYPOTHESIS: A better comprehensive understanding of chemotherapy-related cardiac dysfunction incidence in cancer patients is imperative. Therefore, we performed a meta-analysis to establish the overall incidence of chemotherapy-related cardiac dysfunction in cancer patients. METHODS: We searched articles in PubMed and EMBASE from database inception to May 1, 2023. Studies that reported the incidence of chemotherapy-related cardiac dysfunction in cancer patients were included. RESULTS: A total of 53 studies involving 35 651 individuals were finally included in the meta-analysis. The overall pooled incidence of chemotherapy-related cardiac dysfunction in cancer patients was 63.21 per 1000 person-years (95% CI: 57.28-69.14). The chemotherapy-related cardiac dysfunction incidence increased steeply within half a year of cancer chemotherapy. Also, the trend of chemotherapy-related cardiac dysfunction incidence appeared to have plateaued after a longer duration of follow-up. In addition, chemotherapy-related cardiac dysfunction incidence rates are significantly higher among patients with age ≥50 years versus patients with age <50 years (99.96 vs. 34.48 per 1000 person-years). The incidence rate of cardiac dysfunction was higher among breast cancer patients (72.97 per 1000 person-years), leukemia patients (65.21 per 1000 person-years), and lymphoma patients (55.43 per 1000 person-years). CONCLUSION: Our meta-analysis unveiled a definitive overall incidence rate of chemotherapy-related cardiac dysfunction in cancer patients. In addition, it was found that the risk of developing this condition escalates within the initial 6 months postchemotherapy, subsequently tapering off to become statistically insignificant after a duration of 6 years.

Stage B Heart Failure Is Ubiquitous in Emergency Patients with Asymptomatic Hypertension.

Introduction: Hypertension is the leading risk factor for morbidity and mortality throughout the world and is pervasive in United States emergency departments (ED). This study documents the point prevalence of subclinical heart disease in emergency patients with asymptomatic hypertension. Method: This was a prospective observational study of ED patients with asymptomatic hypertension conducted at two urban academic EDs that belong to an eight-hospital healthcare organization in New York. Adult (≥18 years of age) English- or Spanish-speaking patients who had an initial blood pressure (BP) ≥160/100 millimeters of mercury (mmHg) and second BP ≥140/90 mm Hg, and pending discharge, were invited to participate in the study. We excluded patients with congestive heart failure, renal insufficiency, and atrial fibrillation, or who were pregnant, a prisoner, cognitively unable to provide informed consent, or experiencing symptoms of hypertension. We assessed echocardiographic evidence of subclinical heart disease (left ventricular hypertrophy, and diastolic and systolic dysfunction). Results: A total of 53 patients were included in the study; a majority were young (mean 49.5 years old, [SD 14-52]), self-identified as Black or Other (n = 39; 73.5%), and female (n = 30; 56.6%). Mean initial blood pressure was 172/100 mm Hg, and 24 patients (45.3%) self-reported a history of hypertension. Fifty patients completed an echocardiogram. All (100%) had evidence of subclinical heart disease, with 41 (77.4%) displaying left ventricular hypertrophy and 31 (58.5%) diastolic dysfunction. There was a significant relationship between diastolic dysfunction and female gender [x2 (1, n = 53) = 3.98; P = 0.046]; Black or other race [x2 (3, n = 53) = 9.138; P = 0.03] and Hispanic or other ethnicity [x2 (2, n = 53) = 8.03; P = 0.02]. Less than one third of patients demonstrated systolic dysfunction on echocardiogram, and this was more likely to occur in patients with diabetes mellitus [x2 (1, n = 51) = 4.84; P = 0.02]. Conclusion: There is a high probability that Black, Hispanic, and female patients with asymptomatic hypertension are on the continuum for developing overt heart failure. Emergency clinicians should provide individualized care that considers their unique health needs, cultural backgrounds, and social determinants of health.

The Role of Stem Cells in the Treatment of Cardiovascular Diseases.

Cardiovascular diseases (CVDs) are the leading cause of death and include several vascular and cardiac disorders, such as atherosclerosis, coronary artery disease, cardiomyopathies, and heart failure. Multiple treatment strategies exist for CVDs, but there is a need for regenerative treatment of damaged heart. Stem cells are a broad variety of cells with a great differentiation potential that have regenerative and immunomodulatory properties. Multiple studies have evaluated the efficacy of stem cells in CVDs, such as mesenchymal stem cells and induced pluripotent stem cell-derived cardiomyocytes. These studies have demonstrated that stem cells can improve the left ventricle ejection fraction, reduce fibrosis, and decrease infarct size. Other studies have investigated potential methods to improve the survival, engraftment, and functionality of stem cells in the treatment of CVDs. The aim of the present review is to summarize the current evidence on the role of stem cells in the treatment of CVDs, and how to improve their efficacy.

Placental senescence pathophysiology is shared between peripartum cardiomyopathy and preeclampsia in mouse and human.

Peripartum cardiomyopathy (PPCM) is an idiopathic form of pregnancy-induced heart failure associated with preeclampsia. Circulating factors in late pregnancy are thought to contribute to both diseases, suggesting a common underlying pathophysiological process. However, what drives this process remains unclear. Using serum proteomics, we identified the senescence-associated secretory phenotype (SASP), a marker of cellular senescence associated with biological aging, as the most highly up-regulated pathway in young women with PPCM or preeclampsia. Placentas from women with preeclampsia displayed multiple markers of amplified senescence and tissue aging, as well as overall increased gene expression of 28 circulating proteins that contributed to SASP pathway enrichment in serum samples from patients with preeclampsia or PPCM. The most highly expressed placental SASP factor, activin A, was associated with cardiac dysfunction or heart failure severity in women with preeclampsia or PPCM. In a murine model of PPCM induced by cardiomyocyte-specific deletion of the gene encoding peroxisome proliferator-activated receptor γ coactivator-1α, inhibiting activin A signaling in the early postpartum period with a monoclonal antibody to the activin type II receptor improved heart function. In addition, attenuating placental senescence with the senolytic compound fisetin in late pregnancy improved cardiac function in these animals. These findings link senescence biology to cardiac dysfunction in pregnancy and help to elucidate the pathogenesis underlying cardiovascular diseases of pregnancy.

Multisystem Inflammatory Syndrome in Children and Cardiac Involvement: A Quaternary Center Experience.

We prospectively analyzed clinical and laboratory characteristics associated with cardiac involvement and severe presentation in multisystem inflammatory syndrome in children. Of 146 patients, 66 (45.2%) had cardiac dysfunction and 26 (17.8%) had coronary artery abnormalities. Lower serum albumin levels, absolute lymphocyte and platelet counts, and elevated ferritin, fibrinogen, d-dimer and interleukin-6 levels were associated with cardiac dysfunction. Possible treatment complications were identified.

Physical and Computational Modeling for Transcatheter Structural Heart Interventions.

Structural heart disease interventions rely heavily on preprocedural planning and simulation to improve procedural outcomes and predict and prevent potential procedural complications. Modeling technologies, namely 3-dimensional (3D) printing and computational modeling, are nowadays increasingly used to predict the interaction between cardiac anatomy and implantable devices. Such models play a role in patient education, operator training, procedural simulation, and appropriate device selection. However, current modeling is often limited by the replication of a single static configuration within a dynamic cardiac cycle. Recognizing that health systems may face technical and economic limitations to the creation of "in-house" 3D-printed models, structural heart teams are pivoting to the use of computational software for modeling purposes.

AttGRU-HMSI: enhancing heart disease diagnosis using hybrid deep learning approach.

Heart disease is a major global cause of mortality and a major public health problem for a large number of individuals. A major issue raised by regular clinical data analysis is the recognition of cardiovascular illnesses, including heart attacks and coronary artery disease, even though early identification of heart disease can save many lives. Accurate forecasting and decision assistance may be achieved in an effective manner with machine learning (ML). Big Data, or the vast amounts of data generated by the health sector, may assist models used to make diagnostic choices by revealing hidden information or intricate patterns. This paper uses a hybrid deep learning algorithm to describe a large data analysis and visualization approach for heart disease detection. The proposed approach is intended for use with big data systems, such as Apache Hadoop. An extensive medical data collection is first subjected to an improved k-means clustering (IKC) method to remove outliers, and the remaining class distribution is then balanced using the synthetic minority over-sampling technique (SMOTE). The next step is to forecast the disease using a bio-inspired hybrid mutation-based swarm intelligence (HMSI) with an attention-based gated recurrent unit network (AttGRU) model after recursive feature elimination (RFE) has determined which features are most important. In our implementation, we compare four machine learning algorithms: SAE + ANN (sparse autoencoder + artificial neural network), LR (logistic regression), KNN (K-nearest neighbour), and naïve Bayes. The experiment results indicate that a 95.42% accuracy rate for the hybrid model's suggested heart disease prediction is attained, which effectively outperforms and overcomes the prescribed research gap in mentioned related work.

Comprehensive evaluation and performance analysis of machine learning in heart disease prediction.

Heart disease is a leading cause of mortality on a global scale. Accurately predicting cardiovascular disease poses a significant challenge within clinical data analysis. The present study introduces a prediction model that utilizes various combinations of information and employs multiple established classification approaches. The proposed technique combines the genetic algorithm (GA) and the recursive feature elimination method (RFEM) to select relevant features, thus enhancing the model's robustness. Techniques like the under sampling clustering oversampling method (USCOM) address the issue of data imbalance, thereby improving the model's predictive capabilities. The classification challenge employs a multilayer deep convolutional neural network (MLDCNN), trained using the adaptive elephant herd optimization method (AEHOM). The proposed machine learning-based heart disease prediction method (ML-HDPM) demonstrates outstanding performance across various crucial evaluation parameters, as indicated by its comprehensive assessment. During the training process, the ML-HDPM model exhibits a high level of performance, achieving an accuracy rate of 95.5% and a precision rate of 94.8%. The system's sensitivity (recall) performs with a high accuracy rate of 96.2%, while the F-score highlights its well-balanced performance, measuring 91.5%. It is worth noting that the specificity of ML-HDPM is recorded at a remarkable 89.7%. The findings underscore the potential of ML-HDPM to transform the prediction of heart disease and aid healthcare practitioners in providing precise diagnoses, exerting a substantial influence on patient care outcomes.

Brief report: Effect of cardiac multi-morbidity on COVID hospitalization outcomes.

BACKGROUND: The COVID-19 pandemic has stretched healthcare resources thin and led to significant morbidity and mortality. There have been no studies utilizing national data to investigate the role of cardiac risk factors on outcomes of COVID hospitalizations. The aim of this study was to examine the effect of cardiac multimorbidity on healthcare utilization and outcomes among COVID hospitalizations during the first year of the pandemic. METHODS: Using the national inpatient sample (NIS), we identified all adult hospital admissions with a primary diagnosis of COVID in 2020, using International Classification of Diseases, Tenth Revision, Clinical Modification codes (ICD010-CM). Coronary artery disease, diabetes mellitus, heart failure, peripheral vascular disease, previous stroke, and atrial fibrillation were then identified as cardiac comorbidities using ICD-10-CM codes. Multivariable logistic regression was used to evaluate the effect of cardiac multimorbidity on mortality and mechanical ventilation. RESULTS: We identified 1,005,040 primary COVID admissions in 2020. Of these admissions, 216,545 (20.6%) had CAD, 413,195 (39.4%) had DM, 176,780 (16.8%) had HF, 159,700 (15.2%) had AF, 30735 (2.9%) had PVD, and 25,155 (2.4%) had a previous stroke. When stratified by number of comorbidities, 428390 (40.8%) had 0 comorbidities, 354960 (33.8%) had 1, 161225 (15.4%) had 2, and 105465 (10.0%) had 3+ comorbidities. COVID hospitalizations with higher cardiac multimorbidity had higher mortality rates (p<0.001) higher MV rates (p<0.001). In our multivariable regression, these associations remained with increasing odds for mortality with each stepwise increase in cardiac multimorbidity (1: OR 1.48 (1.45-1.50); 2: OR 2.13 (2.09-2.17); 3+: OR 2.43 (2.38-2.48), p<0.001, all). CONCLUSIONS: Our study is the first national examination of the impact of cardiac comorbidities on COVID outcomes. A higher number of cardiac comorbidities was associated with significantly higher rates of MV and in-hospital mortality, independent of age. Future, more granular, and longitudinal studies are needed to further examine these associations.

The association between Chinese visceral adiposity index and cardiometabolic multimorbidity among Chinese middle-aged and older adults: a national cohort study.

Objective: This study aimed to explore the association between the Chinese visceral adiposity index (CVAI) and cardiometabolic multimorbidity in middle-aged and older Chinese adults. Methods: The data used in this study were obtained from a national cohort, the China Health and Retirement Longitudinal Study (CHARLS, 2011-2018 wave). The CVAI was measured using previously validated biomarker estimation formulas, which included sex, age, body mass index, waist circumference, triglycerides, and high-density lipoprotein cholesterol. The presence of two or more of these cardiometabolic diseases (diabetes, heart disease, and stroke) is considered as cardiometabolic multimorbidity. We used Cox proportional hazard regression models to examine the association between CVAI and cardiometabolic multimorbidity, adjusting for a set of covariates. Hazard ratios (HRs) and 95% confidence intervals (CIs) were used to show the strength of the associations. We also conducted a subgroup analysis between age and sex, as well as two sensitivity analyses. Receiver operator characteristic curves (ROC) were used to test the predictive capabilities and cutoff value of the CVAI for cardiometabolic multimorbidity. Results: A total of 9028 participants were included in the final analysis, with a mean age of 59.3 years (standard deviation: 9.3) and women accounting for 53.7% of the sample population. In the fully-adjusted model, compared with participants in the Q1 of CVAI, the Q3 (HR = 2.203, 95% CI = 1.039 - 3.774) and Q4 of CVAI (HR = 3.547, 95% CI = 2.100 - 5.992) were associated with an increased risk of cardiometabolic multimorbidity. There was no evidence of an interaction between the CVAI quartiles and sex or age in association with cardiometabolic multimorbidity (P >0.05). The results of both sensitivity analyses suggested that the association between CVAI and cardiometabolic multimorbidity was robust. In addition, the area under ROC and ideal cutoff value for CVAI prediction of cardiometabolic multimorbidity were 0.685 (95% CI = 0.649-0.722) and 121.388. Conclusion: The CVAI is a valid biomarker with good predictive capability for cardiometabolic multimorbidity and can be used by primary healthcare organizations in the future for early warning, prevention, and intervention with regard to cardiometabolic multimorbidity.

Survival and causes of death in patients with alpha and beta-thalassemia in Northern Thailand.

BACKGROUND: Thalassemia is the most prevalent hereditary anaemia worldwide. Severe forms of thalassemia can lead to reduced life expectancy due to disease-related complications. OBJECTIVES: To investigate the survival of thalassemia patients across varying disease severity, causes of death and related clinical factors. PATIENTS AND METHODS: We conducted a retrospective review of thalassemia patients who received medical care at Chiang Mai University Hospital. The analysis focused on survival outcomes, and potential associations between clinical factors and patient survival. RESULTS: A total of 789 patients were included in our study cohort. Among them, 38.1% had Hb H disease, 35.4% had Hb E/beta-thalassemia and 26.5% had beta-thalassemia major. Half of the patients (50.1%) required regular transfusions. Sixty-five patients (8.2%) had deceased. The predominant causes of mortality were infection-related (36.9%) and cardiac complications (27.7%). Transfusion-dependent thalassemia (TDT) (adjusted HR 3.68, 95% CI 1.39-9.72, p = 0.008) and a mean serum ferritin level ≥3000 ng/mL (adjusted HR 4.18, 95% CI 2.20-7.92, p < 0.001) were independently associated with poorer survival. CONCLUSIONS: Our study highlights the primary contributors to mortality in patients with thalassemia as infection-related issues and cardiac complications. It also underscores the significant impact of TDT and elevated serum ferritin levels on the survival of thalassemia patients.